Here are four items typically used to measure symbolic racism, in which respondents are asked to indicate their level of agreement with the statements:

1. Irish, Italians, Jewish and many other minorities overcame prejudice and worked their way up. Blacks should do the same without any special favors.

2. Generations of slavery and discrimination have created conditions that make it difficult for blacks to work their way out of the lower class.

3. Over the past few years, blacks have gotten less than they deserve.

4. It's really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites.

These four items are designed such that an antiblack racist would tend to respond the same way as a non-racist principled conservative. Many researchers realize this conflation problem and make an effort to account for this conflation. For example, here is an excerpt from Rabinowitz, Sears, Sidanius, and Krosnick 2010, explaining how responses to symbolic racism items might be influenced in part by non-racial values:

Adherence to traditional values—without concomitant racial prejudice—could drive Whites' responses to SR [symbolic racism] measures and their opinions on racial policy issues. For example, Whites' devotion to true equality may lead them to oppose what they might view as inherently inequitable policies, such as affirmative action, because it provides advantages for some social groups and not others. Similarly affirmative action may be perceived to violate the traditional principle of judging people on their merits, not their skin color. Consequently, opposition to such policies may result from their perceived violation of widely and closely held principles rather than racism.

However, this nuance is sometimes lost. Here is an excerpt from the Pasek, Krosnick, and Tompson 2012 manuscript that was discussed by the Associated Press shortly before the 2012 presidential election:

Explicit racial attitudes were gauged using questions designed to measure "Symbolic Racism" (Henry & Sears, 2002).

...

The proportion of Americans expressing explicit anti-Black attitudes held steady between 47.6% in 2008 and 47.3% in 2010, and increased slightly and significantly to 50.9% in 2012.

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See here and here for a discussion of the Pasek et al. 2012 manuscript.

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From the abstract of Bucolo and Cohn 2010 (gated, ungated):

'Playing the race card' reduced White juror racial bias as White jurors' ratings of guilt for Black defendants were significantly lower when the defence attorney's statements included racially salient statements. White juror ratings of guilt for White defendants and Black defendants were not significantly different when race was not made salient.

The second sentence reports that white mock juror ratings of guilt were not significantly different for black defendants and white defendants when race was not made salient, but the first sentence claims that "playing the race card" reduced white juror racial bias. But if the data can't support the inference that there is bias without the race card ("not significantly different"), then how can the data support the inference that "playing the race card" reduced bias?

For the answer, let's look at the Results section (p. 298). Guilt ratings were reported on a scale from -5 (definitely not guilty) to +5 (definitely guilty):

A post hoc t test (t(75) = .24, p = .81) revealed that ratings of guilt for a Black defendant (M = 1.10, SD = 2.63) were not significantly different than ratings of guilt for a White defendant (M = .95, SD = 2.92) when race was not made salient. When race was made salient, a post hoc t test (t(72) = 3.57, p =.001) revealed that ratings of guilt were significantly lower for a Black defendant (M = -1.32, SD = 2.91) than a White defendant (M = 1.31, SD = 2.96).

More simply, when race was not made salient, white mock jurors rated the black defendant roughly 5% of a standard deviation more guilty than the white defendant, which is a difference that would often fall within the noise created by sampling error (p=0.81). However, when race was made salient by playing the race card, white mock jurors rated the black defendant roughly 90% of a standard deviation less guilty than the white defendant, which is a difference that would often not fall within the noise created by sampling error (p=0.001).

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Here is how Bucolo and Cohn 2010 was described in a 2013 statement from the Peace Psychology division of the American Psychological Association:

Ignoring race often harms people of color, primarily because biases and stereotypes go unexamined. A study by Donald Bucolo and Ellen Cohn at the University of New Hampshire found that the introduction of race by the defense attorney of a hypothetical Black client reduced the effects of racial bias compared to when race was not mentioned (Bucolo & Cohn, 2010). One error in the state's approach in the George Zimmerman murder trial may have been the decision to ignore issues of race and racism.

But a change from 5% of a standard deviation bias against black defendants to 90% of a standard deviation bias against white defendants is not a reduction in the effects of racial bias.

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Note that the point of this post is not to present Bucolo and Cohn 2010 as representative of racial bias in the criminal justice system. There are many reasons to be skeptical of the generalizability of experimental research on undergraduate students acting as mock jurors at a university with few black students. Rather, the point of the post is to identify another example of selective concern in social science.

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Jeffrey A. Segal and Albert D. Cover developed the Segal-Cover scores that are widely used to proxy the political ideology of Supreme Court nominees. Segal-Cover scores are described here (gated) and here (ungated). The scores are based on the coding of newspaper editorials, with each paragraph in the editorial coded as liberal, conservative, moderate, or not applicable (p. 559).

Segal and Cover helpfully provided examples of passages that would cause a paragraph to be coded as liberal, conservative, or moderate. Here is Segal and Cover's first example of a passage that would cause a paragraph to be coded liberal:

Scarcely more defensible were the numerous questions about Judge Harlan's affiliation with the Atlantic Union. The country would have a sorry judiciary indeed, if appointees were to be barred for belonging to progressive and respectable organizations.

Here is Segal and Cover's first example of a passage that would cause a paragraph to be coded conservative:

Judge Carswell himself admits to some amazement now at what he said in that 1948 speech. He should, for his were the words of pure and simple racism.

I can't think of a better example of conservatism than that.

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Looks like #addmaleauthorgate is winding down. I tried throughout the episode to better understand when, if ever, gender diversity is a good idea. I posted and tweeted and commented because I perceived a tension between (1) the belief that gender diversity produces benefits, and (2) the belief that it was sexist for a peer reviewer to suggest that gender diversity might produce benefits for a particular manuscript on gender bias.

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I posted a few comments at Dynamic Ecology as I was starting to think about #addmaleauthorgate. The commenters there were nice, but I did not get much insight about how to resolve the conflict that I perceived.

I posted my first blog post on the topic, which WT excerpted here in a comment. JJ, Ph.D posted a reply comment here that made me think, but on reflection I thought that the JJ, Ph.D comment was based on an unnecessary assumption. One of the comments at that blog post did lead to my second #addmaleauthorgate blog post.

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I received a comment on my first blog post, from Marta, which specified Marta's view of the sexism in the review:

Suggesting getting male input to fix the bias is sexist - the reviewer implies that the authors would not have come to the same conclusions if a male had read the paper.

That's a perfectly defensible idea, but its generalization has implications, such as it being sexist to suggest that a woman be placed on a team investigating gender bias; after all, the implication in suggesting gender diversity in that case would be that an all-male team is unable to draft a report on gender bias without help from a woman.

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The most dramatic interaction occurred on Twitter. After that, I figured that it was a good time to stop asking questions. However, I subsequently received two additional substantive responses. First, Zuleyka Zevallos posted a comment at Michael Eisen's blog that began:

Gender diversity is a term that has a specific meaning in gender studies – it comes out of intersectional feminist writing that demonstrates how cis-gender men, especially White men, are given special privileges by society and that the views, experiences and interests of women and minorities should be better represented.

Later that day, Karen James tweeted:

...diversity & inclusion are about including traditionally oppressed or marginalized groups. Men are not one of those groups.

Both comments refer to the asymmetry-in-treatment explanation that I referred to in note 4 of my first #addmaleauthorgate post. That is certainly a way to reconcile the two beliefs that I mentioned at the top of this post.

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Some more housekeeping. My comments here and here and here did not get very far in terms of attracting responses that disagreed with me. I followed up on a tweet characterizing the "whole review" by asking for the whole review to be made public, but that went nowhere; it seems suboptimal that there is so much commentary about a peer review that has been selectively excerpted.

A writer for Science Insider wrote an article indicating that Science Insider had access to the whole review. I asked for the writer to post the whole review, but the writer tweeted that I should contact the authors for this particular newsworthy item. I don't think that is how journalism is supposed to work.

I replied to a post on the topic in Facebook and might have posted comments elsewhere online. I make no claim about the exhaustiveness of the above links. The links aren't chronological, either.

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One more larger point. It seems that much of the negative commentary on this peer review mischaracterizes the peer review. This mischaracterization is another method by which to make it easier to dismiss thoughtful consideration of ideas that one does not want to consider.

Here is a description of the peer review:

...that someone would think it was OK to submit a formal review of a paper that said "get a male co-author"

Very strange use of quotes in that case, given that the quoted passage did not appear in the public part of the review. Notice also the generalization to "paper" instead of "paper on gender bias" and the more forceful description of "get" as opposed to "It would probably also be beneficial."

Here is more coverage of the peer review:

A scientific journal sparked a Twitter firestorm when it rejected two female scientists' work partly because the paper they submitted did not have male co-authors.

If there is any evidence that the same manuscript would not have been rejected or would have had a lesser chance of being rejected if the manuscript had male co-authors, please let me know.

One more example, from a radio station:

This week the dishonour was given to academic journal PLos One for rejecting a paper written by two female researchers on the basis that they needed to add a male co-author to legitimize their work.

I would be interested in understanding which part of the review could be characterized with the word "needed" and "legitimize." Yes, it would be terribly sexist if the reviewer wrote that the female researchers "needed to add a male co-author to legitimize their work"; however, that did not happen.

that someone would think it was OK to submit a formal review of a paper that said “get a male co-author” - See more at: http://www.michaeleisen.org/blog/?p=1700#sthash.o0RkigoR.dpuf
that someone would think it was OK to submit a formal review of a paper that said “get a male co-author” - See more at: http://www.michaeleisen.org/blog/?p=1700#sthash.o0RkigoR.dpuf
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My previous post on #AddMaleAuthorGate did not focus on the part of the peer review that discussed possible sex differences. However, that part of the peer review has since been characterized as harassment, so I thought that a closer look would be of value. I have placed the relevant part of the public part of the peer review below.

"...perhaps it is not so surprising that on average male doctoral students co-author one more paper than female doctoral students, just as, on average, male doctoral students can probably run a mile race a bit faster than female doctoral students.
... ...
As unappealing as this may be to consider, another possible explanation would be that on average the first-authored papers of men are published in better journals than those of women, either because of bias at the journal or because the papers are indeed of a better quality, on average ... And it might well be that on average men publish in better journals ... perhaps simply because men, perhaps, on average work more hours per week than women, due to marginally better health and stamina."

Below, I'll gloss the passage, with notes that characterize as charitably as possible what the reviewer might have been thinking when writing the passage. Here goes:

"...perhaps it is not so surprising that on average male doctoral students co-author one more paper than female doctoral students,..." = This finding from the manuscript might not be surprising.

"...just as, on average, male doctoral students can probably run a mile race a bit faster than female doctoral students." = There might be an explanation for the finding that reflects something other than bias against women. Let me use an obvious example to illustrate this: men and women are typically segregated by sex in track races, and this might not be due to bias against women. Of course, I believe that there is overlap in the distribution of running speed, so I will toss in an "on average" and a "probably" to signal that I am not one of those sexists who think that men are better than women in running a mile race on average. I'll even use the caveat "a bit faster" to soften the proposed suggestion.

"... ..." = I wrote something here, but this passage was redacted before my review was posted on Twitter. That double ellipsis is unusual.

"As unappealing as this may be to consider..." = I know that this next part of the review might come across as politically incorrect. I'm just trying to signal that this is only something to consider.

"...another possible explanation would be that..." = I'm just proposing this as a possibility.

"...on average..." = I understand the overlap in the distribution.

"...the first-authored papers of men are published in better journals than those of women..." = I understand this finding from the manuscript.

"...either because of bias at the journal..." = That finding might actually be due to journals being biased against women. I realize this possibility, and I am not excluding it as an explanation. I even mentioned this hypothesis first, so that no one will think that I am discounting the manuscript's preferred explanation.

"...or because the papers are indeed of a better quality, on average..." = This is the most reasonable alternate explanation that I can think of. I am NOT saying that every paper by a man is necessarily of a better quality, so I'll mention the "on average" part again because I understand that there is overlap in the distribution. However, if we measure the quality of papers by men and the quality of papers by women and then compare the two measures, it might be possible that the difference in means between the two measures is not 0.00. I hope that no one forgot that this sentence began with a set of caveats about how this is a possible explanation that might be unappealing.

"..." = I wrote something else here, but this passage was also redacted before my review was posted on Twitter.

"And it might well be that on average men publish in better journals..." = Just restating a finding from the manuscript. I remembered the "on average" caveat. That's my fifth  "on average" so far in this short passage, by the way. I hope that my I'm-not-a-sexist signals are working.

"..." = I wrote something else here, too, but this passage was also redacted before my review was posted on Twitter; this ellipsis is mid-sentence, which is a bit suspicious.

"..perhaps simply because men, perhaps.." = This is just a possibility. I used the word "perhaps" twice, so that no one misses the "perhaps"s that I used to signal that this is just a possibility.

"...on average work more hours per week than women..." = This is what it means when the male-female wage gap is smaller when we switch from weekly pay to hourly pay, right?

"...due to marginally better health and stamina." = I remember reading a meta-analysis that found that men score higher than women on tests of cardiovascular endurance; I'm pretty sure that's a plausible proxy for stamina. I hope that no one interprets "health" as life expectancy or risk of a heart attack because the fact that men die on average sooner than women or might be more likely to have a heart attack is probably not much of a factor in the publishing of academic articles by early-career researchers.

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In my voice again. Some caveats of my own:

I am not making the claim that the review or the reviewer is not sexist or that the reviewer would have made the equivalent review if the researchers were all men. The purpose of this exercise was to try to gloss as charitably as possible the part of the review that discussed sex differences. If you do not think that we should interpret the review as charitably as possible, I would be interested in an explanation why.

The purpose of this exercise was not to diminish the bias that women face in academia and elsewhere. This post makes no claim that it is inappropriate for the female researchers in this episode -- or anyone else -- to interpret the review as reflecting the type of sexism that has occurred and has continued to occur.

Rather, the purpose of this exercise was to propose the possibility that our interpretation of the review reflects some assumptions about the reviewer and that our interpretation is informed by our experiences, which might color the review in a certain way for some people and in a certain way for other people. These assumptions are not necessarily invalid and might accurately reflect reality; but I wanted to call attention to their status as assumptions.

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Vox has a post about racial bias and police shootings. The story by Vox writer Jenée Desmond-Harris included quotes from Joshua Correll, who investigated racial bias in police shootings with a shooter game, in his co-authored 2007 study, "Across the Thin Blue Line: Police Officers and Racial Bias in the Decision to Shoot" (gated, ungated).

Desmond-Harris emphasized the Correll et al. 2007 finding about decision time:

When Correll performed his experiment specifically on law enforcement officers, he found that expert training significantly reduced their fatal mistakes overall, but no matter what training they had, most participants were quicker to shoot at a black target.

For readers who only skim the Vox story, this next sentence appears in larger blue font:

No matter what training they had, most participants were quicker to shoot at a black target.

That finding, about the speed of the response, is fairly characterized as racial bias. But maybe you're wondering whether the law enforcement officers in the study were more likely to incorrectly shoot the black targets than the white targets. That's sort of important, right? Well, Desmond-Harris does not tell you that. But you can open the link to the Correll et al. 2007 study and turn to page 1020, where you will find this passage:

For officers (and, temporarily, for trained undergraduates), however, the stereotypic interference ended with reaction times. The bias evident in their latencies did not translate to the decisions they ultimately made.

I wonder why the Vox writer did not mention that research finding.

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I doubt that the aggregate level of racial bias in the decision of police officers to shoot is exactly zero, and it is certainly possible that other research has found or will find such a nonzero bias. Let me know if you are aware of any such studies.

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There has recently been much commentary on the peer review received by female researchers regarding their manuscript about gender bias in academic biology (see here, here, and here). The resulting Twitter hashtag #addmaleauthorgate indicates the basis for the charge of sexism. Here is the relevant part of the peer review:

It would probably also be beneficial to find one or two male biologists to work with (or at least obtain internal peer review from, but better yet as active co-authors), in order to serve as a possible check against interpretations that may sometimes be drifting too far away from empirical evidence into ideologically based assumptions.

I am interested in an explanation of what was sexist about this suggestion. At a certain level of abstraction, the peer reviewer suggested that a manuscript on gender bias written solely by authors of one sex might be improved by having authors of another sex read or contribute to the manuscript in order to provide a different perspective.

The part of the peer review that is public did not suggest that the female authors consult male authors to improve the manuscript's writing or to improve the manuscript's statistics; the part of the peer review that is public did not suggest consultation with male authors on a manuscript that had nothing to do with sex. It would be sexist to suggest that persons of one sex consult persons of another sex to help with statistics or to help interpret results from a chemical reaction. But that did not happen here: the suggestion was only that members of one sex consult members of the other sex in the particular context of helping to improve the *interpretation of data* in a manuscript *about gender bias.*

Consider this hypothetical. The main professional organization in biology decides to conduct research and draft a statement on gender bias in biology. The team selected to perform this task includes only men. The peer reviewer from this episode suggests that including women on the team would help "serve as a possible check against interpretations that may sometimes be drifting too far away from empirical evidence into ideologically based assumptions." Is that sexism, too? If not, why not? If so, then when ‒ if ever ‒ is it not sexist to suggest that gender diversity might be beneficial?

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Six notes:

1. I am not endorsing the peer review. I think that the peer review should have instead suggested having someone read the manuscript who would be expected to provide help thinking of and addressing alternate explanations; there is no reason to expect a man to necessarily provide such assistance.

2. The peer review mentioned particular sex differences as possible alternate explanations for the data. Maybe suggesting those alternate explanations reflects sexism, but I think that hypotheses should be characterized in terms such as substantiated or unsubstantiated instead of in terms such as sexist or inappropriate.

3. It is possible that the peer reviewer would not have suggested in an equivalent case that male authors consult female authors; that would be fairly characterized as sexism, but there is, as far as I know, no evidence of the result of this counterfactual; moreover, what the peer reviewer would have done in an equivalent case concerns only the sexism of the peer reviewer and not the sexism of the peer review.

4. I have no doubt that women in academia face bias in certain situations, and I can appreciate why this episode might be interpreted as additional evidence of gender bias. If the argument is that there is an asymmetry that makes it inappropriate to think about this episode in general terms, I can understand that position. But I would appreciate guidance about the nature and extent of this asymmetry.

5. Maybe writing a manuscript is an intimate endeavor, such that suggesting new coauthors is offensive in a way that suggesting new coauthors for a study by a professional organization is not. But that's an awfully nuanced position that would have been better articulated in an #addauthorgate hashtag.

6. Maybe the problem is that gender diversity works only or best in a large group. But that seems backwards, given that the expectation would be that a lone female student would have more of a positive influence in a class of 50 male students than in a class of 2 male students.

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UPDATE (May 4, 2015)

Good response here by JJ, Ph.D to my hypothetical.

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