'Following several crises, quantitative social scientists now worry about the validity of methods. Such developments have political implications. There may be greatest risk to progressive ideologies, these being predicated on the notion that politicians can improve society. If scholars worry about findings, how can we be confident that policy interventions are effective?'
I mean, the validity of the social sciences methods were, in quite a few cases, questionable. The reproducibility of such studies led to something of a crisis of their own, did they not?
Charismatic leaders with a Narrative will become the organizing poles of society; the notion of a greater shared Truth will fade further. People with the ability to think for themselves and the desire to expend their efforts towards real goals will be elevated beyond contact with reality, or burned as heathens trying to undermine the rest of the tribe.
The dirty secret is people don't base their decisions on academic findings. They make their decision and then search out findings that support it to use as arguments for it.
I passed my Masters on this basis. I worked out what I thought about the topic, then searched the journals for the required number of papers whose abstracts agreed with me.
For those who don't know, this is called motivated reasoning or confirmation bias. Once you can give a name to it, it's easier to notice it all around you. I'd argue that it's one of the biases that plagues humanity more than any other, our brains seem to be hard-wired to engage in motivated reasoning
I'm sure that applies in some cases, but it doesn't seem universally true. Personally, I hate exercising but I do it because the epidemiologists say I should. And I love drinking, but I don't because the epidemiologists say I shouldn't. Smoking has declined pretty significantly over the past several decades, no?
Optimistically, the hackjob happening in the social and other sciences will be used to launch a deep examination of epistemic practices. This does seem to have occurred in social sciences to some extent. There are no sciences so rigorous that they couldn't benefit from it.
But the hard sciences have also had problems with replication. It's worth reading the Structure of Scientific Revolutions by Thomas Kuhn; to some extent, science is socially embedded.
The social sciences are the only ones actually engaging in replication to detect the problems. The replication crisis in, say, software engineering research is not published but instead is implicitly understood by members of the community.
In grad school I was told to generally assume that the tool with the second highest line in the key graph was the best tool. The top line was invariably the author's tool and its results rarely translated to other experiments. But the tool with the second line was usable by somebody other than its original author on a different problem space.
Empirical SE research is part of the social sciences. The subset of SE research that doesn't push hard for collaboration with social science departments is doing just fine.
"I built a tool and it found this many bugs" doesn't feel like part of the social sciences, but these papers are regularly published in ICSE and FSE.
I listed Software Engineering because it is one of the fields I know well but is way less esoteric than the other one I know well (PL). You'll find the same kinds of replication problems in POPL or OOPSLA papers too.
I suspect that other subfields don't fare any better. I certainly hear from my ML friends that a huge portion of ML results are untrustworthy.
> "I built a tool and it found this many bugs" doesn't feel like part of the social sciences, but these papers are regularly published in ICSE and FSE.
Those papers have lots of issues, especially cherry-picking and narration of the results' significance.
But the core claim -- "I found N bugs in the following codebases" -- is generally reproducible.
More rigorous disciplines should then explicitly and loudly disclaim any relationship with those fields driven by agenda and sloppy methods, and the universities should disown them and kick them out from under their roofs.
Scientists in the natural sciences/mathematics criticizing the social sciences (and also the humanities) is literally a trope. Natural scientists have been criticizing the issues in the social sciences for decades. In fact, a lot of the criticism that uncovered the replicated crisis originated in those communities.
I think that the existence of leetcode interviews, where tech companies ignore your background as much as possible, and want to see the skills upfront, is a condemnation of education.
It's essentially saying, we don't believe your degree says anything about your ability to perform the job.
The only reason academia hasnt been completely uprooted, is:
1. Some sects of society use academic prestige as a product. i.e. this harvard educated mckinsey consultant will optimize your business! Or, this harvard educated financier will invest your money carefully!
2. There's no way to have some leetcode like test for most jobs.
3. There used to be more signal in academic credentials, and older sects of society still believe those signals exist. Its the same with doctors, older generations treat doctors like infallible royalty, younger are much more skeptical
theres a huge caveat that some top people in the world do end up at top academic institutions. its just they keep mixing in these political appointees, agendas, etc
> It's essentially saying, we don't believe your degree says anything about your ability to perform the job.
Unfortunately I have worked with people with a master’s in computer science from an american university who couldn’t write a coherent sentence in English. Let alone write code or design a system.
I’ve also interviewed people with illustrious careers who just weren’t a fit for the role they applied to.
Yeah coding is funny, because the code has to work. Theres no getting around it, and most resources for understanding how to get things to work are available on the internet.
I once met an “angular 5” developer. Coding interview I started on the whiteboard.
var a = 1;
a = 2;
Before I could write anything more (this was just setup) the person pipes up “that’s false!” We went through the rest of the interview but I just couldn’t believe it. The individual had been working for a government office as a software developer for 5 years or so before this.
I have no idea what this persons work day looked like but still shake my head when I think about that interview.
If you think like a mathematician, "a" can not be equal to 1 and 2 at the same time. There are languages that actually use := for assignment to emphasise it's not equality.
This is due to the warped incentives in Higher Education. Universities get more tuition fees from accepting more students, and achieve better in national rankings by having higher graduation rates.
Professors are stuck in the middle: asked to teach unprepared students, and forced to pass many who are not suitable.
The people it hurts the most are the students who are actually capable, and put the time in to excel.
There is absolutely a way to have leecode type tests for most jobs. We know that the single best predictor of job success and performance is IQ. Academics act mostly as a signal in some industries where you just back into IQ ineffectively by creating certain filters for pedigree.
instead of IQ test -> competence signal
you have:
SAT/ACT = IQ Test -> university acceptance criteria -> degree/credentials -> competence signal
> We know that the single best predictor of job success and performance is IQ.
Citation for this? As far as I know IQ isn’t a measure of intelligence (because intelligence is hard to define, let alone come up with a single number that quantifies it!)
> Citation for this? As far as I know IQ isn’t a measure of intelligence (because intelligence is hard to define, let alone come up with a single number that quantifies it!)
All you have to do is get a figure that mostly correlates fairly well to most of the phenomena we might consider intelligence, and it works well enough for many purposes, even if it's not measuring any of those others.
That's a far cry from "We know that the single best predictor of job success and performance is IQ."
I think when people say things like that, what they mean is "what simple number is the best predictor of success", which begs the question that a simple number can be a good predictor at all. Keep in mind that something can be the best merely because every other option is even worse: in practice, the best predictor is a really terrible predictor. So bad, in fact, that a five-minute conversation with somebody will tell you more about their ability to succeed at a job than knowing their IQ.
> So bad, in fact, that a five-minute conversation with somebody will tell you more about their ability to succeed at a job than knowing their IQ.
But when you try to put a number on that five minute conversation it turns out that the number is worse than the number provided by IQ tests. Otherwise the simple number from conversations would be well known to be a stronger predictor, but nobody has found such a result.
If we forget about the concept of intelligence for a while, there is a lot of research that points to the direction that whatever the quality that IQ tests measure is, it correlates strongly with financial success, health and a bunch of other things that are often considered good. Whether it is the cause or effect is also anyone's guess.
I've seen rumblings out there[1] that "whiteboard interviews" can be cast as "pre-employment tests" and litigated against in a "Duke Power" sense. Not to endorse that and I'm not sure anyone wants to hear that.
Yeah this is a good point. Another issue though is the SAT is a snapshot of your IQ, but also your general life state at one point in time. I think it's cruel to have that follow you for life, especially if you are going through difficulties as a teenager.
it's not consistently referred to as "IQ" or intellligence, typically the measurement is called "g" or "g factor" or "general mental ability" and over the last couple of decades the meta-analyses just keeps pointing towards g being the single best predictor of performance.
IQ tests are stupid and have large language components to them. The large language components of the tests mean they essentially boil down to culture tests. If your parents were in the in group, you speak scientistese.
Your in group membership is what propels you forward in your career, not your intelligence. Race and Gender are predictors of career success as well.
Any proponent of IQ, I'd challenge to take an IQ test in Chinese, Irish, or AAVE.
If you were trying to get a job in a Chinese workplace with chinese coworkers that spoke chinese, taking a chinese IQ test would be a great predictor of success in that group. Doesn't mean you'res 'stupid', but my giant english IQ would be useless reading docs and taking meetings if they were all or majority in chinese.
> We know that the single best predictor of job success and performance is IQ
I'm not sure a construction company wants a bunch of people with 140+ IQ standing around all day leaning on shovels waiting for gravel to shovel into little holes. I'm pretty sure those employees will just quit or break something on purpose just for something to do. In fact I've seen this with my own eyes.
Maybe you're proposing binning people by IQ instead? Where groups of people who fall in certain ranges of IQs are sorted into different jobs.
But again, I'm not so sure that Walmart wants to hire a shelf stocker with an IQ between 88-95 if that person has oppositional defiant disorder and/or a tendency to steal from their employers.
If you think that you can distill the essence of an entire human down to a single variable and rank them accordingly for jobs, go for it man, but I have a sneaking feeling that it isn't going to work.
There are a ton of people on construction sites with very high IQs that prefer manual labor, physical problem solving or managing divergent teams and contractors to accomplish a project. The notion of clustering people into professions for anything other than their desire to participate in the profession and ability to perform the tasks is a fools errand.
Thanks for this. I'm in Software because that's the best way for me to provide for my family. If I could have my way, I'd be outside working on making things that last longer than a couple of years.
> I'm not sure a construction company wants a bunch of people with 140+ IQ standing around all day leaning on shovels waiting for gravel to shovel into little holes. I'm pretty sure those employees will just quit or break something on purpose just for something to do. In fact I've seen this with my own eyes.
I'm quite convinced that a typical construction site would benefit a lot from employees who would be smart enough to notice inefficient processes and plain mistakes, and take some initiative to fix the problems. And management who would believe the employees, but that is probably never going to happen.
Sure, let me use Raven's progressive matrices to test whether someone has the ability to make plans, stay organized, keep on task and interface with others in a productive way.
Sounds like a smashing idea, I'm sure you'll kill it in business.
I'm going to take a different path from the other responses so far. The claim that IQ predicts job success seems to be contentious among a lot of people, but as far as I can tell, it is fairly well supported and other ways of evaluating candidates are at least as noisy anyway, short of professions with the sort of concrete standards that allow for meaningful licensing or something like being a military officer where they're going to train you and evaluate your performance in context for 4 years before ever giving you a real job anyway.
However, thanks to the way mental traits get distributed, a fairly small proportion of the population is ever going to have a high IQ. Roughly 16% of the population at any one time will have greater than 1 SD north of median. Less than 3% will be greater than 2 SD.
More people than that need to have jobs. If you're going to insist only 97th percentile people can work for you, you need to be offering 97th percentile salary. Currently, that is around $220,000 a year in the US. "Most" jobs can definitely not offer that.
> fairly well supported and other ways of evaluating candidates are at least as noisy anyway
It's on you to back up this claim. And the reason had better not be 'oh a bunch of tech companies do it' when there are entire fields from psychology that do research on this exact question, and they consider things like personalities, etc.
You also might be confusing higher-iq job scopes for job success.
Plus financial backing, and/or inside influence on the process. Cheating is rampant is some cultures, and I guess some people even basically but their whole degree
> We know that the single best predictor of job success and performance is IQ.
WRONG. WRONG. WRONG.
IQ predicts how fast you learn shit, not how well you do on the job. Plenty of studies from the fields of personality/social psychology/psychometrics talk about this, get out of your narrow SWE field and read up on these subjects. This IQ=job success belief is simply SWE self ego-stroking.
>We know that the single best predictor of job success and performance is IQ.
Wow, so many people react so sharply to this, I'm not sure why. May be there is an inherent belief that all one has to do is work hard and success will follow.
Minor nitpick - I think performance has a good correlational with IQ, I think less so a job, because a job also generally requires high conformity (not an enviable trait IMO)
Even if academic qualifications lose their value, there is still value in the actual education provided by academia. If I want to learn a topic really well, especially a more theoretical rather than applied topic, going to do a 3 year degree on the topic at university is a pretty good starting point.
Higher educations origins are in insulating Bourgeoisie kids from working class life.
As it became clear the people had lost belief in god kings, aristocrats began paying the church to educate their kids and confer nonsense degrees the proles could not falsify.
It was not hard learning guitar on my own. We create a lot of carbon mess for junior to get to an official guitar degree.
There is a whole lot of unnecessary LARPing deference to wealthy people who don’t do much of the real work keeping themselves alive.
It’s not a sustainable social meme to tighten the screws on the masses while handing their own kids the keys to the castle. 800,000 sworn LEO in the US, beholden to a paycheck and retirement account. None of the people at my local bank own that bank anymore. Why is my agency propping up someone else’s grandpa?
The current university system (I can only speak to US here) was made post-WW2 to produce employees for office work in large corporate bureaucracies. The degree insured that you could show up on a regular basis, go where you're told, learn how to perform arbitrary tasks whether you thought they were necessary or not, and communicate effectively about this. They also provided, at the larger universities especially, a lot of training in how to deal with a bureaucracy.
All of this was absolutely relevant in 1950 for working at a large corporation, in a white-collar job.
The more recent job market doesn't look much like this, but then good training for the current job market would probably not call for an institution that looks much like a university. It would probably call for something more like trade schools and apprenticeships, with guilds to protect the apprentices from poor treatment (something that, for example, Ph.D. students are sorely lacking). It seems unlikely that universities can adapt to a situation that primarily requires that they go away or at least become much smaller, to be replaced by a different system.
You could argue the reverse. A lot of leetcode questions are/used to be tests you've studied CS, and largely unrelated to day-to-day software dev (e.g. the infamous "invert a binary tree" question).
Therefore, they mainly ensured companies hired people from similar university programs that the test givers also attended.
As much as I hate leetcode, I think it's imperfect but works. I think the biggest tech companies have rigorously tested it, and come to the conclusion that for mass hiring and removing bias/discrimination from the interview process, it's effective.
Knowing how to invert a binary tree is proxy for knowing how to do other none-trivial tasks in your domain of choice. It's so much better than the alternatives for interviews. Which are questions like, obscure trivia, spot-the-bug, how-many-piano-tuners-are-in-chicago, or two-day-long-mini-projects.
Everyone is optimizing for getting the most information in the smallest amount of time. Algorithm questions do that. The interviewee knows that they are going to get algorithm question, and most places tell them ahead of time what the nature of the questions will be. So interviews should be an easy cakewalk that everyone can pass, but they aren't.
I think the point was how can you say Leetcode is rejecting Academic experience when the majority of questions are straight from undergrad DS and Algo courses?
>So interviews should be an easy cakewalk that everyone can pass, but they aren't.
For a person with no CS degree this is definitely not easy and being flippant and saying it is is disingenuous.
It's rejecting academic _credentials_ as a proxy for programming competence. Say what you will about it, Leetcode requires you to demonstrate actual capability, and it's used precisely because a CS degree in and of itself does not accurately signify the presence or absence of that capability.
But it doesn't, it reflects your training in solving DS and Algo problems from undergrad CS curriculum.
I think its almost universally agreed at this point that Algo interviews don't have anything to do with day to day work and don't demonstrate development ability.
It's frustrating in a way. Perhaps I'm in the minority, but I'd say my well graded Master's Thesis on a complex subject from a top university is much more telling about the type of work I'll create than an hour long leetcode interview will.
It seems no matter how many great projects I make, or quality papers I write, that's second best to 10 minute logic puzzles for a growing amount of companies.
The problem is that many graduate degrees are very research focused and they don't say a lot about the skills many company's may need from software developers. Jobs I've worked that used Leetcode simply wouldn't need you to do the kind of work you did in your thesis. So they shouldn't be requiring your degree in the list of candidate requirements, but they also shouldn't place a lot of value on it if they're not doing that kind of R&D. I've met a few computer science Ph.D's who showed up on day 1 and appeared to have the coding skills of someone who used BASIC for an assignment in their "Technology" class in high school. One wonders if they're even the kind of people who got pushed through a program so their advisor could stop dealing with them. Maybe they are great at researchers, and abstract thought, and maybe they were very well versed in writing code a decade ago. Maybe they're just not good at it. But either way stuff like this isn't made up: https://blog.codinghorror.com/why-cant-programmers-program/. Leetcode comes about to deal with that. Not saying it's a great solution, but don't dismiss the problem.
Computer Science departments have always said that they do not prepare students for work in IT [0].
As with most development team leaders, I have interviewed and employed CS graduates who are woefully unprepared for the reality of a job writing production-level code.
I don't see this as a condemnation of education per se. More that the common concept of education (that it prepares young people for their careers) is completely misaligned with academia's concept of education (that it trains young people in how to think, and how to conduct research).
This might vary by school, but my undergraduate university had, in my opinion, a great computer science program which attracted many big-name companies to job fairs. There was definitely a focus on teaching practical and relevant things using relevant technologies. For those interested in research, there were also undergraduate research opportunities.
IMO this is what a university education should look like for most people in order for it to stay relevant. There are otherwise far more too many people attending universities relative to the demand for researchers.
This is the best model. I have been advocating for this forever.
The university that I got my actual degree from was something that a SV company would scoff at. But, the education they were able to scrap together was far more effective in my day-to-day work than prior education I had received at a far more prestigious institution.
Perhaps it was just me, but it always seemed like the less money I spent on my education the more effective it became.
I dont really have any qualifications, never been to uni, in fact I clashed with the educational establishment, but I've worked on some very high profile systems, pioneered novel uses of technology and continue to do so.
Remember it doesnt take any qualifications to set up a business.
The academic culture of "we teach you to think not how to work" only makes sense for a world where the majority of people entering university are from wealthy, elite families such that the economic impact of attending college is negligible, and just an accepted tax to confirm social status. This was true for almost the entire history of college until after WW2.
At those points in history the degree was worth it because it was a signal of your social standing. You would walk into the office as the boss simply because you had a degree.
Today college is not elite. The vast majority of US high school students now go to college. 70% of those students take out loans to afford education. Because it is no longer elite "teaching you how to think" is no longer a great value proposition. Not to mention that most of the new grads I've met have failed to learn "how to think" as well as having no practical skills.
Academic education is not about what the university chooses to teach but about what the student chooses to learn. If you finish the degree by completing only the minimal requirements, that's your failure as a student. Many people need more guidance in their studies, because their motivation to learn for the sake of learning is not strong enough. For such people, many countries offer a parallel track of vocational higher education.
Also research shows that "colleges you've been accepted to but didn't go to" correlates the same to future income as "colleges you went to". I'd say 80% of the signal value of college is the initial sorting vs the education.
Aren't there even earlier sorting events that have predictive value of what colleges you might be accepted to? I thought I read somewhere that "father's income" is the single best predictive signal of the entire chain of events that leads to one's prosperity and career success. If true, even college admission doesn't signal much in and of itself.
My school had plenty of "vocational" classes available to CS (and other) students. The school even made an effort to keep the pre-reqs simple for these so that students from other disciplines could give them a shot (and maybe so that students could prepare for internships). Classes like, iOS development, back-end web development, intro to data science, etc.
I'd be surprised if most universities didn't offer something similar. Even students at Ivy League school must want to get together with other students and learn to build useful software during their first year.
Learning how to code is not the same thing as learning how to write commercial software at production level. There are lots of ancillary skills that must be mastered (git, testing frameworks, cloud deployment), lots of concepts that must be learned (dependency injection, the rule of 3, CPS, etc), and soft skills that must be mastered (how to accept criticism of your code, how to review other people's code, how to have a technical argument without getting emotional, how to tell your boss they're wrong).
Like most professions, there's a lot of "extra" stuff around the core competency. Knowing Excel does not make you an accountant.
You'd be surprised how much of that you actually need to actually get a software project off the ground and into customer's hands.
I've come into projects as the architect for refactoring what was built by someone who had only just learned to code. It was bad, sure, but they were bringing in enough revenue to hire me and get things on course. All with 0 knowledge of devops and 0 lines of test code coverage.
The question becomes at what point do we expect companies to train people and what point do we stop foisting that on universities? This ties into the bigger goal of what the purpose of university is and should be, but I personally think companies need to step up and start training again instead of expecting universities to cover most things they want/need.
Three summer internships is roughly a year of industry experience, especially if they are done at 2 (but not 3) different companies.
Actually, those three 3 month engagements can constitute several years worth of experience if they are done with excellent mentors at good companies. Reasons:
1. You see several teams, several projects, several codebases, without having to spend an awesome amount of time at one place. How many engineers work with multiple teams and companies in their first year (without one of those experiences being terribly catastrophic)?
2. You get the interesting meaty projects, or get to work on prototyping projects, but are also expected to contribute to the existing code base (or at least build on top of it). You participate in meetings, give presentations, etc. Basically, you see an entire compressed project/product lifecycle but embedded in an existing codebase.
3. Most importantly: Doing 1 repeat internship is super valuable. Spending 6 months at a place in 3 month increments with 9 months in between is an exceptionally unique experience in terms of understanding how orgs work and evolve. Most engineers don't get to experience until they are in the consulting portion of their careers.
University students in CS should do as many internships as possible, and universities should be more proactive about finding a way to mock summer internship experiences for students who do not get any internship offers.
Atlassian made some comments like "Australian universities aren't teaching devs what we need them to know" a few years back. It triggered some discussion, but not nearly enough along the lines of "well maybe you should train people in what you need them to know then?"
As an industry, we're utterly crap at employing juniors, or training our staff. We expect everyone to have X years of experience and then get surprised when devs make technology choices based on what's good for their resume, not what's good for the business.
there's a full rant I have for whenever this subject comes up ;)
As someone who moved countries to do a technical masters (Theoretical Physics and Applied Maths) who has to pivot to tech (sadly doesn't seem Ireland recognizes my US teaching credentials or 5 years experience) for a while, I'd be interested to hear the rant as well as how I could better prepare for interviews, etc.
Xavier Niel, a (self-made) French billionaire, founder/owner/president of a few tech companies, said the same thing. And as a result he founded a series of schools (called 42) to "fix" that and provide a more realistic and practical education, focusing on tools and problem solving and critical thinking and industry experience through long internships. Completely free of charge for students.
As an alumni (kinda), it was awesome and IMHO has served me very well in my career.
College was never meant to be and I don't think ever should be Vocational school. Ironically things like Bootcamps have cropped up that in theory teach the vocational part but are pretty disrespected in the industry because the grads didn't learn DS/Algo.
To me that sounds like a company problem, and not something that should be foisted on to the universities to deal with. Perhaps it'd be better if we had more trade school focused places for a wider range of jobs instead of forcing the universities to deal with it all.
But, really, if company wants to retain people after training, maybe make it worth it to the people to stay.
The only reason this happens is because the company doesn't then update the employee's salary to be competitive with their new experience.
Lots of organisations seem to think that if they have to train an employee, then there should be some kind of discount on the salary for that employee. This is totally the wrong way of looking at it.
Training your staff in what you need them to know means that they have a consistent view of the subject, practices, etc. No more "but that's how I've been doing it for 2 years in the last place" or "I taught myself and discovered this way of doing it and I think it's cool". A junior employee who was trained in the exact tech stack you're using is more valuable than a mid (or even senior) who has random experience.
Not to mention, if your employees trust that you'll train them in what they need to know, they're massively less likely to pick technologies based on resume need. And massively more likely to stay with you.
No educational institution will build your corporate culture. And how code review or technical discussion looks like has way more to do with your culture then with whatever went on in school or previous employer.
Also, it should not take long to train someone git or test framework.
My degree dedicated an absurd amount of time to software engineering. And I graduated a while ago. Two of those courses required completed projects in groups, with documentation, a project management plan, VCS, deployment, testing, and a presentation at the end. Plus, we had a capstone engineering project which was essentially all of this, but solo.
My personal option was they were wasted courses. The learning was in the coding, not project management and documentation.
That may be, but when I think back to some of the nonsense classes I took as "breath requirements" to make sure I was well-rounded enough to be a CS grad there was definitely some room in there to teach me how to use git.
My biggest issue with new hires is that they can't write.
I can teach you how to use git in an afternoon. I can't teach you how to write a thorough but concise email about a complicated topic. I can't teach you how to give a good presentation. (Or, I can, but it will take a lot longer than teaching enough git to get started.)
(To be clear, all CS departments should teach students how to use git as a component of the intro programming sequence.)
Well that's embarrassing. Truthfully though, an Android keyboard with a functioning "swipe" algorithm might be more effective for this one. I swear this used to work way better 5 years ago.
> it trains young people in how to think, and how to conduct research
But they don't. If they wanted to students to think more deeply, there would be more of an emphasis on formal logic, developing proofs, etc. rather than "write this in assembly." If they wanted you to conduct research, you would...conduct research.
STEM degree fields are so obviously career-based. There's a reason Merck internships go to biology students, Lockheed internships go to aerospace students, Google to CS, etc. But when people call out universities on how poor of a job they do, they suddenly claim career-based education isn't the goal. It's a widespread CYA move by vastly overpriced universities.
>If they wanted to students to think more deeply, there would be more of an emphasis on formal logic, developing proofs, etc. rather than "write this in assembly." If they wanted you to conduct research, you would...conduct research.
The claim that a university education doesn't do this feels very subjective. My CS course did all of those things. Every student was required to do a research project in their final year for a significant part of that year's credit.
HN comments on CS degrees are always a hot mess because quality in the United States is extraordinarily variable.
At the high end, you have places like MIT/Stanford/UIUC//Harvey Mudd. As far as I can tell, none of the bad stuff that's said in these threads is even remotely relevant to the programs at those places^1.
At the low end, you have branch campuses of state universities and small colleges where half or more of the CS courses are taught by mathematicians who did not study CS, have never worked on even academic code projects, and have never worked as anything other than an academic^2. This is pervasive in Data Science. You're way better off with a boot camp than a data science sequence taught by a desperate pure math PhD taking whatever work they can find.
And there's everything in-between.
A lot of these debates are probably happening between folks who went to good programs and folks who went to mediocre/bad programs. Not all, but quite a lot.
So, when reading comments on HN about how useless or wonderful a CS program was, always ask (at least rhetorically) "where did you go?"
I gave the big famous names because that's the easiest way to make the point. There are tons of really high quality programs whose names you won't immediately know. My intention here is not elitism... BUT!...
It is 100% true that the quality of CS programs is incredibly varied. Way more than it was even 10 years ago. The rapid increase in enrollment and unwillingness to pay even half decent wages for CS faculty has caused an explosion of what I would characterize as fraud in CS higher ed.
So, in the spirit of helping parents identify good programs without depending on name recognition/elite signalling alone:
When deciding if/which college/university to send your child to, carefully read through CS faculty bios. Ideally there will be a good number of faculty with street cred in both academics and industry. In addition to checking out CS faculty buios, also check out the names of instructors in previous years' course schedules. For example, make sure that CS/Data Science courses aren't being staffed by math folks unless those people have significant industry experience in addition to their math phd, or work in an area of applied math where they're doing lots of coding, etc.
Checking who teaches the courses in archived course schedules is more important than department bios! The department bios are a first check, not the final answer. Here's why: at many places you'll have a few half decent CS faculty who are just "fronts" for a department that is mostly staffed by way lower quality labor. It's the EXACT same bait and switch as consulting shops who have super experienced principal/senior-level engineers participate in the sales pitches and once the ink dries you're working with cheap grunts in a body shop.
Three things to watch out for in particular:
1. Non-CS (usually math) phds without substantial industry expertise. They're teaching tons of intro DS/CS courses instead of taking a math job in industry or academia for a reason.
2. Folks with an online masters and maybe a year or two of full time industry experience.
3. Tons of CS courses being offered in the evenings or early morning by faculty whose names don't appear anywhere on department websites (these are industry workers doing ad junct labor... they can be EXCELLENT, and if you get a course taught by one of these people in the middle of the day it's often a gold mine. But if they're always teaching around the 9-5 schedule it signals that their employer considers this a side gig and the course's quality is probably going to depend on how busy things happen to be that quarter at the instructor's "real" job. Okay as an occasional stopgap or an option, but a huge warning sign if this is a standard modus operandi for core courses. Teaching well is a big job; doing that plus engineering wi...
All programs, not just CS, have widely varying quality levels, probably leaning toward "bad", on average (there are a lot of colleges and universities in the US).
Fussell (and probably many others, but I've read him) blamed the rapid, great expansion of colleges and universities when the GI Bill injected a ton of money and eager new students into the system after WWII. He wrote that in 1983, but the system still seems to be reeling from that, and it may simply have stabilized (perhaps unavoidably, hard to say) at a much lower average quality level than before. Generally, institutions that existed before the war are still very good. Ones founded or converted (from, say, teaching colleges) after are much more hit-or-miss.
CS was "equally bad" to other not great fields in the aughts. It has gotten exponentially worse as enrollments have exploded.
CS is embarrassingly bad even relative to the already low standards.
I'm not exaggerating when I say that many computer/data science programs are 100% staffed by pure mathematicians who both have never done academic work in computer/data science and also have never worked a day in industry.
Find me a single mathematics department that offers a BS in Mathematics and in which 40+% of courses are taught by failed psychology PhDs. That's the state of CS at many institutions.
Again, I take your point that everything is not great. CS is a whole order of magnitude worse. Even at places that aren't great.
You are making a very important point in that program content and quality can vary greatly between universities. However, you then go on to specifically recommend the kind of program that has less to do with classic Computer Science and more to do with Software Engineering or development.
The person above you complained there weren't enough proofs in CS degrees, so they probably attended a program that was more focused on relevancy for the industry, while I and others attented programs very much geared towards academic research and theoretical CS, which contained a large amount of maths, often taught by math professors, and involved proofs in pretty much every course, even things like Intro to OOP.
Both of these programs have their place, I'm very glad I attented a program that was very theoretical, since I was able to pick up job skills on the side, while the things I learned in my degree I would have probably largely not been able to teach myself.
> However, you then go on to specifically recommend the kind of program that has less to do with classic Computer Science and more to do with Software Engineering or development.
No, I do not. Is that really how you would describe any of the specific institutions I mentioned?
A good program should have some of both, and two equally good programs could emphasize one or the other more. All of the positive institution examples I listed have very rigorous theory requirements in their undergraduate curriculum, for example.
> ...which contained a large amount of maths, often taught by math professors, and involved proofs in pretty much every course, even things like Intro to OOP.
The problem is one of quality, not the "theory vs practice" axis.
A mathematician can do a great job at teaching pretty much any CS course. But, also, within the last 10 years, a CS/DS major staffed largely by mathematicians or folks without terminal degrees has become a VERY predictable sign of a low-quality department. These two things aren't contradictory.
Have you looked at the composition of CS departments at unselective regional institutions, or CS faculty ads for such places? If not, consider this exercise. Things have gone downhill fast in the past 10 years, and the current situation in CS for regional colleges and universities is very much "caveat emptor".
I know many well educated STEM professionals who rigorously apply critical thinking skills to their profession. They use the scientific method to discern truth from nonsense.
Outside of their profession, they uncritically accept silly ideas as the truth and throw all logic and reason out the window.
The courses that teach SE tools (MIT's Missing semester) are well received. I can understand the resistance for focusing on specific frameworks or dumbing down the syllabus.
What I think is there deserves to be one or two full pledged software engineering courses, teaching how to use testing, version control, software structure etc.. As always, you can start from basic commands / usage and reach to general concepts, it isn't that hard.
And actually I believe US and European academia, at least the Ivy league and second tier colleges, do a decent job at teaching many required concepts. Come to a country like India, and you will see a C programming course that doesn't cover malloc or function pointers, a data structures course without proper introduction to algorithm complexity or difference between abstract data type and implementation, a java course that never properly teaches subtyping. I think students in US graduate decently equipped to write real world software compared to us. At least, I learned a lot of things by reading notes and Ppt of US universities.
(most Indian colleges are woefully inadequate in teaching even the basic concepts for writing software, despite the CS courses being named CSE (comp sci and engineering), not just CS. Incompetence runs to the root in education system except few elite colleges. From that perspective I think CS depts saying that is a first world problem. Sorry for the rant.)
> older sects of society still believe those signals exist.
I'm only in my forties but it's incredible how much this has changed in my lifetime.
I remember talking to an intern a few years ago and they made a comment about what a joke Columbia is (in regards to master's students). I was shocked because when I was a teen Columbia was seen as incredibly prestigious. I argued with them that Columbia is a really prestigious, well regarded school, but they and a few other interns just laughed and rolled their eyes.
Looking into it more it became obvious how this view had changed. It turns out Columbia, like many top tier schools from when I was a kid, has basically turned into get fancy version of a degree mill for master's students. Even though the school boasts some impressive faculty in many departments, it's also clear, based on the grads from there I have worked with after this conversation, that very little of that prestige is passed on.
As someone who used work in academia, it's wild how rapidly the entire system has decayed. From publisher or perish culture creating a mountain of non-reproducible work, to schools across the spectrum rushing to exchange credibility for cash. There have been so many systemic errors made that I don't believe academia will recover.
I suspect we'll see a fairly massive contraction in higher ed in the next decade or so.
Columbia also has the School of General Studies for non-traditional undergraduate students. Tuition is $58,440 an academic year, not including their estimated $26,010 cost of living, and they don’t offer much financial aid.
This may be a phenomenon limited to the tech field.
In many other fields that have advanced degree requirements, companies care far more about where you went to school and who you studied under.
For example - I have a friend that is an occupational therapist. They've had 5 different jobs in the last 10 years. Every single interview they've done has been mostly just a meet and greet. No real difficult questions, no tests, no trial periods. They just applied, the company saw their degree and experience, and the interview was simply there to make sure they could work together.
You’re assuming that the purpose of higher ed is to teach job-relevant skills. That is false. Higher Ed is an apprenticeship program for creating new instructors and researchers. Most people stop that process early before finishing for a variety of very valid reasons. There’s no reason to expect a degree to exactly prepare folks for specific jobs in industry.
It turns out that there’s very high correlation between the characteristics that make successful students and those that make successful workers. So a degree is still a useful signal during hiring, but it doesn’t certify a specific level of competency or skill set.
The purpose of education should not be the attainment of credentials, but rather the attainment of the ability to "do a leetcode interview". Institutions being given license to grant credentials is a more or less completely separable problem from this.
No university has any incentive to say no to someone who wants to pay 200k to have you grade some homework for a couple of years, as long as they aren't at capacity, and moreover very small incentives to fail them.
The irrelevance of the paper as a signal is the solution to this problem.
Not sure if this is a European thing but in the German speaking countries of Europe there are universities and vocational universities. The first focus prepare you for an academic career and the second prepare you for entering the work force (with some academic knowledge in case you need it in the industry or want to pursue an academic career).
I think this makes a lot of sense and we have a system that allows you to get a well paying middle class job by completing a vocational education and offers paths to get higher education from there or even switch to the academic track. This always made sense to me and I think it's crazy how this is in other countries where the choice is going to University or learning your profession on the job.
Except that universities now prepare you for leetcode and those who studies in them do better at leetcode. By that I mean that there are actual classes to train you leetcode like exercises.
On the other, preparing for the test is not gaming it. Fundamentally, if there is a test, it is entirely legitimate and expected to prepade for it. Especially when the test measures skills you rarely use outside of test.
I've understood that the original idea of the Google interviews and others was to see if the applicant can write code at all, has been awake at second year CS class and can apply the ideas on the fly. The idea would have been that good candidates would be able to pass the test anyway. Of course it doesn't work if people start preparing a test that's supposed to be a proxy for other skills. For what it's worth, I've heard a rumor from Google that their interview system used to be quite OK at predicting employees' career development but competitive programmers consistently perform under the expectations because they've been specializing for events that are just like those interviews.
Leetcode interviews don't showcase software engineering skills, they showcase your ability to solve leetcode problems. Those are two very different things
> It's essentially saying, we don't believe your degree says anything about your ability to perform the job.
I had a group project in 4th year university, in a very difficult math-heavy advanced graphics course, and my partner provided me with his half of the project and it was all global variables named A through Z, with a few A1,A2,AA,AB thrown in, and reused extensively for different purposes.
His code actually worked but it surprised me that someone could do 4 years of university (in a good CS school) but have almost no talent for actual coding.
There's a few fields, such as software engineering, where bullshit is in the long run difficult to hide. At the end of the day, you can either build a thing that does what people want or you can't. That is not true of most other fields. If your ideas about e.g. how to teach kids to read are wrong, it may be a long time before you're found out: https://www.nytimes.com/2021/09/03/opinion/kids-reading-spel....
Don't discount how long it takes for a company to uncover a mistakenly hired "Brillant Paula Bean"[1]. I know someone who literally can't code but can talk a good talk and has those soothing and smooth "Ivy Leaguer" mannerisms that executives and hiring managers just love. A total bullshitter. Most BigTech can filter these people out at the interview stage, but evidently smaller companies can easily be fooled. As soon as you're discovered, you can pretty easily hop to another "victim" company, especially during times like now when the job market is hot.
Or the leetcode interviews are an attempt at a second layer of screen. Looking at the school people went to may not be a great predictor of their differential success versus everyone else who went to a similar school, but it can give a good signal (on average) versus someone applying without one.
In the same way that height among professional basketball players may not be a great predictor of their performance relative to other players, but you don't see too many 5ft players eithers.
Speaking as someone who tries to elevate the careers of others based on their potential independent of their credentials…
I think if you’re working with really advanced topics, the credentials start to be meaningless, because the important fact is whether a candidate can truly work with complex concepts/technologies. You expect the candidate to come in already knowing what they need, and you don’t need any assurance that they’re “trainable.”
But for most of us here in the middle of the pack, the degree is more meaningful because it shows that at the very least, a candidate has been exposed to slightly higher-level concepts. As an example, when you’re trying to get someone to step up out of a help desk role into an analyst/developer role, that’s a lot easier to achieve with someone who’s had at least a degree’s worth of exposure to concepts of strategic thinking, lifecycle management, development methodologies, etc. Most of us don’t need to be passionate geniuses to do good work. For us non-geniuses, the conceptual “scaffolding” provided by academia opens up a lot of potential. I definitely believe that some people don’t need the degree, but they probably aren’t the average Joe.
most people are pretty average (tautologically so), and average is pretty unimpressive against the pace at which technology (in the broad sense) has changed and knowledge has so rapidly expanded in the past century or two (which is not to say that we're all that much more advanced yet against the backdrop of everything we could ever collectively know). as such, and compounded by sociopolitical contentions, most people are barely functional in their jobs, let alone adequate or good. that specifically includes so-called "experts", who tend to be further out on the edge nodes of our collective tree of knowledge and therefore more vulnerable to rising to your level of incompetence. once at that level, the competiton turns toward signaling your competence, rather than working on becoming more competent, since that's harder and less socially rewarding.
we need nothing short of a cultural shift toward incentivizing real progress and productivity, and valuing real knowledge rather than education, which we only had for a fleeting moment in the US (middle of last century), that only comes from really constraining markets toward both fairness and risk tolerance. we lost our way when we loosened our belt in that regard (for instance, we now instead reward to act of having capital rather than deploying it strategically).
The uprooting of universities and their subsequent erosion as research university in the Humboldtian sense (in the US the John Hopkins University can be considered its first model) of "unity in teaching and research" based on a holistic concept of Bildung (education) in contrast - but also in addition - to a mere vocational training has very much to do with the neo-liberalization of higher education.
In Europe this became known as the "Bologna process" in which established "academic degrees" literally - in a EU-bureaucratic hunch and self-aggrandizement - got thrown away overnight (in Germany: Diplom, Magister) and then modernized, accordingly rated and standardized in a modular fashion, repurposed for the international/European (labour) market. The faculties and universities themselves from then on were run in a more and more managerial fashion with "operating numbers" and by winning state-funded budgets ("exellency" programs) and by efficiently recruiting third-party sponsoring.
For a typical (german) undergraduate student there isn't much a difference between school and university, anymore.
Most Gen X'ers (and Baby-Boomers for that matter) will readily tell you how they for the first time had to learn to resort to self-reliant learning in want of detailed instructions (like in school) but also began to appreciate the less strict scheduling not only for partying but for developing their critical thinking in heated arguments with peers or when confronted with challenging ideas. This is mostly gone, now, a big part of that former public space has vanished.
For attaining craftmanship a particular skillset for a particular field, universities were never a good place to begin with, that's what internships and later your chosen vocations are for. But if they don't prepare you for the labour market and don't provide you with some kind of Humboldtian ideal - a universal starting point with sufficent leisure in pondering about the right/critical questions to ask in a nourishing environment - so what are they actually for?
> It's essentially saying, we don't believe your degree says anything about your ability to perform the job.
It also says:
1. We don’t trust your former employer to restrict promotion to quality employees only. After all, people have to do the leetcode interviews all over again when applying for their next job.
2. If you’re new to the industry and weren’t enough of a chump to take out student loans, you’re welcome to try your luck here
>> I think that the existence of leetcode interviews, where tech companies ignore your background as much as possible, and want to see the skills upfront, is a condemnation of education.
The funny thing is, all those leetcode questions are just the kind of thing that's taught at CS courses (algorithms and datastructures) and the kind of material that CS grads are likely to know well. And the people who interview you are more often than not graduates themselves.
Because, duh, tech companies are part of the same establishment as academic institutions. But don't tell them that because they all want to be disruptive, instead.
I think that the existence of leetcode interviews, where tech companies ignore your background as much as possible, is a condemnation of my 20+ years of building real-life systems. And a means of filtering out people over 40.
Why did people lose faith in the institutions? Because the institutions deserve it.
Academic findings only have so much scope. It's nuanced and the news reporters, kindergarten teachers, and scientists themselves often overclaim the impact of the findings. All of the short term incentives reward overclaiming over nuance and no one should be surprised that the zeitgeist is where it is.
Yep. It’s an incentive issue (as are most issues, I’m beginning to think). It’s been really hard not to become too hardened in skepticism as I get older.
Skepticism is good, but not to be confused with dismissiveness! Intentional curation and omitting topics you don't care about from your information diet is healthy.
but this is not entirely academia's fault. I'm reminded of the ongoing conversation about alcohol's impact on our health. Over the decades, if you've consumed mainstream media, you've been told everything from "2 glasses of wine per day is good for you" to "no amount of alcohol is good for you" and everything in between.
What's difficult is that it's hard to communicate the nuance of what a study actually studied. How many people were involved? What were the methods used? What was the effect size? What were the confounding factors that couldn't be controlled for? None of this can be effectively communicated in a world that reads headlines and probably not much beyond that.
And of course, the media does sensationalize because they're incentivized to. You'll click a headline that says "alcohol is good for you, says science" but probably won't click a headline that tries to communicate the nuance.
I think the end result is the same. Outsiders should be highly skeptical of reporting on topics which take decades of expertise to start to understand.
People seem to feel compelled to form an opinion on every topic, and then think that whatever their take is must be informed.
It is okay to not have an opinion on a topic!
If someone is particularly interested in obtaining an armature understanding of a subject, by all means, they should jump in and form on opinion, but maintaining some humility is essential.
Advertisers, childhood attention spans, and grant funding explain the gross overhyped claims for each of the three professions you mention, respectively. The good news is that two of them have theoretical solutions.
I disagree with this. Academics don't have too much trouble wading through research and synthesizing results. Laypeople so rarely interface with actual research that the quality of an individual paper is not going to contribute to an overall opinion of academics. Virtually no layperson is forming a coherent opinion of academic research based on an in depth understanding of the replication crisis.
Further, the criticism of academia as being full of egg-headed elites who are completely disconnected from the public need has been around for decades - far longer than the current systemic funding and tenure problems.
I think it's more that the "publish or perish" model has emphasised important/newsworthy results, which has then fed a model of science reporting (and I include the journals in this) that have exaggerated results to the point where trust is strained and science reporting is incredible (in the other sense of the word).
The public have been bombarded with ridiculous, counter-intuitive "science" for decades, only for a lot of it to be quietly withdrawn or superceded later. It erodes trust.
And that's without taking into consideration the shady corporate-science bullshit like the fat vs sugar debate in nutrition science. If a company can buy a paper that says whatever it wants, and get it peer-reviewed and published in a journal, why would we trust science? Should we even?
In medicine, the Journal of the AMA and the New England Journal of Medicine seem to be the main sources of articles that reach the public's eye.
The editor of the New England Journal once complained that it was troubling how papers that had only tentative results, more suggestions for further research than conclusions, would get blown out of proportion in the mainstream news media.
Some of the burden is on the journalists, not the researchers.
Agree completely, but the journals do have some power here - they could stop the journalists writing bullshit. But they like the attention the media coverage brings so they don't do that (and then they blame the journos).
And of course the journals could make the scientists reframe their papers so they're not catnip for journos.
It sets up an endless amount of "legitimate" strawmen that any side knock down to delegitimize/"debunk" their opposition. So the media plays a role in this too.
But I do agree that at least one of the main problems is that academics have the ability to sift through research while others don't. So better self policing and an easier way for the public to digest the information is probably what's needed here. I think the problem here is that the public don't trust the scientific community to self police.
>Further, the criticism of academia as being full of egg-headed elites who are completely disconnected from the public need has been around for decades - far longer than the current systemic funding and tenure problems.
I think the internet and social media just really took the mask off for a lot of people. The tribalism probably kicked into overdrive when they can just look researchers up and actually confirm that the scientists are part of their outgroup.
> So better self policing and an easier way for the public to digest the information is probably what's needed here.
I'm not sure that better self policing is a good idea. I think we want academics to be exposed to a sea of research, much of which is half baked or has big flaws. Preventing the "probably wrong, but maybe something is here" papers from being discussed limits the ability to actually make big things happen. There is simply an education problem where laypeople (and media) have decided that peer review is something that it has never been and a huge amount of misunderstanding (deliberate or accidental) of the scientific community derives from this.
> I think the internet and social media just really took the mask off for a lot of people. The tribalism probably kicked into overdrive when they can just look researchers up and actually confirm that the scientists are part of their outgroup.
I think this is definitely true. When TPUSA can basically publish an "enemies list" of academics they don't like the end result is a stream of harassment.
Partially. People forget that science is also REALLY hard. I have personally had to retract results I presented at a conference after not being able to replicate my own findings -- and I was following best-practices and being scientifically rigorous during the original experiments. I have never been able to figure out what went wrong, but it was extremely embarrassing.
"I have never been able to figure out what went wrong, but it was extremely embarrassing."
Kudos for retracting. Integrity is probably more important for science, than intelligence (not meant as offense, there are a million reasons a experiment can produce odd one time results).
Too many published results seem to not be reproducible anymore and not many are even trying, as there is little benefit in reconfirming findings, but rather incentive to publish, publish, publish.
Quantity over quality it seems. We somehow need to change that again.
The academic system requires a minimum degree of good faith conduct. That honor system effectively does not exist in modern western soft sciences, because ideologues abuse the trust to push their woke agendas with (deliberately?) sloppy science, and the peer review process, thoroughly infiltrated, is unwilling to cast a sufficiently critical eye either for fear of reprisal or out of complicitness. The result of this hijacking is a rigid dogma which manifests as a pseudoscientific justification for the reverse racism that is tearing through western society. That's all before the other deep, systemic issues like perverse incentives and the related replication crisis touched upon in the article.
This article is a nice overview of the modern moral panic gripping academia and spilling over into everything else. At this point laypeople are right to question academia as it's once noble purpose has been totally coopted by ascientific progressive politiking.
I don't think a lot of people are paying attention to the replication crisis and similar problems in academia. Instead their own ideas about legitimacy are emotional.
The US has a focus on "input legitimacy" which is partially "we do it the way they show in Schoolhouse Rock", and partially about the way politician's communication styles make people feel.
The Chinese model based on "output legitimacy" (do institutions demonstrate competence in action) has its own problems (what if things go wrong that we can't control) but should be at least partially emulated in the West. (The flip side of "what if things go wrong" is a reflexive habit of making excuses, sometimes even before they're needed.)
If Ukraine survives, for instance, winning the war will make the Ukraine be perceived as one of the most legitimate in the world as opposed to an illegitimate cesspool of corruption. It is astonishing how 2014 was a wake up call for Ukraine to build up its military competence and how Ukraine responded to that.
I think a lot of ideas about academic legitimacy are neither based on a deep understanding of the replication crisis, nor are they emotional. The fact is, a lot of bad claims coming out of academia don't require any particular expertise to spot. Did you need to be an expert psychologist to realize that Power Posing probably wasn't right?
Very doubtful. You just need common sense. Like, if this actually worked then you'd be seeing it spread very fast everywhere, but in reality it apparently needs a constant flow of TED Talks to get people to take it seriously. Ditto for priming studies, etc.
More recently there's been COVID. The problems here aren't exactly the same as the replication crisis, partly because nobody seems to try and replicate anything in the first place. Really IMHO the problems are much worse. Nothing could possibly destroy confidence in academic and public sector expertise faster than being told masks don't work, followed by they work so well they're now mandatory, followed in turn by seeing case graphs where switching mandates on/off very clearly has no effect whatsoever.
The constant flow of bad models that were never acknowledged is particularly destructive. Most people can't articulate why the models always seemed to be wrong except through vague generalities like "bad assumptions", but it doesn't matter. Epidemiological modelling is toast in the public mind, along with the lockdowns they led to. The understanding that they're unreliable is fact based, not emotional, even if the details aren't there.
At any rate, having done deep dives into too many trash COVID papers in the past two years, I can't say knowing the exact details of why they're wrong makes much difference. The important thing is actually the social problems surrounding them, in particular the lack of any institutional acknowledgement or response that there's an issue. Observe how discussion of the replication crisis started with and still mostly comes from individual researchers, not institutional leaders. We can see there is no psychological acceptance of how badly they've been getting it wrong because, for example, Imperial College London (home of Prof Lockdown himself) just banned parents from attending their children's graduation ceremony due to COVID:
This is at a time of record high cases and after the Queen got it at 95. Nobody cared, it was in the news for barely a day. ICL comes across as a delusional institution with this sort of act, and combined with all the stories of activist craziness on campus, it's getting widely noticed by the general public.
The original paper from Ahlskog & Oskarsson is about bias when applying three domains of determinants to measure political preferences.
It feels very much like the author Thomas Prosser has an axe to grind when he includes this study of methodology (in a subsub field of sociology) with the larger issue of replication.
My field is signal processing (and i've published quite a few papers), but my take on what papers are is a little different. Their purpose was originally, and i think still, a way for researchers to communicate problems they have solved to other researchers. The fact that some subset of papers turns out to be wrong, or that the public doesnt understand them is immaterial. The repositories of knowledge about which papers are good, and which are bad are the research labs. Ask a professor at a research lab which papers have results that can't be reproduced, and which are high quality, and they'll know immediately.
When there are statements in the article "Such results erode confidence in academic work", the confidence is only eroded in the papers that are bad, which is how it has always worked. Confidence isn't lost in every paper, or the scientific process, but laypeople and administrators see some stat about "30%" of papers have some error, then all of must science is wrong.
This is a fair point, but for the layperson who cannot distinguish between the 30% of papers that are bad and the remaining 70% it may as well be a denunciation of all science, since they themselves perhaps cannot tell the difference.
While papers remain the main standard by which science is communicated maybe there is a place for those in the scientific community that do know to be more vocal about which papers are worth reading.
This is something that people have to accept: the target audience of scientific papers is other researchers, not laypeople. Ideally we need more effort spent on synthesis of prior research. In my field (ML) very few prominent researchers write overview papers summarizing state of the art even over last few years. There is little academic incentive in doing so. Laypeople should read books written for them (like Hawking's books), not bleeding edge research papers.
The problem is deeper than this, though. All of the "scientific method" theory which is meant to ensure reliable results applies only to experiments and observational studies. Syntheses are just prose - there's no particular reason you should have confidence in a synthesis if you don't think the author shares your values or it contradicts something else you strongly believe is true.
"studies that replicate are cited at the same rate as studies that do not"
Confidence is eroded in all papers by this sort of thing, because academic structures are the same across fields. Whilst individual fields or labs may be more rigorous than others, people can't be expected to keep a massive database in their heads of which fields are good and bad. To be able to generalize about quality requires institutions that create quality, but universities don't do this. And because universities dominate "science" or at least the public discussion of it, that lack of quality control reflects on all science.
I work in signal processing and as a field of theory it presents no barriers to replication. My fiance is exiting chemistry academia due to an abusive professor. In the past they have wasted over a year of effort on one project trying to build off of prior work. The conclusion they ended up with is that the original work was fraudulent. No paper covers the inability to replicate the previous work.
So what does this mean? The professors pushing the papers out are not doing their due diligence and there is no one else doing public checking. The loop is open. It is not science. That's the crisis.
I’m in electrical power engineering and control, I find the oldest papers are usually the best ones as they present the essence of a concept simply. New papers often don’t add much except a bibliography I can use to find the source and authority on a topic.
The author should have state from the start that the article he bases this upon is about social science and not the whole academic and science world, it's kind of misleading
Social science has always been full of incertainty and biased results, it seems rather normal the public don't trust it blindfully.
There's a sort of sentiment that shows up here on HN -- it's not everyone but it's consistent -- that the problems with replicability are limited to the social sciences, and don't apply elsewhere, which is not true. It's not everyone of course, there's pushback, but I'm surprised and concerned that it persists.
Just last week or so there was a paper in Nature about how fMRI studies -- a modern backbone of neuroscience work -- have also been mostly unreplicable. This follows a litany of other papers showing the same thing. That Nature paper made transparent allusions to genetics which invested tons of money in studies which were also largely unreplicable, with fairly obvious power issues that were ignored. When the replicability crisis started getting attention, there were interviews with pharmacology corporation scientists saying that the pharm industry tends to internally assume that 2/3 of published pharmacology studies will not replicate when applied to the real world. There were studies showing that oncology had similar rates of problems, and so forth and so on.
The social sciences is fuzzy as you say but they also tend to turn the microscope on science itself first. Meta-analysis in its modern form (as opposed to early statistical methodology papers) comes from psychology; this is just more of the same. There probably are differences across fields but I think few fields are immune.
Also, I would push back on the idea that the general public's mistrust is limited to the social sciences. I would argue that issues with climate change skepticism are driven in part by a general distrust of academic findings and scientists, and many of the problems during the pandemic with skepticism about vaccination, masking policies, and so forth were driven by skepticism about biomedical research. Possner said "such challenges do not affect academic confidence in the reality of (say) climate change and Coronavirus"; I was puzzled by this precisely because I couldn't tell if he was being ironic, or pointing these out as areas where there is a contrast between academic confidence and public confidence in those findings, as if to say "well look at how much the public distrusts that; now imagine when academic confidence is eroded further?"
My biggest problem with the linked piece, in fact, is that it is framed around the question "what happens when the public loses confidence in academic findings" when that problem is already here to a big extent. We saw what happened during the pandemic. That's what happens.
Academics to some extent is falling apart, and it's not limited to the social sciences. The problems with misttrust are running deep and I think academic and political communities have their head in the sand, rather than taking their structural problems seriously. It's always the messenger: the irrational public, the muddle-headed social scientists who are exposing the problems, it's never the corruption in academics itself.
This advice is extremely vague (on purpose) and doesn't answer any of the more challenging questions, e.g. "What is the full, comprehensive list of specific consumables should I avoid, and the reasons for doing so?"
Answered vaguely and in a way that's incompatible with a lifestyle that doesn't desire daily grocery store trips or eating in places where you don't have complete control over the menu...
I'd rather know what to avoid, even if you think that question is "wrong" (I don't agree).
Is that it? Is that the full, comprehensive list? If I do these things, am I completely good?
I doubt it, and again it's excessively vague:
* "Limit"?
* "Sugary drinks?"
* "One or two servings" that's literally doubling the serving count. How can that be, where consuming twice as many of something is as fine as consuming half?
* Juices should be limited but my fruit and veg intake per meal should be 50%, that is contradictory information, unless you're trying to suggest blending things reduces its nutritional value.
* If that is the case, how blended? Should I not chop my carrots? Minced onion is worse for me than diced onion, should I just eat the onion whole?
* Is it better to starve than to violate these rules?
* What, specifically, are the consequences of violating these rules? If I, today, eat one additional serving of fruit than I "ought", am I cutting my lifespan by three days? Six weeks?
Even if you can answer every question I put up here, would you mind publishing your phone number so everyone in HN can give you a call every time something isn't covered here? By the way, what are your credentials? Why should I trust your assertion that this is a solved problem, or that your interpretations of this document are accurate? Why should I trust this website in the first place? Yes, it's Harvard, but I don't trust them blindly; how did they arrive at these conclusions?
Please, don't condescendingly link to a nutritional chart page and think it answers every question, or suggest this information isn't regularly changing.
> Even if you can answer every question I put up here, would you mind publishing your phone number so everyone in HN can give you a call every time something isn't covered here? By the way, what are your credentials? Why should I trust your assertion that this is a solved problem
Good questions. I have no credibility and I don't pretend to have it. Ask you nutritionist. I just read the official nutrition advises carefully. And you should too. Also, check the referenced research if you can.
> or suggest this information isn't regularly changing.
You probably don't have to avoid it like a poison. The less, the better, I guess.
> * "Sugary drinks?"
Every drink which contains a lot of sugar. For example, Cola and juice both have about 10 grams/100 ml of sugar. This is 2 table spoons per 200 ml. Compare to the recommended daily sugar intake.
> * "One or two servings" that's literally doubling the serving count. How can that be, where consuming twice as many of something is as fine as consuming half?
It must depend on how much calories you generally need per day. People are very different. If you need a personal advice, ask a nutritionist.
> * Juices should be limited but my fruit and veg intake per meal should be 50%, that is contradictory information, unless you're trying to suggest blending things reduces its nutritional value.
> I have no credibility and I don't pretend to have.
And yet you're giving nutritional advice on Hacker News to complete strangers. Maybe remember your lack of credibility next time you claim a topic is a solved problem.
I'm not giving a nutritional advice. I'm repeating the advice from the official resource and encourage to check it yourself and/or ask your nutritionist.
I'm just tired of lazy people who don't want to read the official advises and prefer to say that everything is unclear in the nutrition science.
Wrong. You are giving nutritional advice by claiming this is "the official resource" (it's not), and by synthesizing the information into new, different information that is both less correct and even more vague.
You may be tired of people not being informed, but I'm tired of ignorant people thinking they know more about a topic than they actually do.
Professional doesn't mean official, and it's not a shallow dismissal, it's just a dismissal due to your self professed lack of credentials on the topic.
> it's not a shallow dismissal, it's just a dismissal due to your self professed lack of credentials on the topic
I didn't provide my own advice (in that case, you would be right). I repeated a professional advice, possibly incorrectly, and you did not provide any explanation why you think it's wrong, just dismissed it. This is by definition a shallow dismissal.
I think our intrinsic reluctance to fully consider genetic differences among populations is a massive confounder in nutritional (and medical) science. Modern human populations are far more genetically distinct than we are allowed to acknowledge. It's a deeply seated bias that pervades medical and social sciences and is the root of so many conflicting results.
nothing is true, you cant trust anyone, professors are all acivists, BLM burned the cities down, the fed is just printing money. bitcoin - the best money we've ever had, deserves the best credit card we ever had.
When I last looked, Google Scholar doesn't take any action on paper retractions. It seems there is no reporting system in place.
Researchers Brock and Thornley of New Zealand published and then almost immediately retracted a paper linking COVID-19 vaccines and a much-higher-than-previously-found miscarriage rate. Scholar still lists the original paper posted---with no cover page indicating the retraction. (They do have a separate link to the retraction press release if you look for it.) The main result on Scholar links to a half dozen "not-so-academic" websites (ellinikahoaxes.gr, wokeguru.org, resistance-mondiale.com) hosting the same paper. I'm willing to bet even if the original paper could be removed, independent websites would continue to try relisting it.
While it's important to keep a record of bad research rather than scrubbing it away from history entirely, it seems feasible to have a reporting system in place for paper retractions, where the title link includes [retracted dd-mm-yyyy] or something.
This was my small taste of disappointment (aka loss of confidence) in a relatively popular academic tool.
> What happens when the public lose confidence in academic findings?
When some X accumulates a track record of not working, people give up on X. Maybe then X will get improved, and slowly people will give it another chance.
The OP seemed to be mostly about the quality of the science in the social sciences. Hmm ....
But, in medicine, there are efforts to be careful. E.g., can test a new drug with double blind randomized placebo controlled trials. Maybe that methodology is good enough to be trusted? It appears that I trusted it when I got two shots and a booster from Moderna against Covid.
In math, hmm ..., if there is a claim of solid proof, published in a respected peer reviewed journal, and so far no one has found any flaw in the proof, then some trust can be justified.
The gravitational detection work of LIGO is astounding, and I'm trusting it. And I have yet to check in detail the math of general relativity -- it's on my long term TODO list!
And I trust the claims for the Webb Space Telescope, and the reasoning for its location at a Lagrange 2 point.
So, in medicine, math, and physics, I can have some trust!
For the social sciences, my view is influenced by my wife and brother, both of whom tried those, got Ph.D. degrees, etc.
This seems to be heavily focused on studying social phenomena and less so about things like engineering papers or Physics etc. The author himself specializes in social-oriented research. I think it would be better to look at how successful non-social studies are vs humanities. It is debated on whether or not Sociology is even a science at all.
For what it is worth, I happen to know that big tech companies follow research at big name CS universities with a bit of interest. At times, even borrowing the research itself in their products. At one point, a professor I worked under was quoted in Android documentation.
Mission accomplished. The US has been an a downward slide into privatization and disenfranchisement since at least the early 80s, probably earlier. I was born in the late 70s and have watched the gradual dismantlement of public institutions my entire life.
Where this matters is: academics used to be able to conduct pure research. Now all they do is fundraise and hustle for grants. Anyone used to be able to go to college. Now the gatekeepers decide who has enough money or connections to attend. We even used to have news and (gasp) investigative journalism and public broadcasting and periodic reports to the public on the state of publicly funded research or some great public works project. Now we have infotainment and the suppression of any real tech that might materially improve lives by reducing the workload of the average person. They only fixate on phantom tech that distracts and enslaves. Now wonder the public doesn't care.
If we really want to get serious about fixing this stuff, it's going to involve at least in some part, a total rejection of vast swaths of the status quo. I'm all for that, I think most Gen Xers are for that, and certainly most people younger than that are for that. But there is just so much concentrated wealth now diluting social movements. And so much momentum behind the previous generation in congress that will do everything it can to hold onto power in the face of so many calamities we face, because at the end of the day, it's not their problem so they're just never gonna get the memo.
If a spiritual revolution away from wealth concentration isn't already underway, it's going to start with some version of "your money's no good here." And individuals withdrawing their contribution from institutions which concentrate wealth and power.
While privatization and the fundraising rat race for grants certainly started us down this trend, academia has been it's own worse enemy recently, and it's primary output these days seems to be ideology and activism, rather than cold, hard, factual, evidenced based research and science, so much so, that the activism and ideology has worked its way into the science itself. It's a poisoned well at this point, and it's sad, having worked in a research lab at university myself in the computer vision department, there is still tons of cool things going on, but they all get massively overshadowed by the hot button issues and whatever the Social Justice cause du jour is.
Yeah. It's not "what happens when the public lose confidence in academic findings?" It's "what happens when academia is no longer worthy of the public confidence?"
I mean, it's not totally that. But it's sure a big chunk of the problem.
I think the idolization of business is killing public institutions. Instead of looking at the greater good everything is focused on money and numbers to achieve. This has corrupted politics, research, education and healthcare.
> What happens when the public lose confidence in academic findings?
flat-earthers
half-joking aside, I have come to understand that the academic institutions are part of the state (perhaps I should say civilization?). the point being that academia (as the part of state that I'm saying it is) has a primary function of ensuring stability (same as the most well known face of the state i.e. government); this is mind-bending when faced with the idea that academic research is at the forefront of advancing civilization into uncharted waters (...a PhD must provide an original novel contribution...).
Seems that at some point artists became showbiz employees and at that same time, only scholars kept 'advancing the state of the art'. Which is a role historically fulfilled by real artists of the sort that ain't doing it for money nor fame.
There is a fallacy in comprehend the meaning of Scientific method: confidence in nice and needed to cooperate, but in Science no one should (despite almost all regularly do) trust blindly anything.
Of course we can't verify the entire involved knowledge any time, and that's why the concept of collaborative peer review was born, not much different than the concept of "chains of trust": interest researchers in something verify some others publications and add up their own confirmations or doubt, "the network" do the rest.
The problem there is that such review and network does not really exists. Oh yes there is the ArXiv, HAL, ... papers circulate etc, but the "mainstream" is a network of hi priced journals and hi paid corporate-backed research + equally hi paid PR in the press. That's why people loose confidence: they do not have ontological means to know but they smell actual Science is mostly commerce and just very little Science.
IMVHO the sole way to correct that is build the above mentioned networks. Public, publicly well-founded universities that do research and reviews for the society, very-well separated from the private sector, and share this knowledge with the entire world. At that point the SciHub will be a public, legal and well founded platform and PR can do something but not enough to contaminate knowledge for private interest. At that point people would still not be able to verify, witch is not good, but they have something worth their confidence.
At the start of the pandemic, an academic at a well-known university asked me to review a paper of his, kinda sorta to build a relationship and to eventually publish something of my own based on his paper. The claim of the paper was basically that white (non-hispanic) communities were significantly more affected by COVID when compared against other races in similar income brackets. Lots of statistics, analysis against census data, etc to support the argument and such. The source of the data from his paper was from an "open data" portal of COVID deaths, published by the city's coroner's office.
Thing is, the data published by the coroner's office didn't include a lot of fields that I'd already received from FOIA. Fields missing like the name of the person who died. Since the paper's conclusions didn't pass a gut check, I dug in and found that just glancing through the names of those marked down as "white", a majority clearly had names with Hispanic origins.
I shared with the researcher that his findings were probably really, really wrong and I was responded with something like, "even if 50% are marked wrong, the findings are still accurate". Some name comparison [1] and spot checking later.. and it ended up being about 80% of hispanic-origin names were marked as "white".
The researcher eventually conceded that the paper was wrong, but it was definitely of an eye opening experience into how the academic world works. I lost a lot of faith in the academic world after that.
I am definitely not a scientist, but speculating on race because of names you find to be too hispanic to be white feels like spectacularly bad science to me. This is not my field though so perhaps that is normal an accepted.
The point of name-based analysis wasn't for publication or even "science", but to instead show that the analysis done by the researcher was very likely wrong in order to prevent its publication. There is no way in hell I would ever publish anything that relied on name-based analysis as an accurate measure, that would be deeply unethical as far as I'm concerned.
I did ask around with these exact concerns in-mind, which led to this paper by the census in their evaluation of this exact problem (the Passel-Word Spanish Surname List was what I compared against): https://www.census.gov/library/working-papers/1993/demo/POP-...
So, I get it, and I had the same concerns as you, but I like to believe I followed proper due diligence in making sure my approach was reasonable. Especially against the risk of the paper being published (consider how the paper could be used in racist narratives).
There are some large datasets for name-race correlations that can and have been used in real science. It is statistical, so not an accurate prediction for an individual, but has some merit for large groups.
For example, someone with the name José Santiago Hernández very is unlikely to be Germanic-white versus Hispanic-white.
> I lost a lot of faith in the academic world after that.
I would argue instead that you have demonstrated the importance of peer review (a cornerstone of academic research). The problem is not really academic research, but that we do too little of both academic research and peer review.
So what you're saying is that the current state of the academic world isn't working as it's theoretically designed to? Frankly, I'm not sure how that's supposed to boost my faith.
If you have a very profitable product but the manager decides not to produce much of it, the problem isn't the product, it's that there's too little of the product to help the company's bottom line. If there was more peer review of the type you described and there were more studies, we wouldn't be inflating the importance of unreliable results because we'd have ten other studies pointing out that it's BS.
I dunno, I've met a lot of profs who take the attitude "if you want your name on crap, be my guest" when it comes to reviewing papers. They might check for glaring errors, but rarely does anyone work through the results for correctness.
I agree but that's a sign we need more peer review. IMO it's unethical to engage in fake peer review like that. I recently encountered the opposite - a reviewer that wrote a fake negative review of my paper without reading it. Killed the paper at a good journal by making claims that are easily verified to be false.
Surname is correlated with descent (which is distinct from race, as people understand that word), while in all likelihood the races that were written down for the patients corresponded to the color of their skin, as well as possibly other features. That would suggest three things:
First, as you found, there was no correlation between deaths and descent. Presumably there weren't statistically anomalously fewer Gomezes than Smiths.
This doesn't eliminate the fact that people wrote down fewer dead as Hispanic than as white. So:
Second, there actually were fewer dead Hispanics than dead whites, understanding "Hispanic" as "a person who looks Hispanic" and "white" as "a person who looks white".
Third, or alternatively there is no statistical difference between dead Hispanics and dead whites, but somehow fewer dead Hispanics ended up at the morgues to be written down as dead.
One of my favorite stories in the Bible is when the priests of Baal are challenged to a religion showdown by Elijah. The idea is each side will pray for an altar to be lit on fire, whichever altar is lit on fire is the altar of the true religion. I won't spoil the ending - but I think the setup makes a lot of sense. If there is a guy who can ignite stuff by simply asking that it be lit then I would really like to know more about that guy's religion.
I have the same opinion of academics - show me what you can light on fire. For example, I don't believe in physics because it makes intuitive sense to me, on the contrary, I find it confusing and counter-intuitive (sometimes). I believe in physics because the people who make magic boxes of light and sound that move fast and connect across vast distances tell me they did so via the knowledge they derived from physics. It's not how I would've guessed the universe would work, but who am I to argue with a blazing altar?
Judging by this standard I find many academic disciplines are severely wanting - there is a lot of chanting and waving of hands, but very little smoke. If I hear on the news that there's going to be an eclipse, I'll go out and look. If I hear on the news that eggs are bad for you, I'm going to roll my eyes.
You don’t “believe” in physics, you understand there is some truth to it based on direct evidence. Belief is accepting something to be true on the foundation of faith—not having direct evidence.
“Now faith is the assurance of things hoped for, the conviction of things not seen.” - Hebrews 11:1 (ESV)
I disagree with this interpretation of the word belief. A belief may be founded in something, or it may not be. Unquestioning belief without evidence requires faith.
Belief is a real word with meaning in the secular context as well.
Belief can be informed by evidence or not. It simply means acceptance or confidence that something is true. You can have faith in the available evidence, or faith in the absence of evidence.
> Belief is accepting something to be true on the foundation of faith—not having direct evidence.
Most people will never understand the direct evidence of even relatively mundane science, and almost everyone is incapable of understanding the direct evidence of the cutting edge.[0] and its implications, ergo in lieu of understanding they must substitute belief. Where science policy/communication fails here is in producing a 'believable' system, with adequate consistency and storytelling for persons who will only ever understand by analogy.
[0]Regular people don't know what an integral is. The intelligent, educated, and motivated don't have the bandwidth to really understand more than a smattering topics deeply.
This interpretation of what faith is was created during the Reformation. Which was unfortunately a few millennia after this episode. Ancient religions were definitely based on getting the goods by magic - they really did sacrifice those oxen to get YHWH to win the war for them, they really did sacrifice those fatted calves to get Zeus to get the king to make good decisions, they really did sacrifice those pigeons to get Portunus the god of locks to keep the lock working.
It's not fatted calves, but we do sacrifice some money to the quantum folks so they can break our enemies' encryption locks ... in like 25 years ...
> One of my favorite stories in the Bible...I won't spoil the ending - but I think the setup makes a lot of sense.
> I have the same opinion of academics - show me what you can light on fire.
I don't know if you're going to be welcome in a lot of liberal art colleges, since this is the ending(SPOILERS!):
> And Elijah said to them, “Seize the prophets of Baal; let not one of them escape.” And they seized them. And Elijah brought them down to the brook Kishon and slaughtered them there.
15 “Beware of false prophets, who come to you in sheep’s clothing, but inwardly they are ravenous wolves. 16 You will know them by their fruits. Do men gather grapes from thornbushes or figs from thistles? 17 Even so, every good tree bears good fruit, but a bad tree bears bad fruit. 18 A good tree cannot bear bad fruit, nor can a bad tree bear good fruit. 19 Every tree that does not bear good fruit is cut down and thrown into the fire. 20 Therefore by their fruits you will know them.
One small but critical addendum I'd add is that it's less about, "The people who make magic boxes of light say they used physics" and more about "EVERY person who makes magic boxes of light, all in unison, say they used the exact same physics."
There's a huge power in knowledge consensus. It's got all kinds of flaws, but it meanders generally in a growth direction, and that's better than any other prediction system I'm familiar with.
I would argue that if two people brought me magic boxes of light saying they used physics, and they each told me about two vastly different "physics" involved with creating those magic boxes, I would instead introduce them to each other in the hopes that they might reconcile their understanding of the fundamental concepts involved and make an even cooler magic box!
What you instead want to look for is:
"MANY people who are familiar with magic boxes tried to make this guy's magic box and couldn't replicate his method."
You are looking for valid contradiction to stated facts to invalidate claims, not for a widespread consensus on the claims.
This is important because, as a single example, two people can use different methods to achieve the same outcome based on their own respective theories that have minor flaws but present strong evidence that they are in their entirety true. It is only by reconciling & finding the contradictions between the two that you can come out with a single VALID theory.
If I were a scientist I would probably have some examples of this occurring in the past, but off the top of my head I would suggest it is improbably that there has never been a situation where two competing theories that each had strong evidence were both eliminated in favor of a single unified theory that reconciled differences between them.
Nah, science happens where the disagreement grows. If there's consensus, that's not science, it's technology. That's why you guys keep talking about light boxes. Try asking 10 scientists about gravity, for example. You'll get 12 different answers. And that's not an off-by-one error.
As an atheist, this is a fascinating analogy, because my take-away is that Elijah made up a story to justify mass execution of political rivals. (Perhaps he played a magic trick, perhaps someone just made the story up whole cloth, but in any case a lie was told to justify a religiously/politically-motivated mass execution.)
This also has a reasonable take-away: sometimes lighting an altar on fire can be faked even when it looks real. Or, "beware the flashy demo". Fusion and especially some of the more shameless corners of AI come to mind.
My apologies if this stretches the analogy too far.
Also: repeatability. Can others reliably invoke YHWH to combust beef? Can Elijah perform it under controlled laboratory conditions? Can the other priests of YHWH? If not, perhaps they too should be taken to the brook and slaughtered.
We're about to find out! The scientific community has done itself a huge disservice in recent years in two ways:
1) Refusing to police non-rigorous fields invoking scientific authority. As the article notes, even rigorous fields are full of results that cannot be reproduced. The situation is even worse in non-rigorous fields. In his famous essay on cargo-cult science, Richard Feynman specifically called out "educational and psychological studies" as "examples of what I would like to call Cargo Cult Science." https://calteches.library.caltech.edu/51/2/CargoCult.htm. Yet today, there is a movement to accord any PhD the respect of the title "doctor," as if an EdD was an authority similar to a PhD in physics. People do this to be polite but it has grave consequences.
The respect people accord "science" is, at the end of the day, built on results. We trust doctors because they delivered concrete results that medicine men could not. In the long run, people will notice that EdD is often wrong, because it's not a rigorous field, and that will tarnish the credibility of everyone with a PhD, because the lay public quite reasonably doesn't understand these distinctions in rigor.
2) Allowing scientific authority to be invoked for political purposes. There is a difference between scientific results, and the value systems of individual scientists. Science can, for example, create a vaccine. It cannot address the political question of whether anyone should get the vaccine--that question relies on cost/benefit analysis that, in turn, depends on individual value systems. Or in another example, science can tell you the probability of spreading a disease in a grocery store versus a church, but cannot tell you whether grocery stores or churches are more important. Moreover, most people intuitively understand this distinction. There are, of course, some people who will ignore scientific facts that are as plain as day. But there are a lot more people who will chafe at feeling like they are being told "I'm smarter than you, so you have to accept my values." That, in the long run, will undermine their trust in scientific results.
And if we, as highly educated people who understand "science" are honest with ourselves, that skepticism may not be unwarranted. We know that biases exist in the system. For example, it is well known that publication bias exists: studies reporting positive results get published, while studies reporting negative results don't get published: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3341407/. As science becomes more politicized, it's inevitable that other kinds of publication bias will affect not only the reported results, but even the kinds of questions that are studied.
Yet today, there is a movement to accord any PhD the respect of the title "doctor," as if an EdD was an authority similar to a PhD in physics. People do this to be polite but it has grave consequences.
No. We shouldn't be putting so much weight on the title of "doctor" for physics PhD's either; several physics PhD's I know personally are absolutely barking mad, and there's a long history of physics PhD's getting over their skis on other fields like medicine.
Meanwhile, the usage of "doctor" that you're decrying here is the more historically well-established one.
I think a lot of comments here are vastly oversimplifying the problem (including this one). People have lost confidence in academic findings due to a wide variety of reasons. There's many people to blame here. There's academics, journals, news/reporting, politicians, and more. Let's look at a few (far from exhaustive and still pretty shallow analysis).
Academics: Incentives are frequently to publish fast and often. This encourages work with less detail, higher uncertainty/error, and less impactful work. You simply cannot produce as high quality work in 3 months as you can in 1 year (or 3) or research. Often we want PhD students to produce 5 first author papers in top tier journals before graduating. That's 5-6 years to produce just as many top tier papers (realistically 3-4 given your first 2 years are more class based). It is possible to put out a high quality and high impact paper every year, yes. But this is also a very difficult task.
Journals: There's no need to explain this one to anyone who has gone through the review process. Everyone I know that has attempted to publish papers has had several papers where they question what the reviewer actually read because it definitely wasn't their paper. Or where reviewers are vastly under-qualified to review the topic at hand. These are common occurrences. (Note: this more often causes false negatives rather than false positives due to incentive alignments) This creates legitimate complaints and can often be misunderstood from people outside academia.
Reporting: We all have seen this. Things like "eating chocolate is healthy" and other things that are obviously wrong. We've seen universities oversell their research. We see news channels oversell or vastly misunderstand research (despite having easy access to experts and that authors are frequently happy to discuss their research). The public also doesn't understand things like confidence levels. They don't understand that we have a different confidence level in anthropocentric climate change vs how much healthier a glass of wine a day is. This isn't their fault though. We should hold the reporters (academic or news sources) accountable since their are structured to be the science communicators. Instead they are politicizing and adding opinions rather than explaining.
Politics: We all know this one. Everything is politicized. Not just that, but to the point where things are "left" or "right". If the left supports one thing then the right opposes it and vise versa. This is far worse than both sides accepting the issue and coming at it from different angles (which I've seen this happen and both angles also not be in line with the actual research). Covid is a great example: people on the left over-estimate the dangers and people on the right vastly underestimate them (these are not equally biased positions and I'm not claiming they are, just noting that both have errors, not the magnitude of the errors). Climate change is another example, where right denies and left only focuses on pop/hip topics like tree planting or banning straws and not larger issues. (I'll note that in my anecdotal observations it seems that the magnitude of error is frequently smaller on the left).
So we have a system where we aren't encouraged to do high quality research (not meaning it doesn't happen, there are a lot of researchers), research (of any kind) is difficult to get properly peer reviewed, it is poorly explained to laymen, and results become tribal. Why does the public lose confidence in academic findings? You tell me.
I'd argue that absolutely nothing "happens" when the public loses confidence in academic findings, and honestly the public should generally butt out of the entire process. It's not written for them, it's not discussed by them in any rigorous way, their input is not valued or noted, and generally they're completely wrong in very basic ways.
Should academic research be done in secret or in a way that actively prevents the public from accessing their results? No. Should we disabuse ourselves of the notion that the public matters to this process? Yes.
None of it matters to the lives of nearly anyone until it's gone through many, many layers of filtering. We, the public, ought to let that filtering play out, rather than meddle in the process
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[ 3.1 ms ] story [ 246 ms ] threadhttps://www.wired.com/story/social-science-reproducibility/
https://www.psychologytoday.com/us/basics/replication-crisis
I didn't learn a damn thing from the process.
In grad school I was told to generally assume that the tool with the second highest line in the key graph was the best tool. The top line was invariably the author's tool and its results rarely translated to other experiments. But the tool with the second line was usable by somebody other than its original author on a different problem space.
Empirical SE research is part of the social sciences. The subset of SE research that doesn't push hard for collaboration with social science departments is doing just fine.
I listed Software Engineering because it is one of the fields I know well but is way less esoteric than the other one I know well (PL). You'll find the same kinds of replication problems in POPL or OOPSLA papers too.
I suspect that other subfields don't fare any better. I certainly hear from my ML friends that a huge portion of ML results are untrustworthy.
Those papers have lots of issues, especially cherry-picking and narration of the results' significance.
But the core claim -- "I found N bugs in the following codebases" -- is generally reproducible.
It will not happen, though.
It's essentially saying, we don't believe your degree says anything about your ability to perform the job.
The only reason academia hasnt been completely uprooted, is:
1. Some sects of society use academic prestige as a product. i.e. this harvard educated mckinsey consultant will optimize your business! Or, this harvard educated financier will invest your money carefully!
2. There's no way to have some leetcode like test for most jobs.
3. There used to be more signal in academic credentials, and older sects of society still believe those signals exist. Its the same with doctors, older generations treat doctors like infallible royalty, younger are much more skeptical
theres a huge caveat that some top people in the world do end up at top academic institutions. its just they keep mixing in these political appointees, agendas, etc
Unfortunately I have worked with people with a master’s in computer science from an american university who couldn’t write a coherent sentence in English. Let alone write code or design a system.
I’ve also interviewed people with illustrious careers who just weren’t a fit for the role they applied to.
Credentialing is in poor shape in our industry.
var a = 1; a = 2;
Before I could write anything more (this was just setup) the person pipes up “that’s false!” We went through the rest of the interview but I just couldn’t believe it. The individual had been working for a government office as a software developer for 5 years or so before this.
I have no idea what this persons work day looked like but still shake my head when I think about that interview.
Professors are stuck in the middle: asked to teach unprepared students, and forced to pass many who are not suitable.
The people it hurts the most are the students who are actually capable, and put the time in to excel.
instead of IQ test -> competence signal
you have:
SAT/ACT = IQ Test -> university acceptance criteria -> degree/credentials -> competence signal
Citation for this? As far as I know IQ isn’t a measure of intelligence (because intelligence is hard to define, let alone come up with a single number that quantifies it!)
https://www.amazon.com/Know-Debunking-Myths-about-Intelligen...
All you have to do is get a figure that mostly correlates fairly well to most of the phenomena we might consider intelligence, and it works well enough for many purposes, even if it's not measuring any of those others.
I think when people say things like that, what they mean is "what simple number is the best predictor of success", which begs the question that a simple number can be a good predictor at all. Keep in mind that something can be the best merely because every other option is even worse: in practice, the best predictor is a really terrible predictor. So bad, in fact, that a five-minute conversation with somebody will tell you more about their ability to succeed at a job than knowing their IQ.
Got any citations to support this?
But when you try to put a number on that five minute conversation it turns out that the number is worse than the number provided by IQ tests. Otherwise the simple number from conversations would be well known to be a stronger predictor, but nobody has found such a result.
[1] https://twitter.com/richgel999/status/1506870732889985025
Who knows this? I sure as hell don’t and would be extremely surprised if that were the case.
every other method of selection, e.g. structured interviews, work samples, etc, are (noisier) proxies of general mental ability.
Not sure why you would use a paper as a "standard reference" when flaws in its method were identified almost 3 decades ago.
Your in group membership is what propels you forward in your career, not your intelligence. Race and Gender are predictors of career success as well.
Any proponent of IQ, I'd challenge to take an IQ test in Chinese, Irish, or AAVE.
I'm not sure a construction company wants a bunch of people with 140+ IQ standing around all day leaning on shovels waiting for gravel to shovel into little holes. I'm pretty sure those employees will just quit or break something on purpose just for something to do. In fact I've seen this with my own eyes.
Maybe you're proposing binning people by IQ instead? Where groups of people who fall in certain ranges of IQs are sorted into different jobs.
But again, I'm not so sure that Walmart wants to hire a shelf stocker with an IQ between 88-95 if that person has oppositional defiant disorder and/or a tendency to steal from their employers.
If you think that you can distill the essence of an entire human down to a single variable and rank them accordingly for jobs, go for it man, but I have a sneaking feeling that it isn't going to work.
I'm quite convinced that a typical construction site would benefit a lot from employees who would be smart enough to notice inefficient processes and plain mistakes, and take some initiative to fix the problems. And management who would believe the employees, but that is probably never going to happen.
Sounds like a smashing idea, I'm sure you'll kill it in business.
However, thanks to the way mental traits get distributed, a fairly small proportion of the population is ever going to have a high IQ. Roughly 16% of the population at any one time will have greater than 1 SD north of median. Less than 3% will be greater than 2 SD.
More people than that need to have jobs. If you're going to insist only 97th percentile people can work for you, you need to be offering 97th percentile salary. Currently, that is around $220,000 a year in the US. "Most" jobs can definitely not offer that.
It's on you to back up this claim. And the reason had better not be 'oh a bunch of tech companies do it' when there are entire fields from psychology that do research on this exact question, and they consider things like personalities, etc.
You also might be confusing higher-iq job scopes for job success.
WRONG. WRONG. WRONG.
IQ predicts how fast you learn shit, not how well you do on the job. Plenty of studies from the fields of personality/social psychology/psychometrics talk about this, get out of your narrow SWE field and read up on these subjects. This IQ=job success belief is simply SWE self ego-stroking.
edit:
Jordan Peterson (psychology phd) - The Mystery of High IQ and Industriousness https://www.youtube.com/watch?v=1C0zS2RAzlI
Wow, so many people react so sharply to this, I'm not sure why. May be there is an inherent belief that all one has to do is work hard and success will follow.
Minor nitpick - I think performance has a good correlational with IQ, I think less so a job, because a job also generally requires high conformity (not an enviable trait IMO)
As it became clear the people had lost belief in god kings, aristocrats began paying the church to educate their kids and confer nonsense degrees the proles could not falsify.
It was not hard learning guitar on my own. We create a lot of carbon mess for junior to get to an official guitar degree.
There is a whole lot of unnecessary LARPing deference to wealthy people who don’t do much of the real work keeping themselves alive.
It’s not a sustainable social meme to tighten the screws on the masses while handing their own kids the keys to the castle. 800,000 sworn LEO in the US, beholden to a paycheck and retirement account. None of the people at my local bank own that bank anymore. Why is my agency propping up someone else’s grandpa?
All of this was absolutely relevant in 1950 for working at a large corporation, in a white-collar job.
The more recent job market doesn't look much like this, but then good training for the current job market would probably not call for an institution that looks much like a university. It would probably call for something more like trade schools and apprenticeships, with guilds to protect the apprentices from poor treatment (something that, for example, Ph.D. students are sorely lacking). It seems unlikely that universities can adapt to a situation that primarily requires that they go away or at least become much smaller, to be replaced by a different system.
Therefore, they mainly ensured companies hired people from similar university programs that the test givers also attended.
Everyone is optimizing for getting the most information in the smallest amount of time. Algorithm questions do that. The interviewee knows that they are going to get algorithm question, and most places tell them ahead of time what the nature of the questions will be. So interviews should be an easy cakewalk that everyone can pass, but they aren't.
>So interviews should be an easy cakewalk that everyone can pass, but they aren't. For a person with no CS degree this is definitely not easy and being flippant and saying it is is disingenuous.
I think its almost universally agreed at this point that Algo interviews don't have anything to do with day to day work and don't demonstrate development ability.
It seems no matter how many great projects I make, or quality papers I write, that's second best to 10 minute logic puzzles for a growing amount of companies.
As with most development team leaders, I have interviewed and employed CS graduates who are woefully unprepared for the reality of a job writing production-level code.
I don't see this as a condemnation of education per se. More that the common concept of education (that it prepares young people for their careers) is completely misaligned with academia's concept of education (that it trains young people in how to think, and how to conduct research).
[0] attribution for this is interesting and varied: https://quoteinvestigator.com/2021/04/02/computer-science/
IMO this is what a university education should look like for most people in order for it to stay relevant. There are otherwise far more too many people attending universities relative to the demand for researchers.
The university that I got my actual degree from was something that a SV company would scoff at. But, the education they were able to scrap together was far more effective in my day-to-day work than prior education I had received at a far more prestigious institution.
Perhaps it was just me, but it always seemed like the less money I spent on my education the more effective it became.
Remember it doesnt take any qualifications to set up a business.
At those points in history the degree was worth it because it was a signal of your social standing. You would walk into the office as the boss simply because you had a degree.
Today college is not elite. The vast majority of US high school students now go to college. 70% of those students take out loans to afford education. Because it is no longer elite "teaching you how to think" is no longer a great value proposition. Not to mention that most of the new grads I've met have failed to learn "how to think" as well as having no practical skills.
I think the number is something around 60%. Not sure that would qualify as Vast Majority.
I'd be surprised if most universities didn't offer something similar. Even students at Ivy League school must want to get together with other students and learn to build useful software during their first year.
Like most professions, there's a lot of "extra" stuff around the core competency. Knowing Excel does not make you an accountant.
I've come into projects as the architect for refactoring what was built by someone who had only just learned to code. It was bad, sure, but they were bringing in enough revenue to hire me and get things on course. All with 0 knowledge of devops and 0 lines of test code coverage.
Actually, those three 3 month engagements can constitute several years worth of experience if they are done with excellent mentors at good companies. Reasons:
1. You see several teams, several projects, several codebases, without having to spend an awesome amount of time at one place. How many engineers work with multiple teams and companies in their first year (without one of those experiences being terribly catastrophic)?
2. You get the interesting meaty projects, or get to work on prototyping projects, but are also expected to contribute to the existing code base (or at least build on top of it). You participate in meetings, give presentations, etc. Basically, you see an entire compressed project/product lifecycle but embedded in an existing codebase.
3. Most importantly: Doing 1 repeat internship is super valuable. Spending 6 months at a place in 3 month increments with 9 months in between is an exceptionally unique experience in terms of understanding how orgs work and evolve. Most engineers don't get to experience until they are in the consulting portion of their careers.
University students in CS should do as many internships as possible, and universities should be more proactive about finding a way to mock summer internship experiences for students who do not get any internship offers.
Atlassian made some comments like "Australian universities aren't teaching devs what we need them to know" a few years back. It triggered some discussion, but not nearly enough along the lines of "well maybe you should train people in what you need them to know then?"
As an industry, we're utterly crap at employing juniors, or training our staff. We expect everyone to have X years of experience and then get surprised when devs make technology choices based on what's good for their resume, not what's good for the business.
there's a full rant I have for whenever this subject comes up ;)
As an alumni (kinda), it was awesome and IMHO has served me very well in my career.
But, really, if company wants to retain people after training, maybe make it worth it to the people to stay.
Lots of organisations seem to think that if they have to train an employee, then there should be some kind of discount on the salary for that employee. This is totally the wrong way of looking at it.
Training your staff in what you need them to know means that they have a consistent view of the subject, practices, etc. No more "but that's how I've been doing it for 2 years in the last place" or "I taught myself and discovered this way of doing it and I think it's cool". A junior employee who was trained in the exact tech stack you're using is more valuable than a mid (or even senior) who has random experience.
Not to mention, if your employees trust that you'll train them in what they need to know, they're massively less likely to pick technologies based on resume need. And massively more likely to stay with you.
Also, it should not take long to train someone git or test framework.
My personal option was they were wasted courses. The learning was in the coding, not project management and documentation.
I can teach you how to use git in an afternoon. I can't teach you how to write a thorough but concise email about a complicated topic. I can't teach you how to give a good presentation. (Or, I can, but it will take a lot longer than teaching enough git to get started.)
(To be clear, all CS departments should teach students how to use git as a component of the intro programming sequence.)
But they don't. If they wanted to students to think more deeply, there would be more of an emphasis on formal logic, developing proofs, etc. rather than "write this in assembly." If they wanted you to conduct research, you would...conduct research.
STEM degree fields are so obviously career-based. There's a reason Merck internships go to biology students, Lockheed internships go to aerospace students, Google to CS, etc. But when people call out universities on how poor of a job they do, they suddenly claim career-based education isn't the goal. It's a widespread CYA move by vastly overpriced universities.
The claim that a university education doesn't do this feels very subjective. My CS course did all of those things. Every student was required to do a research project in their final year for a significant part of that year's credit.
At the high end, you have places like MIT/Stanford/UIUC//Harvey Mudd. As far as I can tell, none of the bad stuff that's said in these threads is even remotely relevant to the programs at those places^1.
At the low end, you have branch campuses of state universities and small colleges where half or more of the CS courses are taught by mathematicians who did not study CS, have never worked on even academic code projects, and have never worked as anything other than an academic^2. This is pervasive in Data Science. You're way better off with a boot camp than a data science sequence taught by a desperate pure math PhD taking whatever work they can find.
And there's everything in-between.
A lot of these debates are probably happening between folks who went to good programs and folks who went to mediocre/bad programs. Not all, but quite a lot.
So, when reading comments on HN about how useless or wonderful a CS program was, always ask (at least rhetorically) "where did you go?"
I gave the big famous names because that's the easiest way to make the point. There are tons of really high quality programs whose names you won't immediately know. My intention here is not elitism... BUT!...
It is 100% true that the quality of CS programs is incredibly varied. Way more than it was even 10 years ago. The rapid increase in enrollment and unwillingness to pay even half decent wages for CS faculty has caused an explosion of what I would characterize as fraud in CS higher ed.
So, in the spirit of helping parents identify good programs without depending on name recognition/elite signalling alone:
When deciding if/which college/university to send your child to, carefully read through CS faculty bios. Ideally there will be a good number of faculty with street cred in both academics and industry. In addition to checking out CS faculty buios, also check out the names of instructors in previous years' course schedules. For example, make sure that CS/Data Science courses aren't being staffed by math folks unless those people have significant industry experience in addition to their math phd, or work in an area of applied math where they're doing lots of coding, etc.
Checking who teaches the courses in archived course schedules is more important than department bios! The department bios are a first check, not the final answer. Here's why: at many places you'll have a few half decent CS faculty who are just "fronts" for a department that is mostly staffed by way lower quality labor. It's the EXACT same bait and switch as consulting shops who have super experienced principal/senior-level engineers participate in the sales pitches and once the ink dries you're working with cheap grunts in a body shop.
Three things to watch out for in particular:
1. Non-CS (usually math) phds without substantial industry expertise. They're teaching tons of intro DS/CS courses instead of taking a math job in industry or academia for a reason.
2. Folks with an online masters and maybe a year or two of full time industry experience.
3. Tons of CS courses being offered in the evenings or early morning by faculty whose names don't appear anywhere on department websites (these are industry workers doing ad junct labor... they can be EXCELLENT, and if you get a course taught by one of these people in the middle of the day it's often a gold mine. But if they're always teaching around the 9-5 schedule it signals that their employer considers this a side gig and the course's quality is probably going to depend on how busy things happen to be that quarter at the instructor's "real" job. Okay as an occasional stopgap or an option, but a huge warning sign if this is a standard modus operandi for core courses. Teaching well is a big job; doing that plus engineering wi...
Fussell (and probably many others, but I've read him) blamed the rapid, great expansion of colleges and universities when the GI Bill injected a ton of money and eager new students into the system after WWII. He wrote that in 1983, but the system still seems to be reeling from that, and it may simply have stabilized (perhaps unavoidably, hard to say) at a much lower average quality level than before. Generally, institutions that existed before the war are still very good. Ones founded or converted (from, say, teaching colleges) after are much more hit-or-miss.
CS is embarrassingly bad even relative to the already low standards.
I'm not exaggerating when I say that many computer/data science programs are 100% staffed by pure mathematicians who both have never done academic work in computer/data science and also have never worked a day in industry.
Find me a single mathematics department that offers a BS in Mathematics and in which 40+% of courses are taught by failed psychology PhDs. That's the state of CS at many institutions.
Again, I take your point that everything is not great. CS is a whole order of magnitude worse. Even at places that aren't great.
The person above you complained there weren't enough proofs in CS degrees, so they probably attended a program that was more focused on relevancy for the industry, while I and others attented programs very much geared towards academic research and theoretical CS, which contained a large amount of maths, often taught by math professors, and involved proofs in pretty much every course, even things like Intro to OOP.
Both of these programs have their place, I'm very glad I attented a program that was very theoretical, since I was able to pick up job skills on the side, while the things I learned in my degree I would have probably largely not been able to teach myself.
No, I do not. Is that really how you would describe any of the specific institutions I mentioned?
A good program should have some of both, and two equally good programs could emphasize one or the other more. All of the positive institution examples I listed have very rigorous theory requirements in their undergraduate curriculum, for example.
> ...which contained a large amount of maths, often taught by math professors, and involved proofs in pretty much every course, even things like Intro to OOP.
The problem is one of quality, not the "theory vs practice" axis.
A mathematician can do a great job at teaching pretty much any CS course. But, also, within the last 10 years, a CS/DS major staffed largely by mathematicians or folks without terminal degrees has become a VERY predictable sign of a low-quality department. These two things aren't contradictory.
Have you looked at the composition of CS departments at unselective regional institutions, or CS faculty ads for such places? If not, consider this exercise. Things have gone downhill fast in the past 10 years, and the current situation in CS for regional colleges and universities is very much "caveat emptor".
Then gave the same text/test to graduating undergrads.
The thesis being that they just spent 4 years being trained in how to critically think and analyze a text.
There was no difference in their performance
Outside of their profession, they uncritically accept silly ideas as the truth and throw all logic and reason out the window.
Which is exactly what a CS program from a reputed university is. We never once touched assembly. Heck most classes involved no coding at all.
What I think is there deserves to be one or two full pledged software engineering courses, teaching how to use testing, version control, software structure etc.. As always, you can start from basic commands / usage and reach to general concepts, it isn't that hard.
And actually I believe US and European academia, at least the Ivy league and second tier colleges, do a decent job at teaching many required concepts. Come to a country like India, and you will see a C programming course that doesn't cover malloc or function pointers, a data structures course without proper introduction to algorithm complexity or difference between abstract data type and implementation, a java course that never properly teaches subtyping. I think students in US graduate decently equipped to write real world software compared to us. At least, I learned a lot of things by reading notes and Ppt of US universities.
(most Indian colleges are woefully inadequate in teaching even the basic concepts for writing software, despite the CS courses being named CSE (comp sci and engineering), not just CS. Incompetence runs to the root in education system except few elite colleges. From that perspective I think CS depts saying that is a first world problem. Sorry for the rant.)
I'm only in my forties but it's incredible how much this has changed in my lifetime.
I remember talking to an intern a few years ago and they made a comment about what a joke Columbia is (in regards to master's students). I was shocked because when I was a teen Columbia was seen as incredibly prestigious. I argued with them that Columbia is a really prestigious, well regarded school, but they and a few other interns just laughed and rolled their eyes.
Looking into it more it became obvious how this view had changed. It turns out Columbia, like many top tier schools from when I was a kid, has basically turned into get fancy version of a degree mill for master's students. Even though the school boasts some impressive faculty in many departments, it's also clear, based on the grads from there I have worked with after this conversation, that very little of that prestige is passed on.
As someone who used work in academia, it's wild how rapidly the entire system has decayed. From publisher or perish culture creating a mountain of non-reproducible work, to schools across the spectrum rushing to exchange credibility for cash. There have been so many systemic errors made that I don't believe academia will recover.
I suspect we'll see a fairly massive contraction in higher ed in the next decade or so.
In many other fields that have advanced degree requirements, companies care far more about where you went to school and who you studied under.
For example - I have a friend that is an occupational therapist. They've had 5 different jobs in the last 10 years. Every single interview they've done has been mostly just a meet and greet. No real difficult questions, no tests, no trial periods. They just applied, the company saw their degree and experience, and the interview was simply there to make sure they could work together.
It turns out that there’s very high correlation between the characteristics that make successful students and those that make successful workers. So a degree is still a useful signal during hiring, but it doesn’t certify a specific level of competency or skill set.
That is completely wrong when applied to e.g. Engineering. And completely true when applied to e.g. Philosophy.
CS courses on the other hand vary in their position on the spectrum.
No university has any incentive to say no to someone who wants to pay 200k to have you grade some homework for a couple of years, as long as they aren't at capacity, and moreover very small incentives to fail them.
The irrelevance of the paper as a signal is the solution to this problem.
That says more to me about the companies practicing this style of interview than it does your degree or the institution granting it.
I think this makes a lot of sense and we have a system that allows you to get a well paying middle class job by completing a vocational education and offers paths to get higher education from there or even switch to the academic track. This always made sense to me and I think it's crazy how this is in other countries where the choice is going to University or learning your profession on the job.
On the other, preparing for the test is not gaming it. Fundamentally, if there is a test, it is entirely legitimate and expected to prepade for it. Especially when the test measures skills you rarely use outside of test.
I had a group project in 4th year university, in a very difficult math-heavy advanced graphics course, and my partner provided me with his half of the project and it was all global variables named A through Z, with a few A1,A2,AA,AB thrown in, and reused extensively for different purposes.
His code actually worked but it surprised me that someone could do 4 years of university (in a good CS school) but have almost no talent for actual coding.
1: https://thedailywtf.com/articles/the_brillant_paula_bean
In the same way that height among professional basketball players may not be a great predictor of their performance relative to other players, but you don't see too many 5ft players eithers.
I think if you’re working with really advanced topics, the credentials start to be meaningless, because the important fact is whether a candidate can truly work with complex concepts/technologies. You expect the candidate to come in already knowing what they need, and you don’t need any assurance that they’re “trainable.”
But for most of us here in the middle of the pack, the degree is more meaningful because it shows that at the very least, a candidate has been exposed to slightly higher-level concepts. As an example, when you’re trying to get someone to step up out of a help desk role into an analyst/developer role, that’s a lot easier to achieve with someone who’s had at least a degree’s worth of exposure to concepts of strategic thinking, lifecycle management, development methodologies, etc. Most of us don’t need to be passionate geniuses to do good work. For us non-geniuses, the conceptual “scaffolding” provided by academia opens up a lot of potential. I definitely believe that some people don’t need the degree, but they probably aren’t the average Joe.
we need nothing short of a cultural shift toward incentivizing real progress and productivity, and valuing real knowledge rather than education, which we only had for a fleeting moment in the US (middle of last century), that only comes from really constraining markets toward both fairness and risk tolerance. we lost our way when we loosened our belt in that regard (for instance, we now instead reward to act of having capital rather than deploying it strategically).
In Europe this became known as the "Bologna process" in which established "academic degrees" literally - in a EU-bureaucratic hunch and self-aggrandizement - got thrown away overnight (in Germany: Diplom, Magister) and then modernized, accordingly rated and standardized in a modular fashion, repurposed for the international/European (labour) market. The faculties and universities themselves from then on were run in a more and more managerial fashion with "operating numbers" and by winning state-funded budgets ("exellency" programs) and by efficiently recruiting third-party sponsoring.
For a typical (german) undergraduate student there isn't much a difference between school and university, anymore. Most Gen X'ers (and Baby-Boomers for that matter) will readily tell you how they for the first time had to learn to resort to self-reliant learning in want of detailed instructions (like in school) but also began to appreciate the less strict scheduling not only for partying but for developing their critical thinking in heated arguments with peers or when confronted with challenging ideas. This is mostly gone, now, a big part of that former public space has vanished.
For attaining craftmanship a particular skillset for a particular field, universities were never a good place to begin with, that's what internships and later your chosen vocations are for. But if they don't prepare you for the labour market and don't provide you with some kind of Humboldtian ideal - a universal starting point with sufficent leisure in pondering about the right/critical questions to ask in a nourishing environment - so what are they actually for?
It also says:
1. We don’t trust your former employer to restrict promotion to quality employees only. After all, people have to do the leetcode interviews all over again when applying for their next job.
2. If you’re new to the industry and weren’t enough of a chump to take out student loans, you’re welcome to try your luck here
The funny thing is, all those leetcode questions are just the kind of thing that's taught at CS courses (algorithms and datastructures) and the kind of material that CS grads are likely to know well. And the people who interview you are more often than not graduates themselves.
Because, duh, tech companies are part of the same establishment as academic institutions. But don't tell them that because they all want to be disruptive, instead.
Academic findings only have so much scope. It's nuanced and the news reporters, kindergarten teachers, and scientists themselves often overclaim the impact of the findings. All of the short term incentives reward overclaiming over nuance and no one should be surprised that the zeitgeist is where it is.
What's difficult is that it's hard to communicate the nuance of what a study actually studied. How many people were involved? What were the methods used? What was the effect size? What were the confounding factors that couldn't be controlled for? None of this can be effectively communicated in a world that reads headlines and probably not much beyond that.
And of course, the media does sensationalize because they're incentivized to. You'll click a headline that says "alcohol is good for you, says science" but probably won't click a headline that tries to communicate the nuance.
People seem to feel compelled to form an opinion on every topic, and then think that whatever their take is must be informed.
It is okay to not have an opinion on a topic!
If someone is particularly interested in obtaining an armature understanding of a subject, by all means, they should jump in and form on opinion, but maintaining some humility is essential.
Further, the criticism of academia as being full of egg-headed elites who are completely disconnected from the public need has been around for decades - far longer than the current systemic funding and tenure problems.
The public have been bombarded with ridiculous, counter-intuitive "science" for decades, only for a lot of it to be quietly withdrawn or superceded later. It erodes trust.
And that's without taking into consideration the shady corporate-science bullshit like the fat vs sugar debate in nutrition science. If a company can buy a paper that says whatever it wants, and get it peer-reviewed and published in a journal, why would we trust science? Should we even?
In medicine, the Journal of the AMA and the New England Journal of Medicine seem to be the main sources of articles that reach the public's eye.
The editor of the New England Journal once complained that it was troubling how papers that had only tentative results, more suggestions for further research than conclusions, would get blown out of proportion in the mainstream news media.
Some of the burden is on the journalists, not the researchers.
And of course the journals could make the scientists reframe their papers so they're not catnip for journos.
How do they do that? Start suing news outlets?
But I do agree that at least one of the main problems is that academics have the ability to sift through research while others don't. So better self policing and an easier way for the public to digest the information is probably what's needed here. I think the problem here is that the public don't trust the scientific community to self police.
>Further, the criticism of academia as being full of egg-headed elites who are completely disconnected from the public need has been around for decades - far longer than the current systemic funding and tenure problems.
I think the internet and social media just really took the mask off for a lot of people. The tribalism probably kicked into overdrive when they can just look researchers up and actually confirm that the scientists are part of their outgroup.
I'm not sure that better self policing is a good idea. I think we want academics to be exposed to a sea of research, much of which is half baked or has big flaws. Preventing the "probably wrong, but maybe something is here" papers from being discussed limits the ability to actually make big things happen. There is simply an education problem where laypeople (and media) have decided that peer review is something that it has never been and a huge amount of misunderstanding (deliberate or accidental) of the scientific community derives from this.
> I think the internet and social media just really took the mask off for a lot of people. The tribalism probably kicked into overdrive when they can just look researchers up and actually confirm that the scientists are part of their outgroup.
I think this is definitely true. When TPUSA can basically publish an "enemies list" of academics they don't like the end result is a stream of harassment.
Kudos for retracting. Integrity is probably more important for science, than intelligence (not meant as offense, there are a million reasons a experiment can produce odd one time results).
Too many published results seem to not be reproducible anymore and not many are even trying, as there is little benefit in reconfirming findings, but rather incentive to publish, publish, publish. Quantity over quality it seems. We somehow need to change that again.
This article is a nice overview of the modern moral panic gripping academia and spilling over into everything else. At this point laypeople are right to question academia as it's once noble purpose has been totally coopted by ascientific progressive politiking.
The US has a focus on "input legitimacy" which is partially "we do it the way they show in Schoolhouse Rock", and partially about the way politician's communication styles make people feel.
The Chinese model based on "output legitimacy" (do institutions demonstrate competence in action) has its own problems (what if things go wrong that we can't control) but should be at least partially emulated in the West. (The flip side of "what if things go wrong" is a reflexive habit of making excuses, sometimes even before they're needed.)
If Ukraine survives, for instance, winning the war will make the Ukraine be perceived as one of the most legitimate in the world as opposed to an illegitimate cesspool of corruption. It is astonishing how 2014 was a wake up call for Ukraine to build up its military competence and how Ukraine responded to that.
http://www.bbc.co.uk/news/av/world-41521671/100-women-amy-cu...
Very doubtful. You just need common sense. Like, if this actually worked then you'd be seeing it spread very fast everywhere, but in reality it apparently needs a constant flow of TED Talks to get people to take it seriously. Ditto for priming studies, etc.
More recently there's been COVID. The problems here aren't exactly the same as the replication crisis, partly because nobody seems to try and replicate anything in the first place. Really IMHO the problems are much worse. Nothing could possibly destroy confidence in academic and public sector expertise faster than being told masks don't work, followed by they work so well they're now mandatory, followed in turn by seeing case graphs where switching mandates on/off very clearly has no effect whatsoever.
The constant flow of bad models that were never acknowledged is particularly destructive. Most people can't articulate why the models always seemed to be wrong except through vague generalities like "bad assumptions", but it doesn't matter. Epidemiological modelling is toast in the public mind, along with the lockdowns they led to. The understanding that they're unreliable is fact based, not emotional, even if the details aren't there.
At any rate, having done deep dives into too many trash COVID papers in the past two years, I can't say knowing the exact details of why they're wrong makes much difference. The important thing is actually the social problems surrounding them, in particular the lack of any institutional acknowledgement or response that there's an issue. Observe how discussion of the replication crisis started with and still mostly comes from individual researchers, not institutional leaders. We can see there is no psychological acceptance of how badly they've been getting it wrong because, for example, Imperial College London (home of Prof Lockdown himself) just banned parents from attending their children's graduation ceremony due to COVID:
https://dailysceptic.org/2022/03/31/imperial-college-london-...
This is at a time of record high cases and after the Queen got it at 95. Nobody cared, it was in the news for barely a day. ICL comes across as a delusional institution with this sort of act, and combined with all the stories of activist craziness on campus, it's getting widely noticed by the general public.
It feels very much like the author Thomas Prosser has an axe to grind when he includes this study of methodology (in a subsub field of sociology) with the larger issue of replication.
When there are statements in the article "Such results erode confidence in academic work", the confidence is only eroded in the papers that are bad, which is how it has always worked. Confidence isn't lost in every paper, or the scientific process, but laypeople and administrators see some stat about "30%" of papers have some error, then all of must science is wrong.
While papers remain the main standard by which science is communicated maybe there is a place for those in the scientific community that do know to be more vocal about which papers are worth reading.
https://fantasticanachronism.com/2020/09/11/whats-wrong-with...
"studies that replicate are cited at the same rate as studies that do not"
Confidence is eroded in all papers by this sort of thing, because academic structures are the same across fields. Whilst individual fields or labs may be more rigorous than others, people can't be expected to keep a massive database in their heads of which fields are good and bad. To be able to generalize about quality requires institutions that create quality, but universities don't do this. And because universities dominate "science" or at least the public discussion of it, that lack of quality control reflects on all science.
So what does this mean? The professors pushing the papers out are not doing their due diligence and there is no one else doing public checking. The loop is open. It is not science. That's the crisis.
Social science has always been full of incertainty and biased results, it seems rather normal the public don't trust it blindfully.
Just last week or so there was a paper in Nature about how fMRI studies -- a modern backbone of neuroscience work -- have also been mostly unreplicable. This follows a litany of other papers showing the same thing. That Nature paper made transparent allusions to genetics which invested tons of money in studies which were also largely unreplicable, with fairly obvious power issues that were ignored. When the replicability crisis started getting attention, there were interviews with pharmacology corporation scientists saying that the pharm industry tends to internally assume that 2/3 of published pharmacology studies will not replicate when applied to the real world. There were studies showing that oncology had similar rates of problems, and so forth and so on.
The social sciences is fuzzy as you say but they also tend to turn the microscope on science itself first. Meta-analysis in its modern form (as opposed to early statistical methodology papers) comes from psychology; this is just more of the same. There probably are differences across fields but I think few fields are immune.
Also, I would push back on the idea that the general public's mistrust is limited to the social sciences. I would argue that issues with climate change skepticism are driven in part by a general distrust of academic findings and scientists, and many of the problems during the pandemic with skepticism about vaccination, masking policies, and so forth were driven by skepticism about biomedical research. Possner said "such challenges do not affect academic confidence in the reality of (say) climate change and Coronavirus"; I was puzzled by this precisely because I couldn't tell if he was being ironic, or pointing these out as areas where there is a contrast between academic confidence and public confidence in those findings, as if to say "well look at how much the public distrusts that; now imagine when academic confidence is eroded further?"
My biggest problem with the linked piece, in fact, is that it is framed around the question "what happens when the public loses confidence in academic findings" when that problem is already here to a big extent. We saw what happened during the pandemic. That's what happens.
Academics to some extent is falling apart, and it's not limited to the social sciences. The problems with misttrust are running deep and I think academic and political communities have their head in the sand, rather than taking their structural problems seriously. It's always the messenger: the irrational public, the muddle-headed social scientists who are exposing the problems, it's never the corruption in academics itself.
Eating eggs gives you cancer. Next week it protects you from cancer.
Coffee cause hearth problems. Next week it prevents heart problems.
And so on and on for basically everything we eat.
For some time, Kale was faddy, every study was recommending eating it. REcently, I read somewhere it gives you cancer.
groan
I'd rather know what to avoid, even if you think that question is "wrong" (I don't agree).
> Skip sugary drinks, limit milk and dairy products to one to two servings per day, and limit juice to a small glass per day.
> Limit red meat, and avoid processed meats such as bacon and sausage.
> avoid partially hydrogenated oils, which contain unhealthy trans fats. Remember that low-fat does not mean “healthy.”
I doubt it, and again it's excessively vague:
* "Limit"?
* "Sugary drinks?"
* "One or two servings" that's literally doubling the serving count. How can that be, where consuming twice as many of something is as fine as consuming half?
* Juices should be limited but my fruit and veg intake per meal should be 50%, that is contradictory information, unless you're trying to suggest blending things reduces its nutritional value.
* If that is the case, how blended? Should I not chop my carrots? Minced onion is worse for me than diced onion, should I just eat the onion whole?
* Is it better to starve than to violate these rules?
* What, specifically, are the consequences of violating these rules? If I, today, eat one additional serving of fruit than I "ought", am I cutting my lifespan by three days? Six weeks?
Even if you can answer every question I put up here, would you mind publishing your phone number so everyone in HN can give you a call every time something isn't covered here? By the way, what are your credentials? Why should I trust your assertion that this is a solved problem, or that your interpretations of this document are accurate? Why should I trust this website in the first place? Yes, it's Harvard, but I don't trust them blindly; how did they arrive at these conclusions?
Please, don't condescendingly link to a nutritional chart page and think it answers every question, or suggest this information isn't regularly changing.
Good questions. I have no credibility and I don't pretend to have it. Ask you nutritionist. I just read the official nutrition advises carefully. And you should too. Also, check the referenced research if you can.
> or suggest this information isn't regularly changing.
It doesn't for quite some time already. Also all changes have been explained. See for example: https://news.ycombinator.com/item?id=12480733.
> * "Limit"?
You probably don't have to avoid it like a poison. The less, the better, I guess.
> * "Sugary drinks?"
Every drink which contains a lot of sugar. For example, Cola and juice both have about 10 grams/100 ml of sugar. This is 2 table spoons per 200 ml. Compare to the recommended daily sugar intake.
> * "One or two servings" that's literally doubling the serving count. How can that be, where consuming twice as many of something is as fine as consuming half?
It must depend on how much calories you generally need per day. People are very different. If you need a personal advice, ask a nutritionist.
> * Juices should be limited but my fruit and veg intake per meal should be 50%, that is contradictory information, unless you're trying to suggest blending things reduces its nutritional value.
I don't see any contradiction here. Fruits contain not just sugar but also fiber which is necessary for a good health. See also: https://www.nhs.uk/live-well/eat-well/5-a-day/why-5-a-day/.
> unless you're trying to suggest blending things reduces its nutritional value.
This is not how I understand it. See also recipes from the HSPH.
> * Is it better to starve than to violate these rules?
In general, they recommend a diet with a great variety, so it's a "no".
> What, specifically, are the consequences of violating these rules?
There is a lot of info on that website. If you read that, you will see, e.g., that processed red meat increases the risk of a cancer.
And yet you're giving nutritional advice on Hacker News to complete strangers. Maybe remember your lack of credibility next time you claim a topic is a solved problem.
I'm just tired of lazy people who don't want to read the official advises and prefer to say that everything is unclear in the nutrition science.
You may be tired of people not being informed, but I'm tired of ignorant people thinking they know more about a topic than they actually do.
Care to elaborate? Harvard Public School of Health is a professional nutritional organization, isn't it?
> both less correct and even more vague.
This is a shallow dismissal, which is against the HN rules.
I'm always happy to be corrected and understand nutrition better.
Why does this distinction matter here?
> it's not a shallow dismissal, it's just a dismissal due to your self professed lack of credentials on the topic
I didn't provide my own advice (in that case, you would be right). I repeated a professional advice, possibly incorrectly, and you did not provide any explanation why you think it's wrong, just dismissed it. This is by definition a shallow dismissal.
secondarily, high glycemic index and low fiber, generally not as good as low glycemic index and high fiber.
its really simple
https://www.theonion.com/eggs-good-for-you-this-week-1819565...
Researchers Brock and Thornley of New Zealand published and then almost immediately retracted a paper linking COVID-19 vaccines and a much-higher-than-previously-found miscarriage rate. Scholar still lists the original paper posted---with no cover page indicating the retraction. (They do have a separate link to the retraction press release if you look for it.) The main result on Scholar links to a half dozen "not-so-academic" websites (ellinikahoaxes.gr, wokeguru.org, resistance-mondiale.com) hosting the same paper. I'm willing to bet even if the original paper could be removed, independent websites would continue to try relisting it.
While it's important to keep a record of bad research rather than scrubbing it away from history entirely, it seems feasible to have a reporting system in place for paper retractions, where the title link includes [retracted dd-mm-yyyy] or something.
This was my small taste of disappointment (aka loss of confidence) in a relatively popular academic tool.
When some X accumulates a track record of not working, people give up on X. Maybe then X will get improved, and slowly people will give it another chance.
The OP seemed to be mostly about the quality of the science in the social sciences. Hmm ....
But, in medicine, there are efforts to be careful. E.g., can test a new drug with double blind randomized placebo controlled trials. Maybe that methodology is good enough to be trusted? It appears that I trusted it when I got two shots and a booster from Moderna against Covid.
In math, hmm ..., if there is a claim of solid proof, published in a respected peer reviewed journal, and so far no one has found any flaw in the proof, then some trust can be justified.
The gravitational detection work of LIGO is astounding, and I'm trusting it. And I have yet to check in detail the math of general relativity -- it's on my long term TODO list!
And I trust the claims for the Webb Space Telescope, and the reasoning for its location at a Lagrange 2 point.
So, in medicine, math, and physics, I can have some trust!
For the social sciences, my view is influenced by my wife and brother, both of whom tried those, got Ph.D. degrees, etc.
For what it is worth, I happen to know that big tech companies follow research at big name CS universities with a bit of interest. At times, even borrowing the research itself in their products. At one point, a professor I worked under was quoted in Android documentation.
Where this matters is: academics used to be able to conduct pure research. Now all they do is fundraise and hustle for grants. Anyone used to be able to go to college. Now the gatekeepers decide who has enough money or connections to attend. We even used to have news and (gasp) investigative journalism and public broadcasting and periodic reports to the public on the state of publicly funded research or some great public works project. Now we have infotainment and the suppression of any real tech that might materially improve lives by reducing the workload of the average person. They only fixate on phantom tech that distracts and enslaves. Now wonder the public doesn't care.
If we really want to get serious about fixing this stuff, it's going to involve at least in some part, a total rejection of vast swaths of the status quo. I'm all for that, I think most Gen Xers are for that, and certainly most people younger than that are for that. But there is just so much concentrated wealth now diluting social movements. And so much momentum behind the previous generation in congress that will do everything it can to hold onto power in the face of so many calamities we face, because at the end of the day, it's not their problem so they're just never gonna get the memo.
If a spiritual revolution away from wealth concentration isn't already underway, it's going to start with some version of "your money's no good here." And individuals withdrawing their contribution from institutions which concentrate wealth and power.
I mean, it's not totally that. But it's sure a big chunk of the problem.
flat-earthers
half-joking aside, I have come to understand that the academic institutions are part of the state (perhaps I should say civilization?). the point being that academia (as the part of state that I'm saying it is) has a primary function of ensuring stability (same as the most well known face of the state i.e. government); this is mind-bending when faced with the idea that academic research is at the forefront of advancing civilization into uncharted waters (...a PhD must provide an original novel contribution...).
Seems that at some point artists became showbiz employees and at that same time, only scholars kept 'advancing the state of the art'. Which is a role historically fulfilled by real artists of the sort that ain't doing it for money nor fame.
Of course we can't verify the entire involved knowledge any time, and that's why the concept of collaborative peer review was born, not much different than the concept of "chains of trust": interest researchers in something verify some others publications and add up their own confirmations or doubt, "the network" do the rest.
The problem there is that such review and network does not really exists. Oh yes there is the ArXiv, HAL, ... papers circulate etc, but the "mainstream" is a network of hi priced journals and hi paid corporate-backed research + equally hi paid PR in the press. That's why people loose confidence: they do not have ontological means to know but they smell actual Science is mostly commerce and just very little Science.
IMVHO the sole way to correct that is build the above mentioned networks. Public, publicly well-founded universities that do research and reviews for the society, very-well separated from the private sector, and share this knowledge with the entire world. At that point the SciHub will be a public, legal and well founded platform and PR can do something but not enough to contaminate knowledge for private interest. At that point people would still not be able to verify, witch is not good, but they have something worth their confidence.
Thing is, the data published by the coroner's office didn't include a lot of fields that I'd already received from FOIA. Fields missing like the name of the person who died. Since the paper's conclusions didn't pass a gut check, I dug in and found that just glancing through the names of those marked down as "white", a majority clearly had names with Hispanic origins.
I shared with the researcher that his findings were probably really, really wrong and I was responded with something like, "even if 50% are marked wrong, the findings are still accurate". Some name comparison [1] and spot checking later.. and it ended up being about 80% of hispanic-origin names were marked as "white".
The researcher eventually conceded that the paper was wrong, but it was definitely of an eye opening experience into how the academic world works. I lost a lot of faith in the academic world after that.
[1] https://www.census.gov/data/developers/data-sets/surnames.ht...
I did ask around with these exact concerns in-mind, which led to this paper by the census in their evaluation of this exact problem (the Passel-Word Spanish Surname List was what I compared against): https://www.census.gov/library/working-papers/1993/demo/POP-...
So, I get it, and I had the same concerns as you, but I like to believe I followed proper due diligence in making sure my approach was reasonable. Especially against the risk of the paper being published (consider how the paper could be used in racist narratives).
For example, someone with the name José Santiago Hernández very is unlikely to be Germanic-white versus Hispanic-white.
I would argue instead that you have demonstrated the importance of peer review (a cornerstone of academic research). The problem is not really academic research, but that we do too little of both academic research and peer review.
First, as you found, there was no correlation between deaths and descent. Presumably there weren't statistically anomalously fewer Gomezes than Smiths.
This doesn't eliminate the fact that people wrote down fewer dead as Hispanic than as white. So:
Second, there actually were fewer dead Hispanics than dead whites, understanding "Hispanic" as "a person who looks Hispanic" and "white" as "a person who looks white".
Third, or alternatively there is no statistical difference between dead Hispanics and dead whites, but somehow fewer dead Hispanics ended up at the morgues to be written down as dead.
I have the same opinion of academics - show me what you can light on fire. For example, I don't believe in physics because it makes intuitive sense to me, on the contrary, I find it confusing and counter-intuitive (sometimes). I believe in physics because the people who make magic boxes of light and sound that move fast and connect across vast distances tell me they did so via the knowledge they derived from physics. It's not how I would've guessed the universe would work, but who am I to argue with a blazing altar?
Judging by this standard I find many academic disciplines are severely wanting - there is a lot of chanting and waving of hands, but very little smoke. If I hear on the news that there's going to be an eclipse, I'll go out and look. If I hear on the news that eggs are bad for you, I'm going to roll my eyes.
“Now faith is the assurance of things hoped for, the conviction of things not seen.” - Hebrews 11:1 (ESV)
Belief is not a synonym for faith.
Faith implies belief without requiring any evidence. But belief can be conditional on evidence.
(That didn’t turn out to be a good definition, but not because of the “belief” part.)
Belief can be informed by evidence or not. It simply means acceptance or confidence that something is true. You can have faith in the available evidence, or faith in the absence of evidence.
Most people will never understand the direct evidence of even relatively mundane science, and almost everyone is incapable of understanding the direct evidence of the cutting edge.[0] and its implications, ergo in lieu of understanding they must substitute belief. Where science policy/communication fails here is in producing a 'believable' system, with adequate consistency and storytelling for persons who will only ever understand by analogy.
[0]Regular people don't know what an integral is. The intelligent, educated, and motivated don't have the bandwidth to really understand more than a smattering topics deeply.
It's not fatted calves, but we do sacrifice some money to the quantum folks so they can break our enemies' encryption locks ... in like 25 years ...
(*Or “convincing evidence.”)
Those with faith have proof or evidence that can be used to demonstrate or to back up that faith. It's not blind.
> I have the same opinion of academics - show me what you can light on fire.
I don't know if you're going to be welcome in a lot of liberal art colleges, since this is the ending(SPOILERS!):
> And Elijah said to them, “Seize the prophets of Baal; let not one of them escape.” And they seized them. And Elijah brought them down to the brook Kishon and slaughtered them there.
I suppose that’s an early instance of p-hacking.
Ah... Good, Old-Fashioned Organic Agriculture.
There's a huge power in knowledge consensus. It's got all kinds of flaws, but it meanders generally in a growth direction, and that's better than any other prediction system I'm familiar with.
What you instead want to look for is:
"MANY people who are familiar with magic boxes tried to make this guy's magic box and couldn't replicate his method."
You are looking for valid contradiction to stated facts to invalidate claims, not for a widespread consensus on the claims.
This is important because, as a single example, two people can use different methods to achieve the same outcome based on their own respective theories that have minor flaws but present strong evidence that they are in their entirety true. It is only by reconciling & finding the contradictions between the two that you can come out with a single VALID theory.
If I were a scientist I would probably have some examples of this occurring in the past, but off the top of my head I would suggest it is improbably that there has never been a situation where two competing theories that each had strong evidence were both eliminated in favor of a single unified theory that reconciled differences between them.
There is no room for laypeople in scientific disagreement.
This also has a reasonable take-away: sometimes lighting an altar on fire can be faked even when it looks real. Or, "beware the flashy demo". Fusion and especially some of the more shameless corners of AI come to mind.
My apologies if this stretches the analogy too far.
Alexa, set room temperature to 28°C!
1) Refusing to police non-rigorous fields invoking scientific authority. As the article notes, even rigorous fields are full of results that cannot be reproduced. The situation is even worse in non-rigorous fields. In his famous essay on cargo-cult science, Richard Feynman specifically called out "educational and psychological studies" as "examples of what I would like to call Cargo Cult Science." https://calteches.library.caltech.edu/51/2/CargoCult.htm. Yet today, there is a movement to accord any PhD the respect of the title "doctor," as if an EdD was an authority similar to a PhD in physics. People do this to be polite but it has grave consequences.
The respect people accord "science" is, at the end of the day, built on results. We trust doctors because they delivered concrete results that medicine men could not. In the long run, people will notice that EdD is often wrong, because it's not a rigorous field, and that will tarnish the credibility of everyone with a PhD, because the lay public quite reasonably doesn't understand these distinctions in rigor.
2) Allowing scientific authority to be invoked for political purposes. There is a difference between scientific results, and the value systems of individual scientists. Science can, for example, create a vaccine. It cannot address the political question of whether anyone should get the vaccine--that question relies on cost/benefit analysis that, in turn, depends on individual value systems. Or in another example, science can tell you the probability of spreading a disease in a grocery store versus a church, but cannot tell you whether grocery stores or churches are more important. Moreover, most people intuitively understand this distinction. There are, of course, some people who will ignore scientific facts that are as plain as day. But there are a lot more people who will chafe at feeling like they are being told "I'm smarter than you, so you have to accept my values." That, in the long run, will undermine their trust in scientific results.
And if we, as highly educated people who understand "science" are honest with ourselves, that skepticism may not be unwarranted. We know that biases exist in the system. For example, it is well known that publication bias exists: studies reporting positive results get published, while studies reporting negative results don't get published: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3341407/. As science becomes more politicized, it's inevitable that other kinds of publication bias will affect not only the reported results, but even the kinds of questions that are studied.
No. We shouldn't be putting so much weight on the title of "doctor" for physics PhD's either; several physics PhD's I know personally are absolutely barking mad, and there's a long history of physics PhD's getting over their skis on other fields like medicine.
Meanwhile, the usage of "doctor" that you're decrying here is the more historically well-established one.
Academics: Incentives are frequently to publish fast and often. This encourages work with less detail, higher uncertainty/error, and less impactful work. You simply cannot produce as high quality work in 3 months as you can in 1 year (or 3) or research. Often we want PhD students to produce 5 first author papers in top tier journals before graduating. That's 5-6 years to produce just as many top tier papers (realistically 3-4 given your first 2 years are more class based). It is possible to put out a high quality and high impact paper every year, yes. But this is also a very difficult task.
Journals: There's no need to explain this one to anyone who has gone through the review process. Everyone I know that has attempted to publish papers has had several papers where they question what the reviewer actually read because it definitely wasn't their paper. Or where reviewers are vastly under-qualified to review the topic at hand. These are common occurrences. (Note: this more often causes false negatives rather than false positives due to incentive alignments) This creates legitimate complaints and can often be misunderstood from people outside academia.
Reporting: We all have seen this. Things like "eating chocolate is healthy" and other things that are obviously wrong. We've seen universities oversell their research. We see news channels oversell or vastly misunderstand research (despite having easy access to experts and that authors are frequently happy to discuss their research). The public also doesn't understand things like confidence levels. They don't understand that we have a different confidence level in anthropocentric climate change vs how much healthier a glass of wine a day is. This isn't their fault though. We should hold the reporters (academic or news sources) accountable since their are structured to be the science communicators. Instead they are politicizing and adding opinions rather than explaining.
Politics: We all know this one. Everything is politicized. Not just that, but to the point where things are "left" or "right". If the left supports one thing then the right opposes it and vise versa. This is far worse than both sides accepting the issue and coming at it from different angles (which I've seen this happen and both angles also not be in line with the actual research). Covid is a great example: people on the left over-estimate the dangers and people on the right vastly underestimate them (these are not equally biased positions and I'm not claiming they are, just noting that both have errors, not the magnitude of the errors). Climate change is another example, where right denies and left only focuses on pop/hip topics like tree planting or banning straws and not larger issues. (I'll note that in my anecdotal observations it seems that the magnitude of error is frequently smaller on the left).
So we have a system where we aren't encouraged to do high quality research (not meaning it doesn't happen, there are a lot of researchers), research (of any kind) is difficult to get properly peer reviewed, it is poorly explained to laymen, and results become tribal. Why does the public lose confidence in academic findings? You tell me.
Should academic research be done in secret or in a way that actively prevents the public from accessing their results? No. Should we disabuse ourselves of the notion that the public matters to this process? Yes.
None of it matters to the lives of nearly anyone until it's gone through many, many layers of filtering. We, the public, ought to let that filtering play out, rather than meddle in the process