This is original data, written up in the general style of a scientific paper (albeit somewhat more informally). It should be readable regardless of background, although for a summary you can skip to the discussion or conclusion. I encourage comments, criticism, and suggestions, especially (but not only) from people with backgrounds in research.

Note: Since posting, this page has undergone nontrivial revisions. See § 7 for details.

Sections:

(Length: 2,500 words.)

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1. Introduction

Imagine if our society were half as indignant about the police engaging in gender profiling as it is about their racial profiling! – Roy Baumeister (author of Is There Anything Good About Men?)

I’ve previously suggested that there is a double standard in society, particularly on the social justice left, that holds it to be acceptable to fear or profile men as violent but unacceptable to do the same to ethnic or religious minorities. To show this I contrasted articles and statements that condemn fearing minorities with ones that advocate and justify a fear of men (§ 1.2 of “Social Justice’s Punching Bags”).

The examples were compelling but I want to gather some quantitative data on attitudes towards profiling to see specifically how widespread and overlapping these attitudes are. To do this I will conduct an online survey-based study measuring people’s attitudes towards profiling under various conditions. I will be testing three hypotheses:

Hypothesis 1 : Profiling will be considered more acceptable for men than minorities.

: Profiling will be considered more acceptable for men than minorities. Hypothesis 2 : The disparity will be larger on the political left than the political right.

: The disparity will be larger on the political left than the political right. Hypothesis 3: The disparity will be diminished when people have to think about both types of profiling at once, compared to thinking about each one in isolation.

I am not aware of any existing research or polling on attitudes towards gender profiling. For a summary of the work on profiling minorities, see Johnson et al. (2011). As they explain, profiling for crime prevention is generally seen quite negatively (Bill Clinton called it a “morally indefensible, deeply corrosive practice”). Many polls in the months and years following 9/11 found relatively high support for profiling in terrorism prevention, although Johnson et al.’s own survey-based study did not find a context difference; both were seen very negatively. Their study found, consistent with past research, that whites, men, and conservatives show higher levels of support for profiling.

Johnson et al. (2011): “Attitudes Toward the Use of Racial/Ethnic Profiling to Prevent Crime and Terrorism” (2011, Criminal Justice Policy Review).

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2. Methodology

2.1 Participants

Seventy-six Americans were recruited from an online research platform and paid a small sum to complete the survey, which took approximately three minutes. The only demographic information collected was gender (46 men, 26 women, and 4 other), age (mean = 28.6, sd = 8.8, range = 18–65), and political identification (44 left-leaning, 18 centrists, and 14 right-leaning; this was originally measured on a 7-point scale but collapsed afterwards to three options due to the lack of numbers on the right).

2.2 Materials

Eight survey questions were created to test willingness to demographically profile. The first four scenarios covered institutional profiling (airport security, bouncers/doormen at nightclubs, refugee acceptance decisions, and police on street patrol), while the final four scenarios covered profiling in people’s personal safety precautions (walking home at night, in a parking lot or parking garage, answering the door while home alone, and giving directions to someone in a car). Two versions of the survey were made: one to specify profiling men in those scenarios, and one to specify profiling minorities.

The eight questions are below, with {curly brackets} indicating the content that varies by version. All questions started with “Is it acceptable or unacceptable for”.

… airport security to target {men over women, people from the Middle East} for extra scrutiny? … bouncers (doormen) at nightclubs to give less attention to searching {women than men, white people than black people}? … countries accepting refugees from the Middle East to prioritize {women over men, Christians over Muslims}? … police on street patrol to keep a closer eye on {men than women, black people than white people}? … a {woman, white person} walking home at night to speed up or cross the street due to the presence of a {man, black person} walking behind {her, them}? … a {woman, white person} in a parking lot or parking garage at night to hear someone else and feel safe only after seeing that they’re {a woman, white}? … a {woman, white person} who’s home alone to refuse to open her door after seeing that the person who knocked is {a man, black}? … a {woman, white person} walking alone on a street, who sees a car slow down to ask directions, to approach and give directions only after seeing that the driver is {a woman, white}?

These scenarios were picked for their plausibility with both gender and ethnic/religious profiling. Most ended up involving profiling of black people. I suspect they’re the minority most profiled in the same contexts as men, although a follow-up study would benefit from looking at profiling of a wider and more balanced range of minority groups.

2.3 Procedure

Participants first gave their age and gender. They then completed both versions of the survey one after the other, with half seeing the version about men first and the other half seeing the version about minorities first (making this a within-subjects design). Within each survey, participants were presented with the eight questions in random order. They were asked to rate each profiling scenario on a 7-point rating scale, from unacceptable (1) to acceptable (7). Background was given at the top of each survey to ensure that the rationale for and against the profiling was clear:

Statistically speaking, {men, some minority groups} are disproportionately likely to engage in many types of violence, including terrorism and street crime. Some argue that safety precautions can be optimized by taking these statistics into account, while others argue that this is discriminatory and unfair to individuals. What are your thoughts on the following scenarios?

After completing both versions of the survey, participants indicated their political views using a 7-point scale (1 is left and 7 is right) in response to the following question:

Where would you place your political beliefs on a spectrum from left-wing (liberal or Democratic Party) to right-wing (conservative or Republican Party)?

2.4 Data analysis

Hypothesis 1 (profiling men will be rated as more acceptable), Hypothesis 2 (the disparity will be larger on the political left), and Hypothesis 3 (the disparity will diminish when people have to think about both types of profiling at once) will be tested using a linear mixed effects model (lme4/lmerTest in R) on the rating scale data. The model will have three fixed effects: target (men, minorities), political leanings (left, centre, right), and order (first, second). For the purposes of Hypothesis 3, participants’ responses to their first survey (on men or minorities) will be understood as their views on that type of profiling in isolation; their responses to the second survey (men after seeing minorities, or vice versa) will be understood as their views on that type of profiling when having to think about both types of profiling at once. (In other words, Hypothesis 3 predicts that the disparity between the men and minorities surveys that are viewed second will be smaller than the disparity between the surveys that are viewed first.) In addition to these fixed effects, the two random effects are participant (n = 76) and scenario (n = 8). To simplify the results section, the detailed model summary is in the appendix.

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3. Results

3.1 Statistical analyses

Profiling of men was rated significantly more acceptable than profiling of minorities: 4.13 compared to 2.62 (out of 7) (see target in the appendix analysis summary). The greater willingness to profile men is evident in the counts of each response below.

Figure 1

To show individual variation, I’ve plotted below the difference between each person’s willingness to profile minorities and their willingness to profile men. Negative values indicate a greater willingness to profile men than minorities.

Figure 2

Political identification had a significant effect on overall ratings (pol in the appendix), with right-leaning indicating the overall highest acceptability for profiling. Politics also had a statistically significant interaction with target (target:pol in the appendix)—right-leaning people targeted men the least (applied profiling most equally).

Table 1. Acceptability by target and political affiliation of participant

Left (n = 44) Centre (n = 18) Right (n = 14) Minorities 2.18 2.53 4.12 Men 3.92 4.09 4.83 Disparity 1.74 1.56 0.71 Overall 3.05 3.31 4.48

To show presentation order effects, I’ve split the ratings for each survey when it was viewed first from when it was viewed second. When the surveys were viewed second, the profiling targeted men less disproportionately than when the surveys were viewed first (target:order in the analysis summary).

Table 2. Acceptability by target and order

First (n = 38) Second (n = 38) All (n = 76) Minorities 2.37 2.88 2.62 Men 4.77 3.49 4.13 Disparity 2.40 0.61 1.51

3.2 Other data

The gender of the participant was not a part of the hypotheses, although for completeness I have provided the responses split by gender below.

Table 3. Acceptability by target and gender of participant

Men (n = 46) Women (n = 26) Other (n = 4) Minorities 2.91 2.20 2.06 Men 4.20 3.94 4.59 Disparity 1.29 1.74 2.53

Similarly, here are the responses split by each scenario. They are medians rather than means because they each comprise one rating scale item, rather than an aggregate.

Table 4. Acceptability by target and scenario

Airport Bouncer Refugees Police Walking Parking Home Directions Minorities 2 1 1 2 3 2 3 2 Men 2 3 3 4 6 5 6 5

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4. Discussion

4.1 Hypotheses

Given the results, let’s evaluate the three hypotheses.

Hypothesis 1: Profiling will be considered more acceptable for men than minorities.

Participants rated profiling of men as significantly more acceptable than profiling of minorities, which supports Hypothesis 1. However, six of the eight scenarios involved one particular minority (black people), and so we should be cautious about drawing conclusions about willingness to profile minorities in general from this. A follow-up study could compare profiling of men to profiling of a wider range of minorities (such as Latinos and Native Americans) that in the U.S. are plausibly profiled in similar situations as men.

Another concern is social desirability bias; perhaps these these results are driven not just by individual views but also by social taboos on profiling minorities. This happens less in an anonymous online survey than a personal interaction, but it is still possible. I am not sure what the implications of this are. On one hand, it would also be interesting to find a disparity in perceived social pressure. On the other hand, we would still want to distinguish that from a disparity in actual views, which is difficult because views and social pressures are so intertwined. People’s views contribute to social pressures, and pressures influence not just reporting but also actual views. I don’t have a solution.

Hypothesis 2: The disparity will be larger on the political left than the political right.

In addition to being overall more supportive of profiling, right-leaning people did indeed apply their profiling more equally, which supports Hypothesis 2.

Hypothesis 3: The disparity will be diminished when people have to think about both types of profiling at once, compared to thinking about each one in isolation.

Half of the participants saw the survey on men first and the survey on minorities second, while the other half saw the opposite order. We can thus compare what people think about each type of profiling in isolation (surveys viewed first) with what people think about each type of profiling when considered alongside the other type (surveys viewed second). The acceptability gap between profiling of men and profiling of minorities was smaller in the surveys viewed second than the surveys viewed first, which supports Hypothesis 3.

The strength of this effect actually suggests that the within-subjects design (where each participant saw both surveys) produced a misleading result that underestimates the disparity in attitudes towards profiling men and minorities in real life. It is interesting to find that support for profiling of men decreases when people are forced to think about profiling of minorities, but mentioning minority profiling beforehand is not a neutral way to get opinions on profiling of men.

In other words, imagine that you are polling for opinions on car emissions standards. It would be interesting to learn that support is higher when people have just seen a question on urban pollution. But if you want the best measure of public opinion on car emissions, you won’t average together results from people who saw the question in isolation and people who saw it after the question on urban pollution. You’ll just look at when the question was asked in isolation. For the present results, perhaps the most accurate picture is not the entire data-set but rather just the surveys shown first. If so, we would replace Figure 1 above with Figure 3 below and see an even bigger disparity in attitudes towards profiling men and minorities (disparity on 7-point scale of 2.40 instead of 1.51).

Figure 3

4.2 Limitations

Compared to the U.S. population, this sample skewed young, male, and politically left-leaning. This should be taken into account when interpreting the overall results. Also, as mentioned, self-reported attitudes can be affected by desirability bias.

4.3 Future research

The most obvious follow-up study, given the design and results here, would compare profiling of men to profiling of a wider range of minorities, and get a larger sample of right-leaning people to clarify right–left differences. Other avenues for future study include investigating the effect of wording (e.g., asking about “gender profiling” and “racial profiling” in the abstract), the effect of the identity of the person doing the profiling (how do people’s thoughts on women profiling men compare to their thoughts on men profiling other men?), and the effect of type of scenario (both institutional and personal profiling were included here, but not part of the hypotheses or analysis). It would also be interesting to confirm the main result in countries other than the United States.

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5. Conclusion

This survey-based study found evidence for the United States that profiling men is considered more acceptable than profiling minority groups in the same scenarios, but that the disparity in attitudes is significantly reduced when people are made to think about both types of profiling at once. This suggests, at least for people who oppose profiling on principle, that there is a blind-spot in our society’s opposition to profiling, but a blind-spot that could be reduced by pointing out the double standard and referencing profiling of minorities. The results also suggest that people on the political right target men less disproportionately than those on the left, although they are more supportive of profiling overall.

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6. Appendix

Here is the ANOVA table of the mixed effects model. The three fixed effects were target (minorities, men), politics (left, centre, right), and order (first, second).

Type III Analysis of Variance Table with Satterthwaite's method Sum Sq Mean Sq NumDF DenDF F value Pr(>F) target 384.55 384.55 1 1127 183.3885 < 2.2e-16 *** pol 43.93 21.96 2 70 10.4738 0.0001049 *** order 11.47 11.47 1 1127 5.4685 0.0195363 * target:pol 45.62 22.81 2 1127 10.8781 2.093e-05 *** target:order 26.12 26.12 1 70 12.4583 0.0007403 *** pol:order 17.67 8.84 2 1127 4.2134 0.0150296 * target:pol:order 0.06 0.03 2 70 0.0136 0.9865383 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

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7. Revisions

In the interests of transparency, I am documenting (in reverse chronological order) any nontrivial changes that I made to this page since it was first posted.

The initial mixed effects analysis mistakenly provided simple effects (rather than main effects) due to defaults in R and the use of summary() . I have switched to summarizing the mixed effects model with anova() , which provides main effects as desired. This has changed the evaluation of one hypothesis.