Ask HN: What are the best open-access journals for non-academics to submit to?

I don't mean to be harsh, but it's hard to see how your article is publishable in its current form.

An academic paper is a kind of conversation between experts. You need to describe the problem you're exploring, state what others have done in the area, and finally explain how you are contributing to the problem and show that your contribution is novel.

What you're writing about reads like a combination of philosophy and machine learning. The philosophy probably makes it unsuitable for a machine learning publication. I can't really speak for the academic philosophy side because I don't know the publication conventions there.

If you want to take this further, your first steps should be to identify the conversation you want to be a part of, and get to know the current landscape of that conversation (I'm mixing metaphors, but you know what I mean).

The biggest problem with this paper, as a published scientist, is that I read the abstract and had no idea what your paper was about. Your abstract needs to be more substantial, and cover a) the problem you're addressing, b) the approach you took, and c) the degree to which you succeeded.

Comments from a machine learning / AI focused PhD student. Sorry if I get a bit ridiculous below, I'm up to my neck in coffee and having one of my more "esoteric" days...

0) Golden rules:

- Readability & formatting matters.

- Know your audience.

- Context matters.

- Brevity is best.

- Be clear & concise.

- Abstract, General Intro, Aims, Background/Previous work, Method, Results, Conclusions, Future work => In that order.

- Most important: Nothing goes into the main body unless it makes a tangible, useful & clear contribution.

Some of the best papers are the shortest ones: I can read, understand and explain it to someone else in 1 hour. Among the worst are the 25 pagers that take me 2 days to realise that they aren't useful to me.

1) Footnotes

You aren't commenting code. If it doesn't go in the main text, why is it even there? It is distracting away from the important part - the main body of text.

It either lives in the main text body, a reference or the appendix. If it doesn't live there, then maybe footnote (e.g. a url to some very specific data you trained against).

Get very delete happy with them. For example:

- viii & xiii @ on page 3, xvi @ page 4 should either be in main body (if important, they don't look it), or deleted.

- Things like python commands should just get dumped in the appendix. No footnote / reference. A blanket "you can see all the commands used along with descriptions in the appendix". I'm going to look at what is in the appendix anyway. Because I'm a pedantic academic.

2) Formatting:

- Think about using a template like [1].

- Reduce your font size to 10pt please.

- If you are going to be very maths heavy, think about moving to a single column style. I, personally, find it makes it easier to read eqns and to follow their logic. Currently I have to jump from around the page and keep getting lost.

- For sections 5 & 6: Stop putting something in bold every paragraph. Bold is only to highlight when it's really important. The name of something is not really important. Prefer italics over bold, but even use that sparingly. How difficult was it to focus on reading this paragraph when the words keep changing shape?

3) Graphs & Tables

Graphs & Tables exist at the top of a page. That's the only place they live if they live in the main body. They don't have to be on the same page as where you refer to them, and you can group them together. Otherwise, appendix that stuff.

Else you'll to end up with blank space (like end of page 4 & 5) and formatting headaches later on.

You haven't done your results discussion part yet... When you do, make sure you don't talk about every single table/graph. Only talk about the results that are important. Otherwise it's guff that will bore your audience.

4) Structure:

You have so many sections that I need a table of contents to work out where I am. For a 10-15 pager, that's silly. Learn to love subsections. Especially those early parts.

5) Intro & Background work:

I have no idea what previous work this relates to. Is there previous work in the field? If so, talk about it. Talk about how you're improving it. Talk about what the context of this paper is.

Don't know what the context is? Then you better find out... People will ask!

6) Quotations

This seems like a technical paper, not an English lit assignment. If you directly quote anything, let alone a whole paragraph, it better blow my mind. I am afraid page 3, column 2 does not. Remove it. Just reference anything like that. If people want/need to know, they will read it too.

[1] https://www.ctan.org/pkg/ieeetran

well, until someone vouches for you.

My understanding is that whether or not endorsement is required is dependent on which "area" you submit to. And even if I'm wrong about that, "endorsement" in their terms is really just meant to mean "this person is not a total quack / spammer / etc." So don't feel shy about reaching out to people in the academic community who are potential endorsers and just ask "I want to submit this to ArXiv, would you be willing to give it a quick look and possibly endorse me so I can submit?"

If you already know somebody in the academic community, it would probably be better to try them first. But if not, it appears that ArXiv etiquette allows cold-emailing people... they just ask you not to blast requests out to mass numbers of people simultaneously.

Computer science in general is conference-oriented, and even more so in security. It makes sense, simply because by the time you get published in a journal, the state-of-the-art would have likely already moved forward. So it follows that the state-of-the-art work is centered around conferences. In CS at least, journal articles are used to meet the "requirements" for faculty positions and/or promotions (e.g., 5 journal papers).

On the other hand, in EE, journals are more prestigious in general, partly due to the slower-moving nature of the field. A 9-12 month wait to get your article into a journal is not a huge deal. Further, a journal article typically shows more "complete" work than a conference article would, because it usually takes much more time to fully validate your work (relative to CS, for example).

For instance, if you're presenting a novel low-power circuit, you could get away with a simulation and/or a hastily taped-out version for the conference paper (ISSCC is the top conference for this). But publishing your results in a high impact journal like JSSC will require that you have a fully tested version, etc.

Absolutely. None of the modern advancements in knowledge and understanding involve the waste of time known as "peer-review". See http://timecube.2enp.com/.

Something ridiculous like 90% of arXiv papers get lost in the sheer volume of submissions - 90% of it could be wrong (that's a made up number, sue me).

Just like flat earth or anti-vaxer theories on YouTube, incorrectly published work could be damaging and dangerous.

Getting peer-reviewed & published legitimizes the research work. It has been verified by a panel of experts.

Good for those start ups. I can't wait to attack all their Deep Learning APIs [1].

[1] https://openai.com/blog/adversarial-example-research/

"Proper" peer review could mean formal peer review which, indeed, has a lot of flaws. In the context of OP, however, just having any academic look at it and suggest improvements would probably already be a huge boon, regardless of potential funding or challenge: it achieves better knowledge discovery. Either form of peer review is pretty hard to obtain through arXiv.

> So, why would you want "proper" peer review nowadays?

Because I want other people to help catch my mistakes. Why wouldn't you want that?