I agree: no more family killing. Even one family dead is too many.
However, the paper you posted dealt with hypothetical candidates only. I am guessing that actual data of recent hires would not paint such a rosy picture for women, even in the non-STEM fields in this study and especially if math, physics, chemistry and computer science were included.
I already responded to the invalidity of your "not real" argument. You have zero theoretical basis to predict that the result would magically reverse just because the very real seeming applications were not real. Faculty regularly evaluate other faculties credentials for things other the hiring, including giving feedback to each other on areas of weakness, etc. There is nothing really out of the ordinary about their evaluation of these. In addition, and as I already pointed out multiple times and as the article points out, other research on actual hires shows that women are more likely to get the academic jobs they bother to apply for after controlling for any significant difference in their objective qualifications (number of pubs, grants, etc.). IOW, your baseless assumption on which you conveniently dismiss all this data has been shown empirically false.
Except for actual hiring stats, of course.
I see, so the problem is basic scientific illiteracy. You blindly accept that hiring statistics which are shown to be confounded in countless ways with other factors can be directly interpreted in terms of the effect of gender bias, even though research shows that statistical controls on those confounds eliminate any reliable hiring differences . Your ignorance-based conclusion that you believe with certainty, then makes you think that any findings to the contrary of your conclusion must be invalid because it conflicts with your conclusion you already illogically and unscientifcally drew from meaningless confounded data. That isn't an argument supporting your presumption of the new research's invalidity, it is an ideological dismissal based solely on whether the findings cohere with your prior conclusion that was based on evidence of far poorer quality than what you are now dismissing. IOW, if you were a peer-reviewer of this paper and you made that argument, the editor would dismiss you from the panel for incompetence. The reason this paper was published in one of the most impactful journals (second most read in the world), which is peer-reviewed by panels of leaders in the field and members of the National Academy of Sciences who reject 83% of all submissions is that these reviewers understand that your basis for dismissing the evidence as irrelevant is bogus and invalid.
Oh yeah, and I bet you don't even have hiring stats at all. You just presume they conform to your a priori belief. Show me actual stats, which means what % of males and females who actually apply for a STEM faculty position get the position they apply for? Presuming their actually is any numerical difference in hiring rates (again, rates mean condition on applying), then you can start to think about the countless factors that are confounded with gender which do and by all reasonable minds should heavily determine hiring.
Or the inclusion of non STEM fields
The topic is about STEM hiring because that is where almost all focus is regarding under-representation of females and that is where claimed gender stereotypes are strongest. Are you seriously going to pretend that it is plausible that English, Anthro, Gender-studies, Ethnic-studies (now about 10 different departments),and sociology are less friendly and in favor of female faculty than Engineering and Economics?
and the very pointed exclusion of actual STEM fields from your study.
Wow. So the fields included were neither STEM nor non-STEM? You should get a Nobel Prize because you just discovered something that is logically impossible.
Violating the most foundational principle of all logic and rational thought. IF that isn't clear evidence of blind faith and unwillingness to reason, then nothing is.
I'm neither blind nor am I scientifically illiterate.
Your arguments that violate the most basic principles of scientific reasoning show otherwise. You claim the results are not meaningful because of the methods.
No, I didn't.
All of your comments have been rooted in your "not the real world" assertion which you continue to repeat below. That is an assertion about methods, but then not even knowing what "methods" refers to is part of scientific illiteracy.
Then when I asked you to give a specific argument as to how the methods would impact psychological mechanism in a manner that would produce fundamentally different if not opposite results from what would be produced when essentially the same task was performed in reference to an actual hiring process.
You provided nothing except a claim that the results of the study are in conflict with what you presume to be true based upon "hiring stats".That is fallacious circular reasoning
No. What I am suggesting is that actual hiring practices at universities demonstrate discrimination or lack of discrimination that actually occurs more accurately than this one study reflects actual hiring.
And why would they be "more accurate", except due to methodological issues? Results are not more valid because you agree with them. Methodology is the only thing that determines the validity and implications of results. And again, you fail to provide any hiring stats or address any of the numerous confounds in them that make them far less valid an indicator of anything that impacts hiring. And you fail to account for the cited research showing that when hiring stats are properly analyzed to account for differences in applying and objective quantified differences in academic records, they show the same result as this controlled experiment, namely bias in favor of females.
in which your are claiming that the results are invalid because the methods are invalid, and you know the methods are invalid because the results are invalid.
Not my argument.
Exactly your argument, and you continue to make it. You just admitted above that your rejection of the OP results as inaccurrate is not do to problems with its methods. That leaves no possibility but that you are rejecting the results because you do not agree with the results. You claim those results don't agree with the hiring stats, yet provide no evidence of this and refuse to acknowledge the provided evidence against that claim which shows that scientific analysis of those stats is consistent with the OP study and fails to support an anti-female bias in academic hiring.
Methodological validity is completely independent of the findings. If the methods are invalid, then they must be so even if the results were exactly what you believe to be true.
I agree
And yet you provide zero argument as to how the methods would produce opposite results from what you believe on faith is accurate, fail to acknowledge the fatal methodological flaws in simply looking at raw numbers of females and males hired in the "real world", and fail to acknowledge the research that uses unquestionably superior methods and shows results opposite of what you claim.
For you to argue as you have but then claim "I agree", is like a fundamentalist saying "The Bible is the infallible word of God. Oh, and I agree that beliefs should be based on evidence."
In addition, your use of "hiring stats" as evidence for what you believe to be true shows you have no concept of confounds and how the prohibit the causal inference you are drawing from uncontrolled correlational data. You are making all of the same kind of invalid assumptions of perfect equality between male and female applicants that I enumerated for KeepTalking.
You are making a very good case against your argument here.
More evidence of scientific illiteracy. You don't even know what a confound is or the difference between an experiment and correlational data. The OP study is controlled experiment without any confounds. It is not correlational data but shows direct causal impact of the inclusion of gender pronouns in the applications materials on hiring rankings. Hiring stats are correlational and have numerous confounds, the most major being who actually applied for the job. That is why those numbers are meaningless without statistical analyses that at least control for all of the most obvious and objective quantifiable factors. Any flaws with the OP study are in external/ecological validity which has nothing to do with confounds or inferring causal relations among the measured variables. They have to do with whether the sample and the studied behaviors map onto the people and the behaviors of broader theoretical interests. And "its not identical to the 'real world'" is not a rational or scientific critique, and yet it is the entire extent of your critique. The sample includes and is highly representative of the actual people who make the hiring decisions in the studies disciplines, moreso than virtually ever other experimental study claiming to show hiring biases against females or other under-represented sub-groups. The materials the decision makers were given and their task was highly similar to what is the case in actual hiring scenarios, and the differences that exist, if anything, would be theoretically more likely to decrease pro-female gender bias than inflate it, meaning that the causal impact in the "real world" would be more likely to be larger than smaller, with no basis (and you've provided none) to think that the results would be opposite.
Moreover, you seem to conflate the results of a perfectly controlled study with actual real world statistics involving actual people
.
Every one of the 800 academic faculty in the study are not only "actual people" but are among the very people who make the actual hiring decisions in their departments. The application materials were indistinguishable from "real world" materials.
And you seem to be ignorant of the different ways that real people evaluate real vs theoretical CVs and applications
Again, they were all real people and the same people who evaluate real CVs. There are not parts of the human brain that process "real" CVs in one way and fake CVs in another. It would take extra effort for a person to use a fundamentally different approach to CV evaluation just because it is not for an actual current position. All relevant psychological theory says they would take the same basic approach. The only notable difference is that their rankings and decisions would be more public in the "real world" and they would have to defend them to a highly pro Affirmative Action administration.
and how easily these are parsed into meeting whatever criteria is being sought. Or not meeting those criteria.
Not sure what this vague claim actually refers to, and I doubt you do either since you've actively avoided any specific explanation of how and why the differences from the "real world" would produce opposite results.
The major "criteria" sought in "real" hiring at most Universities is Affirmative Action, and there is very real social and political pressure put on faculty to hire in accord with it and never say anything that would imply one does not agree with it. In contrast, faculty in this study were less pressured by this, and the research was cleverly designed to mask the fact that applicants' gender as what was being studied, and they conducted post study interviews and showed that almost none of the participants suspected that gender-bias was being studied. IOW, the differences from the "real world" reduced the pressure on faculty to favor female applicants merely for their gender, meaning the 2:1 bias is likely lower than what occurs in the "real world".
It is your "hiring stats" that are meaningless invalid data in relation to gender bias in hiring preferences, because unlike my linked study they are full of countless confounds that severe any connection with the causal influence of gender.
You sound like a lot of grad students during the first week they are in grad school: bemoaning the fact that theoretical data does not match reality. Most grow out of that conceit.
They are not theoretical data. They are the actual data which in contrast to your faith are the best indicator of reality. You have zero data or reality that supports your faith. You only have a grotesquely unscientific abuse of meaningless raw numbers that you misrepresent as something they are objectively not. You don't sound like a grad student because no one as ignorant of basic scientific and statistical issues would get into grad school (at least not without affirmative action).
And as I predicted, you do not even have hiring stats, just faith that they support your presumption. Again, raw number of men and women hired are scientifically meaningless numbers, because baserate values (number of applicants of each gender) are a minimal requirement to make any comparison informative.
No, I'm just not in the mood to do your research for you.
You're not in the mood to do any rational thinking for yourself. The research is already done. I linked it for you, and shows your are completely wrong and that hiring stats show evidence of pro-female bias.
Unlike you and some others participating in this thread, I have actually read the paper linked in the OP. I understand what it claims and also the difference between the attitudes expressed by respondents in this study and actual staffing of positions at universities.
The "respondents" in the study were all actually faculty who are the ones that do the hiring,
Not at any university I'm familiar with. Faculty may make recommendations but administration, not faculty, makes the decision to hire or not hire.
Absolute nonsense. No one in administration ever even sees 99% of that applications. The actual faculty in the department are the only ones that actually look at the applicant pool and their decisions determine the 2-5 person short list, which are the only ones anyone in administration would ever look at, even usually not even that. The search committee is typically 100% faculty and they put the short list into their order of preference, and it is rare for the administration to override it. The only cases of that I have encountered is when the #1 candidate is a white male and the admin pushes for someone else.
In fact, if there are no minorities on the short list, admin sometimes forces the faculty to go back through all the applications to make sure there isn't one that they might have "missed".
IN sum, any minor and rather uncommon influence administration has is even more pro Affirmative Action and pro-female than the faculty. They tend to be the biggest ideologues on the issue which is what drove them into the politics of administration. They are directly beholden to the AA mission statements. They don't actually have to work with less competent faculty, so they care more about being able to talk about the numbers of minority faculty that have and how fair and progressive their University is.
In the "real world" the top applicants get ranked ordered by individual faculty, plus rated on whether they are "hireable" meaning above a minimum standard. IOW, just like in this study. The rankings are then statistically pooled to determine the top ranked candidates favored by the search committee and the host department. There is extreme explicit and implicit pressure to put forth under-represented candidates. Many Universities have policies that require written rationalizations any time a short list does not include any under-represented people but never if the list doesn't include "over-represented" people.
So, the faculty in the study you linked behaved as they normally would: they responded to pressures that were not related to the candidates themselves but to external pressures to hire under represented candidates.
No. There is nothing that would have made them behave in a manner that was the exact opposite of the "real world", as your dismissal of the data presumes.
The main notable difference between the study and the "real world" is they lack of external pressure to be even more biased in favor of hiring female faculty than they might already be themselves. After all, it is the personal biases of the majority of faculty that create the cultural atmosphere that exerts the external pressure. IOW, qualitatively, their behavior is representative, it just might be less extreme than actual hiring biases, meaning the 2:1 bias is an under-estimate.
People regurlar make arguments for hiring a person because they are female or minority, but any arguments give "because they are white or male" for hiring are reported to the Dean and the person comes under serious heat.
Why would there be any such pressure to hire women or minority faculty?
Because all relevant data shows that academics skew massively to the political left, which means they would get informal pressure from most colleagues, plus formal pressure in the form of explicit AA policies that are not just unobserved platitudes in University settings.
If anything, the "not real" aspect of the study would have reduced female bias among faculty who don't agree with the dominant and enforced affirmative action political climate on all University campuses. That would reduce the bias relative to what happens in real searches where one's choices are more public and under scrutiny. Like I said, "its different than reality" is not a valid methodological critique.
Seems like you are agreeing with me: reality is different than the theoretical.
No. Actual valid data is reality, you have zero of it favoring your faith based delusions. Reality is the thing you are blindly denying. The realities in a controlled experiment (which all still occur in the real world with real people engaged in actual behavior) can differ in ways from the target context of interest. But that is not a valid critique. The differences must be of the sort that would plausibly reverse the results from what they would be in the target context, and you must specify how that would happen. You have specified nothing. Every single experiment differs in ways from the "real world". Thus, you must dismiss 100% of science, if you are going to dismiss this study on such vacuous grounds. I have specified the differences and pointed out how they would make the pro-female bias in the study less extreme than the real world. That doesn't invalidate the study. It means that it gives us a lower bound estimate of how strong the pro-female bias is.
You must specify exactly how the differences outweigh the similarity in a precise way that would make the results completely different or reverse than what was observed.
No, I don't.
No, you can be irrational, faith based, and completely unwilling to present any argument or evidence that supports your anti-science position. You can do that and that is all you have done.
I also understand the difference between a STEM field and a non-STEM field, both at a university and in the real world. And also how to read.
You apparently don't understand the logical fact that a field cannot fail to qualify as both a STEM field and a non-STEM field,]
which is what you claimed is true of Economics, Engineering, Biology, and Psychology. They must be one or the other (hint: Engineering is the "E" in STEM, Biology is part of the "S", Psychology is a mixed bag, and Economics is non-STEM though is male dominated and tends to skew politically conservative compared to other academic disciplines.
DING DING DING!!!! We have a winner.
Oh boy!! Are you going to admit the logical absurdity of your claim that these fields are both non-STEM and not non-STEM??? Oh no, your going to pretend you never said that despite the undeniable empirical proof.
Economics is not typically listed as a STEM field although I would argue that it is more mathematically dependent than psychology nor is psychology considered to be a STEM field, yet both are included in this paper purporting to demonstrate the lack of bias against female candidates in hiring for tenure track faculty in STEM fields. Half of the fields surveyed were not STEM. My point was that only two STEM fields were included in this study, along with two non-STEM fields, while several STEM fields were ignored, those being mathematics, chemistry, physics and computer science.
Why were not faculty in those excluded departments included in this study? Why the extra effort to include non-stem fields?
If you actually read and were able to minimally comprehend the article or just understand basic realities of scientific research, you would know the answer to that and wouldn't baseless presume it is some devious plot on the researcher's part to bias their findings. They explain several times that they want to include STEM and non-STEM, because some non-STEM (Psychology) has been studied for hiring bias but 20 years ago, while no controlled study of STEM has been done. They also wanted disciplines that varied in their mathematical intensity and in their gender disparities among current faculty. They wanted to test whether gender bias in hiring was related to these factors that differ between the disciplines, namely math-focus, being typical STEM, and current level of gender disparity in faculty. What they showed is that the answer is "No, gender bias is pro-female among disciplines that vary in these ways and is not systematically related to these dimensions". This is counter to the non-evidence based faith that there is a particularly strong anti-female bias in math-heavy STEM fields that is responsible for their current low female representation. No, not every single STEM field was included, because in "the real world" where actual research is conducted (as opposed to your fictitious imaginary world), research takes lots of time and money. So they selected disciplines that vary highly on the described dimensions and thus cover the various ways in which disciplines differ that have been claimed to be related to gender biases against women.
Do you have a specific mechanism by which you claim the Physics is so different from Engineering and Biology and on dimensions other than math, being part of STEM, or current % of female faculty? Because only such a difference provides any reasonable basis to think it would show opposing results from these disciplines. I am betting no, because like your entire argument you have no legit intellectual or empirical basis for your objections, just trumped up post-hoc excuses that you'd never make if the results happened to support your faith.
