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By Posted on Posted in Race 2 Comments

Political Behavior recently published Filindra et al 2022 "Beyond Performance: Racial Prejudice and Whites' Mistrust of Government". Hypothesis 1 is the expectation that "...racial prejudice (anti-Black stereotypes) is a negative and significant predictor of trust in government".

Filindra et al 2022 limits the analysis to White respondents and measures anti-Black stereotypes by combining responses to available items in which respondents rate Blacks on seven-point scales, ranging from hardworking to lazy, and/or from peaceful to violent, and/or from intelligent to unintelligent. The data include items about how respondents rate Whites on these scales, but Filindra et al 2022 didn't use these responses to measure anti-Black stereotyping.

But information about how respondents rate Whites is useful for measuring anti-Black stereotyping. For example, a respondent who rates all racial groups at the midpoint of a stereotype scale hasn't indicated an anti-Black stereotype; this respondent's rating about Blacks doesn't differ from the respondent's rating about other racial groups, and it's not clear to me why rating Blacks equal to all other racial groups would be a moderate amount of "prejudice" in this case.

But this respondent who rated all racial groups equally on the stereotype scales nonetheless falls halfway along the Filindra et al 2022 measure of "negative Black stereotypes", in the same location as a respondent who rated Blacks at the midpoint of the scale and rated all other racial groups at the most positive end of the scale.

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I think that this flawed measurement means that more analyses need to be conducted to know whether the key Filindra et al 2022 finding is merely due to the flawed measure of racial prejudice. Moreover, I think that more analyses need to be conducted to know whether Filindra et al 2022 overlooked evidence of the effect of prejudice against other racial groups.

Filindra et al 2022 didn't indicate whether their results held when using a measure of anti-Black stereotypes that placed respondents who rated all racial groups equally into a different category than respondents who rated Blacks less positively than all other racial groups and a different category than respondents who rated Blacks more positively than all other racial groups. Filindra et al 2022 didn't even report results when their measure of anti-White stereotypes was included in the regressions estimating the effect of anti-Black stereotypes.

A better review process might have produced a Filindra et al 2022 that resolved questions such as: Is the key Filindra et al 2022 finding merely because respondents who don't trust the government rate *all* groups relatively low on stereotype scales? Is the key finding because anti-Black stereotypes and anti-White stereotypes and anti-Hispanic stereotypes and anti-Asian stereotypes *each* reduce trust in government? Or are anti-Black stereotypes the *only* racial stereotypes that reduce trust in government?

Even if anti-Black stereotypes among Whites is the most important combination of racial prejudice and respondent demographics, other combinations of racial stereotype and respondent demographics are important enough to report on and can help readers better understand racial attitudes and their consequences.

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NOTES

1. Filindra et al 2022 did note that:

Finally, another important consideration is the possibility that other outgroup attitudes or outgroup-related policy preferences may also have an effect on public trust.

That's sort of close to addressing some of the alternate explanations that I suggested, but the Filindra et al 2022 measure for this is a measure about immigration *policy* and not, say, the measures of stereotypes about Hispanics and about Asians that are included in the data.

2. Filindra et al 2022 suggested that:

Future research should focus on the role of attitudes towards immigrants and other racial groups—such as Latinos— and ethnocentrism more broadly in shaping white attitudes toward government.

But it's not clear to me why such analyses aren't included in Filindra et al 2022.

Maybe the expectation is that another publication should report results that include the measures of anti-Hispanic stereotypes and anti-Asian stereotypes in the ANES data. And another publication should report results that include the measures of anti-White stereotypes in the ANES data. And another publication should report results that include or focus on respondents in the ANES data who aren't White. But including all this in Filindra et al 2022 or its supplemental information would be more efficient and could produce a better understanding of political attitudes.

3. Filindra et al 2022 indicated that:

All variables in the models are rescaled on 0–1 scales consistent with the nature of the original variable. This allows us to conceptualize the coefficients as maximum effects and consequently compare the size of coefficients across models.

Scaling all predictors to range from 0 to 1 means that comparison of coefficients likely produces better inferences than if the predictors were on different scales, but differences in 0-to-1 coefficients can also be due to differences in the quality of the measurement of the underlying concept, as discussed in this prior post.

4. Filindra et al 2022 justified not using a differenced stereotype measure, citing evidence such as (from footnote 2):

Factor analysis of the Black and white stereotype items in the ANES confirms that they do not fall on a single dimension.

The reported factor analysis was on ANES 2020 data and included a measure of "lazy" stereotypes about Blacks, a measure of "violent" stereotypes about Blacks, a feeling thermometer about Blacks, a measure of "lazy" stereotypes about Whites, a measure of "violent" stereotypes about Whites, and a feeling thermometer about Whites.[*] But a "differenced" stereotype measure shouldn't be constructed by combining measures like that, as if the measure of "lazy" stereotypes about Blacks is independent of the measure of "lazy" stereotypes about Whites.

A "differenced" stereotype measure could be constructed by, for example, subtracting the "lazy" rating about Whites from the "lazy" rating about Blacks, subtracting the "violent" rating about Whites from the "violent" rating about Blacks, and then summing these two differences. That measure could help address the alternate explanation that the estimated effect for rating Blacks low is because respondents who rate Blacks low also rate all other groups low. That measure could also help address the concern that using only a measure of stereotypes about Blacks underestimates the effect of these stereotypes.

Another potential coding is a categorical measure, coded 1 for rating Blacks lower than Whites on all stereotype measures, 2 for rating Blacks equal to Whites on all stereotype measures, coded 3 for rating Blacks higher than Whites on all stereotype measures, and coded 4 for a residual category. The effect of anti-Black stereotypes could be estimated as the difference net of controls between category 1 and category 2.

Filindra et al 2022 provided justifications other than the factor analysis for not using a differenced stereotype measure, but, even if you agree that stereotype scale ratings about Blacks should not be combined with stereotype scale ratings about Whites, the Filindra et al 2022 arguments don't preclude including their measure of anti-White prejudice as a separate predictor in the analyses.

[*] I'm not sure why the feeling thermometer responses were included in a factor analysis intended to justify not combining stereotype scale responses.

5. I think that labels for the panels of Filindra et al 2022 Figure 1 and the corresponding discussion in the text are backwards: the label for each plot in Figure 1a appears to be "Negative Black Stereotypes", but the Figure 1a label is "Public Trust"; the label for each plot in Figure 1b appears to be "Level of Trust in Govt", but the Figure 1b label is "Anti-Black stereotypes".

My histogram of the Filindra et al 2022 measure of anti-Black stereotypes for the ANES 2020 Time Series Study looks like their 2020 plot in Figure 1a.

6. I'm not sure what the second sentence is supposed to mean, from this part of the Filindra et al 2022 conclusion:

Our results suggest that white Americans' beliefs about the trustworthiness of the federal government have become linked with their racial attitudes. The study shows that even when racial policy preferences are weakly linked to trust in government racial prejudice does not. Analyses of eight surveys...

7. Data source for my analysis: American National Election Studies. 2021. ANES 2020 Time Series Study Full Release [dataset and documentation]. July 19, 2021 version. www.electionstudies.org.

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By Posted on Posted in Race No Comments

The British Journal of Political Science published Jardina and Piston 2021 "The Effects of Dehumanizing Attitudes about Black People on Whites' Voting Decisions".

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1.

Jardina and Piston 2021 used the "Ascent of Man" measure of dehumanization, which I have discussed previously. Jardina and Piston 2021 subtracted participant responses to the 0-to-100 measure of perceptions of how evolved Blacks are from participant responses to the 0-to-100 measure of perceptions of how evolved Whites are, and placed this difference on a 0-to-1 scale.

Jardina and Piston 2021 placed this 0-to-1 measure of dehumanization into an OLS regression with controls, took the resulting coefficient, such as 0.60 in Table 1 (for which the p-value is less than p=0.001), and halved that coefficient, so that, for the 0.60 coefficient, moving from the neutral point on the dehumanization scale to the highest measured dehumanizing about Blacks relative to Whites accounted for 0.30 points on the outcome variable scale, which for this estimate was a 0-to-100 feeling thermometer rating about Donald Trump placed on a 0-to-1 scale.

However, this research design means that 0.30 points on a 0-to-1 scale is also the corresponding estimate of how much dehumanizing about Whites relative to Blacks affected feeling thermometer ratings about Donald Trump. Jardina and Piston 2021 thus did not permit the estimate of the marginal effect of dehumanizing Blacks to differ from the estimate of the marginal effect of dehumanizing Whites.

I discussed this before (1, 2), but it's often better to not assume a linear association for continuous predictors (citation to Hainmueller et al. 2019).

Figure 3 of Jardina and Piston 2021 censors the estimated effect of dehumanizing Whites, by plotting predicted probabilities of a Trump vote among Whites but restricting the range of dehumanization to run from neutral (0.5 on the dehumanization measure) to most dehumanization about Blacks (1.0 on the measure).

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2.

Jardina and Piston 2021 claimed that "Finally, our findings serve as a warning about the nature of Whites' racial attitudes in the contemporary United States" (p. 20). But Jardina and Piston 2021 did not report any evidence that Whites' attitudes in this area differ from non-Whites' attitudes in this area. That seems like a relevant question for researchers interested in understanding racial attitudes.

If I'm reading page 9 correctly, Jardina and Piston 2021 reported on original survey data from a 2016 YouGov two-wave panel of 600 non-Hispanic Whites, a 2016 Qualtrics survey of 500 non-Hispanic Whites, a 2016 GfK survey of 2,000 non-Hispanic Whites, and another 2016 YouGov two-wave panel of 600 non-Hispanic Whites.

The funding statement in Jardina and Piston 2021 acknowledges only Duke University and Boston University. That's a lot of internal resources for surveys conducted in a single year, and I don't think that Jardina and Piston 2021 limiting the analysis to Whites can be reasonably attributed to a lack of resources.

The Qualtrics_BJPS.dta dataset at the Dataverse page for Jardina and Piston 2021 has cases for 1,125 Whites, 242 Blacks, 88 Asians, 45 Native Americans, and 173 coded Other, with respective non-Latino cases of 980, 213, 83, 31, and 38. The Dataverse page doesn't have a codebook for that dataset, and the relevant variable names in that dataset aren't clear to me, but I'll plan to post a follow-up here if I get sufficient information to analyze responses from non-White participants.

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3.

Jardina and Piston 2021 suggested (p. 4) that:

We also suspect that recent trends in the social and natural sciences are legitimizing beliefs about biological differences between racial groups in ways that reinforce a propensity to dehumanize Black people.

This passage did not mention the Jardina and Piston 2015/6 TESS experiment in which participants were assigned to a control condition, or a condition with a reading entitled "Genes May Cause Racial Difference in Heart Disease", or a condition with a reading entitled "Social Conditions May Cause Racial Difference in Heart Disease".

My analysis of data for that experiment found a p<0.01 difference between treatment groups in mean responses to an item about whether there are biological differences between Blacks and Whites, which suggests that the treatment worked. But the treatment didn't produce a detectable effect on key outcomes, according to the description of results on the page for the Jardina and Piston 2015/6 TESS experiment, which indicates that "Experimental conditions are not statistically associated with the distribution of responses to the outcome variables". This null result seems to be relevant for the above quoted suspicion from Jardina and Piston 2021.

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4.

Jardina and Piston 2021 indicated that "Dehumanization has serious consequences. It places the targets of these attitudes outside of moral consideration, ..." (p. 6). But the Jardina and Piston proposal for the 2015/6 TESS experiment had proposed that some participants be exposed to a treatment that Jardina and Piston hypothesized would increase participant "biological racism", to use a term from their proposal.

Selected passages from the proposal are below:

We hypothesize that the proportion of respondents rating whites as more evolved than blacks is highest in the Race as Genetics Condition, lower in the Control Condition, and lowest in the Race as Social Construction Condition.

...Our study will also inform scholarship on news media communication, demonstrating that ostensibly innocuous messages about race, health, and genetics can have pernicious consequences.

Exposing some participants to a treatment that the researchers hypothesized as having "pernicious consequences" seems like an interesting ethical issue that the proposal didn't discuss.

Moreover, like some other research that uses the Ascent of Man measure of dehumanization, the Jardina and Piston 2015/6 TESS experiment included the statement that "People can vary in how human-like they seem". I wonder which people this statement is meant to refer to. Nothing in the debriefing indicated that this statement was deception.

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5.

The dataset for the Jardina and Piston 2015/6 TESS experiment includes comments from participants. I thought that comments from participants with IDs 499 and 769 were worth highlighting (the statements were cut off in the dataset):

I disliked this survey as you should ask the same questions about whites. I was not willing to say blacks were not rational but whites are not rational either. But to avoid thinking I was prejudice I had to give a higher rating. All humans a

Black people are not less evolved, 'less evolved' is a meaningless term as evolution is a constant process and the only difference is what particular adaptations a group has. I don't like to claim certainty about things of which I am unsure, a

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NOTES

1. The Table 3 header for Jardina and Piston 2021 indicates that vote choice is the outcome for that table, but the corresponding note indicates that "Higher values of the dependent variable indicate greater warmth toward Trump on the 101-point feeling thermometer". Moreover, Figure 3 of Jardina and Piston 2021 plots predicted probabilities of a vote for Trump, but the figure note indicates that the figure was "based on Table 4, Model 4", which is instead about warmth toward Obama.

2. Jardina and Piston 2021 reported results for participant responses about the "dehumanizing characteristics" of "savage", "barbaric", and "lacking self-restraint, like animals", so I checked how responses to the "violent" stereotype item associated with two-party presidential vote choice in data from the ANES 2020 Time Series Study.

Results indicated that, compared to White participants who rated Whites as being as violent on average as Blacks, White participants who rated Blacks as being more violent on average than Whites were more likely to vote for Donald Trump net of controls (p<0.05). But result also indicated that, compared to White participants who rated Whites as being as violent on average as Blacks, White participants who rated Whites as being more violent on average than Blacks were less likely to vote for Donald Trump net of controls (p<0.05). See lines 105 through 107 in the output.

3. Jardina and Piston 2021 reported that, in their 2016b YouGov survey, 42% of Whites rated Whites as more evolved than Blacks (pp. 9-10). For a comparison, the Martherus et al. 2019 study about Democrat and Republican dehumanization of outparty members reported dehumanization percentages of "nearly 77%" (2018 SSI study) and "just over 80%" (2018 CCES study).

4. Data sources:

American National Election Studies. 2021. ANES 2020 Time Series Study Preliminary Release: Combined Pre-Election and Post-Election Data [dataset and documentation]. March 24, 2021 version. www.electionstudies.org.

Ashley Jardina and Spencer Piston. 2015/6. Data for: "Explaining the Prevalence of White Biological Racism against Blacks". Time-sharing Experiments for the Social Sciences. https://www.tessexperiments.org/study/pistonBR61

Ashley Jardina and Spencer Piston. 2021. Replication Data for: The Effects of Dehumanizing Attitudes about Black People on Whites' Voting Decisions, https://doi.org/10.7910/DVN/A3XIFC, Harvard Dataverse, V1, UNF:6:nNg371BCnGaWtRyNdu0Lvg== [fileUNF]
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By Posted on Posted in Race No Comments

The recent Mason et al. Monkey Cage post claimed that:

We found about 30 percent of Americans surveyed in 2011 reported feelings of animosity towards African Americans, Hispanics, Muslims, and the LGBTQ community. These individuals make up our MAGA faction.

But much less than 30% of Americans reported animus toward all four of these groups. In unweighted analyses using the 2011 VOTER data, the percentage that rated the group under 50 on a 0-to-100 feeling thermometer was 13% for Blacks, 17% for Latinos, 46% for Muslims, and 26% for gays and lesbians. Only about 3% rated all four groups under 50.

So how did Mason et al. get 30%? Based on the Mason et al. figure note (and my check in Stata), 30% is percentage of average ratings across all four groups that is under 50.

But I don't think that the average across variables should be used to describe responses to individual variables. I think that it would be misleading, for instance, to describe the respondent who rated Blacks at 75 and Muslims at 0 as reporting animosity toward Blacks and Muslims, especially given that the respondent rated Whites at 71 and Christians at 0.

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Mason et al. write that:

Our research does suggest that, as long as this MAGA faction exists, politicians may be tempted to appeal to it, hoping to repeat Trump's success. In fact, using inflammatory and divisive appeals would be a rational campaign strategy, since they can animate independent voters who dislike these groups.

It seems reasonable to be concerned about politicians appealing to intolerant people, but I'm not sure that it's reasonable to limit this concern about intolerance to the MAGA faction.

Below are data from ANES 2020 Time Series Survey, of the percentage of the U.S. population that rated a set of target groups under 50 on a 0-to-100 feeling thermometer, disaggregated by partisanship:

So the coalitions that reported cold ratings about Hispanics, Blacks, gay men and lesbians, Muslims, transgender people, and illegal immigrants are disproportionately Republican (compared to Democratic), and the coalitions that reported cold ratings about rural Americans, Whites, Christians, and Christian fundamentalists are disproportionately Democratic (compared to Republican).

Democrats were more common in the data than Republicans were, so the plot above doesn't permit direct comparison of the blue bars to the red bars to assess relative frequency of cold ratings by party. To permit that assessment, the plot below indicates the percentage of Democrats and the percentage of Republicans that reported a cold rating of the indicated target group:

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Mason et al. end their Monkey Cage post with:

But identifying this MAGA faction as both separate from and related to partisan politics can help us better understand the real conflict. When a small, intolerant faction of citizens wields disproportionate influence over nationwide governance, democracy erodes. Avoiding discussion about this group only protects its power.

But the Mason et al. Monkey Cage post names only one intolerant group -- the MAGA faction -- and avoids naming the group that is intolerant of Whites and Christians, which, by the passage above, presumably protects the power of that other intolerant group.

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NOTES

1. Data citation: American National Election Studies. 2021. ANES 2020 Time Series Study Full Release [dataset and documentation]. July 19, 2021 version. www.electionstudies.org.

2. Link to the Mason et al. 2021 APSR letter.

3. Directions for the 2011 VOTER survey thermometer items directed respondents to "Click on the thermometer to give a rating". If this means that respondents did something like moving a widget instead of inputting a numeric rating, then I think that that might overestimate cold ratings, if some respondents try to rate at 50, instead move to a bit under 50, and then figure that 49 or so is close enough.

But this might not be a large bias: for example, the thermometer about Blacks respectively had 27, 44, 745, 376, and 212 responses for ratings of 48 through 52.

4. Draft plots:

5. Stata code for the analyses, plus: tab pid3_2011 if ft_white_2011==71 & ft_christian_2011==0 & ft_black_2011==75 & ft_muslim_2011==0

6. R data and code for the "three color" barplot.

7. R data and code for the "back-to-back" barplot.

8. R data and code for the "full sample" barplot.

9. R data and code for the "two panel" barplot.

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By Posted on Posted in Evolution 2 Comments

I posted to OSF data, code, and a report for my unpublished "Public perceptions of human evolution as explanations for racial group differences" [sic] project that was from a survey that YouGov ran for me in 2017, using funds from Illinois State University New Faculty Start-up Support and the Illinois State University College of Arts and Sciences. The report describes results from preregistered analyses, but below I'll highlight key results.

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The key item asked participants whether God's design and/or evolution, or neither, helped cause a particular racial difference:

Some racial groups have [...] compared to other racial groups. Select ALL of the reasons below that you think help cause this difference:
□ Differences in how God designed these racial groups
□ Genetic differences that evolved between these racial groups
○ None of the above

Participants were randomly assigned to receive one racial difference in the part of the item marked [...] above. Below are the racial differences asked about, along with the percentage assigned to that item who selected only the "evolved" response option:

70% a greater risk for certain diseases
55% darker skin on average
54% more Olympic-level runners
49% different skull shapes on average
26% higher violent crime rates on average
24% higher math test scores on average
21% lower math test scores on average
18% lower violent crime rates on average

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Another item on the survey (discussed at this post) asked about evolution. The reports that I posted for these items removed all or a lot of the discussion and citation of literature from the manuscripts that I had submitted to journals but were rejected, in case I can use that material for a later manuscript.

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By Posted on Posted in Race No Comments

Social Forces published Wetts and Willer 2018 "Privilege on the Precipice: Perceived Racial Status Threats Lead White Americans to Oppose Welfare Programs", which indicated that:

Descriptive statistics suggest that whites' racial resentment rose beginning in 2008 and continued rising in 2012 (figure 2)...This pattern is consistent with our reasoning that 2008 marked the beginning of a period of increased racial status threat among white Americans that prompted greater resentment of minorities.

Wetts and Willer 2018 had analyzed data from the American National Election Studies, so I was curious about the extent to which the rise in Whites' racial resentment might be due to differences in survey mode, given evidence from the Abrajano and Alvarez 2019 study of ANES data that:

We find that respondents tend to underreport their racial animosity in interview-administered versus online surveys.

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I didn't find a way to reproduce the exact results from Wetts and Willer 2018 Supplementary Table 1 for the rise in Whites' racial resentment, but, like in that table, my analysis controlled for gender, age, education, employment status, marital status, class identification, income, and political ideology.

Using the ANES Time Series Cumulative Data File with weights for the full samples, my analysis detected p<0.05 evidence of a rise in Whites' mean racial resentment from 2008 to 2012, which matches Wetts and Willer 2018; this holds net of controls and without controls. But the p-values were around p=0.22 for the change from 2004 to 2008.

But using weights for the full samples compares respondents in 2004 and in 2008 who were only in the face-to-face mode, with respondents in 2012, some of whom were in the face-to-face mode and some of whom were in the internet mode.

Using weights only for the face-to-face mode, the p-value was not under p=0.25 for the change in Whites' mean racial resentment from 2004 to 2008 or from 2008 to 2012, net of controls and without controls. The point estimates for the 2008-to-2012 change were negative, indicating, if anything, a drop in Whites' mean racial resentment.

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NOTES

1. For what it's worth, the weighted analyses indicated that Whites' mean racial resentment wasn't higher in 2008, 2012, or 2016, relative to 2004, and there was evidence at p<0.05 that Whites' mean racial resentment was lower in 2016 than in 2004.

2. Abrajano and Alvarez 2019 discussing their Table 2 results for feeling thermometers ratings about groups indicated that (p. 263):

It is also worth noting that the magnitude of survey mode effects is greater than those of political ideology and gender, and nearly the same as partisanship.

I was a bit skeptical that the difference in ratings about groups such as Blacks and illegal immigrants would be larger by survey mode than by political ideology, so I checked Table 2.

The feeling thermometer that Abrajano and Alvarez 2019 discussed immediately before the sentence quoted above involved illegal immigrants; that analysis had coefficients of -2.610 for internet survey mode, but coefficients of 6.613 for Liberal, -1.709 for Conservative, 6.405 for Democrat, and -8.247 for Republican. So the liberal/conservative difference is 8.322 and the Democrat/Republican difference is 14.652, compared to the survey mode difference is -2.610.

3. Dataset: American National Election Studies. 2021. ANES Time Series Cumulative Data File [dataset and documentation]. November 18, 2021 version. www.electionstudies.org

4. Data, code, and output for my analysis.

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By Posted on Posted in Evolution No Comments

I posted to OSF data, code, and a report for my unpublished "Public Perceptions of the Potential for Human Evolution" project that was from a survey that YouGov ran for me in 2017, using funds from Illinois State University New Faculty Start-up Support and the Illinois State University College of Arts and Sciences. The report describes results from preregistered analyses, but below I'll highlight key results.

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"Textbook" evolution

About half of participants received an item that asked about what I think might be reasonably described as a textbook description of evolution, in which one group is more reproductively successful than another group. The experimental manipulations involved whether the more successful group had high intelligence or low intelligence and whether the response options mentioned or did not mention "evolved".

Here is the "high intelligence" item, with square brackets indicating the "evolved" manipulation:

If, in the future, over thousands of years, people with high intelligence have more children and grandchildren than people with low intelligence have, which of the following would be most likely to happen?

  • The average intelligence of humans would [increase/evolve to be higher].
  • The average intelligence of humans would [remain the same/not evolve to be higher or lower].
  • The average intelligence of humans would [decrease/evolve to be lower].

Percentages from analyses weighted to reflect U.S. population percentages were 55% for the "increase" option (N=245) and 49% for the "evolve to be higher" option (N=260), with the residual category including other responses and non-responses. So about half of participants selected what I think is the intuitive response.

Here is the "low intelligence" item:

If, in the future, over thousands of years, people with low intelligence have more children and grandchildren than people with high intelligence have, which of the following would be most likely to happen?

  • The average intelligence of humans would [increase/evolve to be higher].
  • The average intelligence of humans would [remain the same/not evolve to be higher or lower].
  • The average intelligence of humans would [decrease/evolve to be lower].

Percentages from analyses weighted to reflect U.S. population percentages were 41% for the "decrease" option (N=244) and 35% for the "evolve to be lower" option (N=244), with the residual category including other responses and non-responses.

So, compared to the "high intelligence" item, participants were less likely (p<0.05) to select what I think is the intuitive response for the "low intelligence" item.

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Evolution due to separation into different environments

Participants not assigned to the aforementioned item received an item about whether the participant would expect differences to arise between groups separated into different environments, but the item did not include an indication of particular differences in the environments. The experimental manipulations were whether the item asked about intelligence or height and whether the response options mentioned or did not mention "evolved".

Here is the intelligence item, with square brackets indicating the "evolved" manipulation:

Imagine two groups of people. Each group has some people with high intelligence and some people with low intelligence, but the two groups have the same average intelligence as each other. If these two groups were separated from each other into different environments for tens of thousands of years and had no contact with any other people, which of the following would be more likely to happen?

  • After tens of thousands of years, the two groups would still have the same average intelligence as each other.
  • After tens of thousands of years, one group would [be/have evolved to be] more intelligent on average than the other group.

Percentages from analyses weighted to reflect U.S. population percentages were 32% for the "be more intelligent" option (N=260) and 29% for the "evolved to be more intelligent" option (N=236), with the residual category including other responses and non-responses.

Here is the height item:

Imagine two groups of people. Each group has some short people and some tall people, but the two groups have the same average height as each other. If these two groups were separated from each other into different environments for tens of thousands of years and had no contact with any other people, which of the following would be more likely to happen?

  • After tens of thousands of years, the two groups would still have the same average height as each other.
  • After tens of thousands of years, one group would [be/have evolved to be] taller on average than the other group.

Percentages from analyses weighted to reflect U.S. population percentages were 32% for the "be taller" option (N=240) and 32% for the "evolved to be taller" option (N=271), with the residual category including other responses and non-responses.

So not much variation in these percentages between the intelligence version of the item and the height version of the item. And only about 1/3 of participants indicated an expectation of intelligence or height differences arising between groups separated from each other into different environments for tens of thousands of years.

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Another item on the survey (eventually discussed at this post) asked about evolution and racial differences. The reports that I posted for these items removed all or a lot of the discussion and citation of literature from the manuscripts that I had submitted to journals but were rejected, in case I can use that material for a later manuscript.

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Criminology recently published Schutten et al 2021 "Are guns the new dog whistle? Gun control, racial resentment, and vote choice".

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I'll focus on experimental results from Schutten et al 2021 Figure 1. Estimates for respondents low in racial resentment indicated a higher probability of voting for a hypothetical candidate:

[1] when the candidate was described as Democrat, compared to when the candidate was described as a Republican,

[2] when the candidate was described as supporting gun control, compared to when the candidate was described as having a policy stance on a different issue, and

[3] when the candidate was described as not being funded by the NRA, compared to when the candidate was described as being funded by the NRA.

Patterns were reversed for respondents high in racial resentment. The relevant 95% confidence intervals did not overlap for five of the six patterns, with the exception being for the NRA funding manipulation among respondents high in racial resentment; eyeballing, it doesn't look like the p-value is under p=0.05 for that estimated difference.

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For the estimate that participants low in racial resentment were less likely to vote for a hypothetical candidate described as being funded by the NRA than for a hypothetical candidate described as not being funded by the NRA, Schutten et al 2021 suggested that this might reflect a backlash against of "the use of gun rights rhetoric to court prejudiced voters" (p. 20). But, presuming that the content of the signal provided by the mention of NRA funding is largely or completely racial, the "backlash" pattern is also consistent with a backlash against support of a constitutional right that many participants low in racial resentment might perceive to be disproportionately used by Whites and/or rural Whites.

Schutten et al 2021 conceptualized participants low in racial resentment as "nonracists" (p. 3) and noted that "recent evidence suggests that those who score low on the racial resentment scale 'favor' Blacks (Agadjanian et al., 2021)" (p. 21), but I don't know why the quotation marks around "favor" are necessary, given that there is good reason to characterize a nontrivial percentage of participants low in racial resentment as biased against Whites: for example, my analysis of data from the ANES 2020 Time Series Study indicated that about 40% to 45% of Whites (and about 40% to 45% of the general population) that fell at least one standard deviation under the mean level of racial resentment rated Whites lower on the 0-to-100 feeling thermometers than they rated Blacks, and Hispanics, and Asians/Asian-Americans. (This is not merely respondents rating Whites on average lower than Blacks, Hispanics, and Asians/Asian-Americans, but is rating Whites lower than each of these three groups).

Schutten et al 2021 indicated that (p. 4):

Importantly, dog whistling is not an attempt to generate racial prejudice among the public but to arouse and harness latent resentments already present in many Americans (Mendelberg, 2001).

Presumably, this dog whistling can activate the racial prejudice against Whites that many participants low in racial resentment have been comfortable expressing on feeling thermometers.

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NOTES

1. Schutten et al 2021 claimed that (p. 8):

If racial resentment is primarily principled conservatism, its effect on support for government spending should not depend on the race of the recipient.

But if racial resentment were, say, 70% principled ideology and 30% racial prejudice, racial resentment should still associate with racial discrimination due to the 30%.

And I think that it's worth considering whether racial resentment should also be described as being influenced by progressive ideology. If principled conservatism can cause participants to oppose special favors for Blacks, presumably a principled progressivism can cause participants to support special favors for Blacks. If so, it seems reasonable to also conceptualize racial resentment as the merging of principled progressivism and prejudice against Whites, given that both could presumably cause support for special favors for Blacks.

2. Schutten et al 2021 claimed that (p. 16):

The main concern about racial resentment is that it is a problematic measure of racial prejudice among conservatives but a suitable measure among nonconservatives (Feldman & Huddy, 2005).

But I think that major concerns about racial resentment are present even among nonconservatives. As I indicated in a prior blog post, I think that the best case against racial resentment has two parts. First, racial resentment captures racial attitudes in a way that is difficult if not impossible to disentangle from nonracial attitudes; that concern remains among nonconservatives, such as the possibility that a nonconservative would oppose special favors for Blacks because of a nonracial opposition to special favors.

Second, many persons at low racial resentment have a bias against Whites, and limiting the sample to nonconservatives if anything makes it more likely that the estimated effect of racial resentment is capturing the effect of bias against Whites.

3. Figure 1 would have provided stronger evidence about p<0.05 differences between estimates if plotting 83.4% confidence intervals.

4. [I deleted this comment because Justin Pickett (co-author on Schutten et al 2021) noted in review of a draft version of this post that this comment suggested an analysis that was reported in Schutten et al 2021, that an analysis be limited to participants low in racial resentment and an analysis be limited to participants high in racial resentment. Thanks to Justin for catching that.]

5. Data source for my analysis: American National Election Studies. 2021. ANES 2020 Time Series Study Preliminary Release: Combined Pre-Election and Post-Election Data [dataset and documentation]. July 19, 2021 version. www.electionstudies.org.

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