People mention this in autobiographies. It’s discussed very often in some subsets of self-help and self improvement materials as it relates to taking charge of one’s life, dealing with discomfort/anxiety and whatnot. There’s an empowerment aspect of it all, to “owning your name” as a form of building confidence. I think it’s kind of silly to need a study to “find” this, and I’m not saying that in an “it should be obvious” sort of way, but more so in the fact that some things will not be easily studied or observed or obvious, but when we point it out we have at least an anecdote of having experienced it in some way. More importantly, perhaps, is if a study came out claiming otherwise I would readily call it bullshit because of the aforementioned autobiographies and self improvement processes.
Good example is the musician will.i.am. That is a liberating name for anyone who sees themselves as having an inherent capability to realize their internal, often creative or artistic goals.
I believe this and other things related to names to a certain extent (without statistically significant supporting data).
I've been told I look like a Kevin (I imagine more like the Minion rather than Costner), who tend to be shit-disturbers for the fun of it. Not my name BTW but I'll take it as a compliment.
* Calling p = 0.062 "marginally significant" (Study 1, child perceivers, adult targets) rings my alarm bells.
* The adult photos used (for studies 1/2/4B) are headshots from an Israeli casting agency. Are there any stage names in use? The child photos are all twins from a twin study the same lab was running. Those seem like, uh, different datasets, with no attempt to control for differences between them. What are the results if you use child actor headshots. What are the results if you use random adult twins. Come on now.
* Any control for real correlations between name and visible features like race or class? The false names in the multiple-choice question were taken at random from the set of names in the dataset. The mean accuracy (for photos of adults) was like 30% - was that more or less even across photos? Or is the average dragged up by a few photos? Imagine an American context: how much of this result is from people correctly identifying the black guy as Darius or Hakeem (or from correctly identifying that the white guy ISN'T Darius or Hakeem)? If you can eliminate one option from a 4-choice question, then your odds are 33%, not 25%.
* The way the results are interpreted (people change their appearance in adulthood in a way that makes them look more like their name) depends entirely on the "we aged up these photos of children using a GAN" experiment, which seems extremely shaky. Also be serious here: do they really think people named Ariel have more lion-y haircuts on average in a way that people subconsciously pick up on? That people named David are gonna look more kingly? Not to shit on their proposed mechanism too much, but get real.
* They preregistered that they were going to look at the differences between men and women, between children and adults, between people who went to religious schools and people who didn't, and between people who knew an example of most of the names used and people who didn't, AND between participants' scores using names they were familiar with vs names they weren't. Lotta comparisons there; I hope they did a Bonferroni correction on the reported p-values.
God I keep coming back to them using photos of twins for the children. Imagine taking this study. You're shown a photo of a kid. Does he look more like a John, Paul, George, or Ringo*? You click John. Two photos later you're shown the same goddamn kid. Does he look more like a Matthew, Mark, Luke or John*? You figure the test is bugged or something, so you click John again. OOPS, actually those two photos were identical twins, so you're guaranteed to have gotten one wrong! Does this affect the results? Who knows?
I find the conclusion unlikely to have the effect size they describe and there are two similar explanations that fit the data better.
Take the name "Maria" in the US. In the 1930's a girl with that name would have strong odds of being from a Catholic background, probably from a large family, maybe Hispanic/Italian/Porto Rican. Then the film the "Sound of Music" came out, and the number girls of being given the name Maria tripled in the 1960's and 1970's. And these new Maria's were born to parents who were trying to evoke a white, blond, energetic, musical Austrian image.
The "stereotypes" associated names change each generation. One big of tell of this, from the linked study, is that adults don't revert to chance on children's names, but are in fact actively worse than chance. In fact, adults are more "worse than chance" on matching children than adults are "better than chance" a matching adult faces.
It's not that adults aren't getting data from looking at children's faces, it's that they are mapping what they are getting to an incorrect mapping!
This initially sounded impossible, but in reality the results are unsurprising and the interpretation is the strange part.
All the children depicted were 9 years old while the adult pictures were presumably from a wider range of age/class cohorts.
It's unsurprising then that participants were able to tell Barbara from Taylor and Brittany from Alexis. (I'm presuming that Ines wasn't present in either sample.)
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[ 3.6 ms ] story [ 28.6 ms ] threadGood example is the musician will.i.am. That is a liberating name for anyone who sees themselves as having an inherent capability to realize their internal, often creative or artistic goals.
I've been told I look like a Kevin (I imagine more like the Minion rather than Costner), who tend to be shit-disturbers for the fun of it. Not my name BTW but I'll take it as a compliment.
No way does this replicate.
* Calling p = 0.062 "marginally significant" (Study 1, child perceivers, adult targets) rings my alarm bells.
* The adult photos used (for studies 1/2/4B) are headshots from an Israeli casting agency. Are there any stage names in use? The child photos are all twins from a twin study the same lab was running. Those seem like, uh, different datasets, with no attempt to control for differences between them. What are the results if you use child actor headshots. What are the results if you use random adult twins. Come on now.
* Any control for real correlations between name and visible features like race or class? The false names in the multiple-choice question were taken at random from the set of names in the dataset. The mean accuracy (for photos of adults) was like 30% - was that more or less even across photos? Or is the average dragged up by a few photos? Imagine an American context: how much of this result is from people correctly identifying the black guy as Darius or Hakeem (or from correctly identifying that the white guy ISN'T Darius or Hakeem)? If you can eliminate one option from a 4-choice question, then your odds are 33%, not 25%.
* The way the results are interpreted (people change their appearance in adulthood in a way that makes them look more like their name) depends entirely on the "we aged up these photos of children using a GAN" experiment, which seems extremely shaky. Also be serious here: do they really think people named Ariel have more lion-y haircuts on average in a way that people subconsciously pick up on? That people named David are gonna look more kingly? Not to shit on their proposed mechanism too much, but get real.
* They preregistered that they were going to look at the differences between men and women, between children and adults, between people who went to religious schools and people who didn't, and between people who knew an example of most of the names used and people who didn't, AND between participants' scores using names they were familiar with vs names they weren't. Lotta comparisons there; I hope they did a Bonferroni correction on the reported p-values.
And there's only 16 adult faces used. If even one of these had a skewed name, that would be a bigger effect size than the entire experiment.
Take the name "Maria" in the US. In the 1930's a girl with that name would have strong odds of being from a Catholic background, probably from a large family, maybe Hispanic/Italian/Porto Rican. Then the film the "Sound of Music" came out, and the number girls of being given the name Maria tripled in the 1960's and 1970's. And these new Maria's were born to parents who were trying to evoke a white, blond, energetic, musical Austrian image.
The "stereotypes" associated names change each generation. One big of tell of this, from the linked study, is that adults don't revert to chance on children's names, but are in fact actively worse than chance. In fact, adults are more "worse than chance" on matching children than adults are "better than chance" a matching adult faces.
It's not that adults aren't getting data from looking at children's faces, it's that they are mapping what they are getting to an incorrect mapping!
All the children depicted were 9 years old while the adult pictures were presumably from a wider range of age/class cohorts.
It's unsurprising then that participants were able to tell Barbara from Taylor and Brittany from Alexis. (I'm presuming that Ines wasn't present in either sample.)