I was under the impression that this was pretty much common knowledge, but sure, I can point you in the right direction.
One interesting place to start is Harvard's "Project Implicit". They have a massive publication list[1] and you can even test your own implicit reactions[2].
There are plenty of other scientists testing things like whether people judge women as less competent. A quick google search pulled up a PNAS paper where they did an experiment on women in science, for example.[3]
This is just the tip of the iceberg, of course. There is a whole host of related work, testing other sorts of biases and using other methodologies. I'd suggest a search on your favorite academic search engine for "implicit bias".
I'm a programmer, not a psychologist. I have, however, some slight familiarity with IATs as a purported measure of unconscious bias; they have never impressed me as being particularly reliable as such, given what seems to be their questionable repeatability, not to mention the ease with which they are manipulated, and the way most of the results so obtained tend to hover just outside the margin of error. I won't even talk about the tendentious nature of the investigations themselves, because experience suggests there's no point in so doing.
You disappoint me, sir. I had such hopes of finding something new and interesting, only to discover that your mere vagueness led me astray.
So even if we arbitrarily exclude a perfectly valid psychological technique because it "doesn't impress you", there's still the matter of my third link. Didja click it?
EDIT: The most surprising part of the PNAS study, to me, is that people who agreed with statements like "Discrimination against women is no longer a problem in the United States" were statistically more affected by implicit gender bias.
I fail to see how questioning the validity of the technique constitutes "goal-post movement". I requested citations and you supplied them, which I appreciate. I fail to see how said exchange requires that I respond "oh, hey, there sure are a lot of papers, you must be right!"
On the other hand, I must concede that I previously failed to look closely enough on first inspection at your third link. In my opinion, it does a great deal more to substantiate your statement than the IAT stuff does. I'd like to see similar studies with much higher n, but it's hard to argue with the analysis.
You asked for a citation. That's the original position of the goal post. When you were provided with multiple citations, you decided that wasn't good enough, and so started complaining about the veracity of studies in general and finished by ignoring those citations and claiming "vagueness." That's the second position of the goal post. Those two positions are different. Therefor, the goal post has moved.
Your response was filled with bitterness, like someone who was flustered at having been proved wrong. It sounded just like a child crossing their arms and yelling, "Well citations are stupid anyway!"
One interesting place to start is Harvard's "Project Implicit". They have a massive publication list[1] and you can even test your own implicit reactions[2].
There are plenty of other scientists testing things like whether people judge women as less competent. A quick google search pulled up a PNAS paper where they did an experiment on women in science, for example.[3]
This is just the tip of the iceberg, of course. There is a whole host of related work, testing other sorts of biases and using other methodologies. I'd suggest a search on your favorite academic search engine for "implicit bias".
[1] https://www.projectimplicit.net/papers.html [2] https://implicit.harvard.edu/implicit/ [3] http://www.pnas.org/content/early/2012/09/14/1211286109#aff-...