These are serious suggestions for having a productive discussion or debate with a feminist. The goal isn’t to embarrass or “own” them, but to increase the chance that they (and others watching) will consider your points and change their mind.
These survey studies are an attempt to better understand how men are seen and treated in our society. While not equivalent to peer-reviewed academic studies, they do provide some hard data that I hope will inspire thought, discussion, and further interest in these topics.
(Length: 1,400 words.)
Heterosexual dating typically involves men initiating contact (approaching and asking for a number in real life, or sending the first message on a dating site) and taking on a greater share of planning, proposing, and even paying for dates. Given this dating dynamic, I am interested in whether people perceive dating as being primarily about men proving themselves to women, like how job interviews are typically seen as more about the applicant proving themselves to the employer than vice versa. I am also interested in whether people perceive men as having less “value” in relationships than women.
In the survey study reported below, respondents were nine times more likely to say that dating was about men proving themselves than to say it was about women proving themselves (one third of respondents did not indicate any difference). When asked about relationship value, half did not indicate a difference between men and women; however, those who did were more likely to rate men lower in value, to the effect that the average man’s value was rated as 6.3 out of 10, compared to 7.3 for the average woman.
Kim Cambell’s personal website describes her as Canada’s first and only female prime minister, but in a Status of Women Canada profile she’s instead Canada’s first woman prime minister. Theresa May referred to herself as the UK’s second female prime minister, but in the Telegraph she’s the country’s second “woman PM”. And a Los Angeles Timesarticle about Elizabeth Warren asks whether Americans are ready for a female president in the page text but a woman president in the page’s title bar.
Feminism has a special preoccupation with women’s physical safety. “Violence against women” is a key topic in feminist discourse, frequently discussed with a tone of unique seriousness, urgency, and outrage that portrays it as something separate from, and worse than, “regular violence” (i.e., against men). What is interesting, but hardly ever remarked on, is that this special concern for violence against women actually looks a lot like the protective attitudes towards women commonly found in traditional gender roles. Feminists and traditionalists obviously differ in some of the details but both sides have rhetoric that sends similar messages when it comes to violence and safety.
The outrage over and public inquiry into “missing and murdered Indigenous women” (MMIW) is a major story from Canada that deserves wider attention. It demonstrates attitudes or even policies of male disposability (less concern for the safety and well-being of men than of women) from a government that vocally champions gender equality.
In March of 2019, some women working at the provincial legislature in British Columbia were issued warnings that their sleeveless shirts did not meet the institution’s standards of business attire. This incident evoked controversy that largely portrayed the policy or its enforcement as a gendered attack on women, even though the sleeve requirement applied to both genders. Dress code requirements that applied only to men, like the need to wear a tie, received no such controversy or interpretation as a gender issue.
I want to bring attention to this incident and the response it received as an example of problems with the modern discourse on gender issues. It seems that none of the people who portrayed the dress code incident as a gendered attack on women gave any thought or concern to the men’s side of the issue, and the fact that they have to follow the same or more restrictive dress code requirements.
This is an informal survey-based study of desire for police and media to take a policy of not including race or gender in their description of the suspect of a crime. Two-hundred-and-one Americans, balanced for gender (50:50 men and women) and party affiliation (50:50 Republican and Democrat, used as a proxy for the broader “Red Tribe” and “Blue Tribe” cultures in the United States that differ in politics, religion, gender roles, geography, urbanization, etc.), indicated their approval level (on a 1–7 scale) of one of the two following policy statements:
When a crime is committed, police and media should avoid mentioning race in their description of the suspect or wanted person, to avoid fueling stereotypes about race and crime.
When a crime is committed, police and media should avoid mentioning gender in their description of the suspect or wanted person, to avoid fueling stereotypes about gender and crime.
Results indicate a greater approval rating for the first policy (of not mentioning race) than the second policy (of not mentioning gender).
Note that I do not ask this with the assumption that either the policy of mentioning less or more about the suspect is the right one. Regardless of my or your overall leanings here, I want to raise the question of whether race and gender should be treated differently.
2. Main findings
The average approval rating when asked about gender was 2.5 out of 7, compared to 3.5 out of 7 for race (SDs = 2.0 and 2.4). This is a difference of 1 point, or about half a standard deviation (Cohen’s d = 0.45), and is statistically significant (see section 3).
Democrats had overall higher approval responses across both questions (average of 3.6/7) than Republicans (2.3). There was additionally a trend in the data towards Democrats having a larger disparity between their responses for race and gender, but this was not statistically significant (meaning that this is something that might be worth looking into more in the future, but at this point no concrete conclusions should be drawn).
3. Additional details
The 201 respondents were the same as in the previous survey study comparing attitudes on charging men more for car insurance with attitudes on charging women more for health insurance. Respondents were assigned to the question about race or gender based on identifying whether the last digit in their day of birth was an even number or an odd number, which divided them approximately in half. Respondents also provided their ages, which are reported in the other study. Republicans were a bit older than Democrats.
Statistical analysis was done using a linear regression (lm in R). The response variable was the 1–7 rating of acceptability; the predictor variables were question (i.e., which question was asked: #1 about race or #1 about gender), gender of the respondent (man, woman), and party affiliation of the respondent (Republican or Democrat). The ANOVA table is provided below. The most relevant result is the significant main effect of group (people had higher approval ratings for a policy of not mentioning race than a policy of not mentioning gender).
This is an informal survey-based study on people’s views of gender-based pricing in insurance. Two-hundred-and-one Americans, balanced for gender (men and women) and party affiliation (Republican and Democrat, although my interest isn’t party politics itself so much as the broader “Red Tribe” and “Blue Tribe” cultures in the United States that differ in politics, religion, gender roles, geography, urbanization, etc.), indicated their approval level (on a 1–7 scale) of one of the two following policy statements:
Insurance companies should be allowed to charge women more for health insurance, if they find that women on average access health services more often.
Insurance companies should be allowed to charge men more for car insurance, if they find that men on average get in car accidents more often.
Results indicate greater approval for charging men more for car insurance than for charging women more for health insurance. Respondent gender and party affiliation were relevant—women exhibited a larger difference than men in approval ratings, and the “Blue Tribe” (Democrats) had a larger difference than the “Red Tribe” (Republicans).
Some might question whether car insurance and health insurance are comparable. I think they are comparable, although there are obviously some differences. Health insurance is more essential, although car insurance is not far behind in the notoriously car-dependent United States (77% of Americans drive to work, not counting carpools). Health insurance is also more expensive to buy, but more likely to be provided by someone else (a majority of Americans have coverage through their employer, Medicare, or Medicaid). I don’t see these details giving an obvious justification for why gender pricing would be acceptable in one type of insurance and not the other, but that’s an open possibility.
2. Main findings
The overall average approval rating for gender-based pricing in insurance was 3.3 out of 7 (SD = 2.1). The average for charging men more for car insurance was 3.8, compared to 2.8 for charging women more for health insurance. This is a difference of 1 point or about half a standard deviation (Cohen’s d = 0.49), and is statistically significant (see section 3).
Both gender and party of respondent had a significant effect on the difference in ratings between scenarios. Men exhibited a smaller difference in their approval ratings than women did, and Republicans exhibited a smaller difference than Democrats. As a result of the effects of party and gender, Democrat women exhibit numerically the largest disparity (2.5 points) and Republican men the smallest (0.3 points in the other direction), with Democrat men (1.2) and Republican women (1.1) in the middle.
3. Additional details
The 201 participants were recruited from an online research platform and paid a small sum to complete the survey, which took under a minute (and included one other policy question). Respondents were assigned to the question about health insurance or car insurance based on identifying whether the last digit in their day of birth was an even number or an odd number, which divided them approximately in half.
Table 1: Question answered, by gender and party affiliation
Answered question on men & car insurance
Answered question on women & health insurance
Having participants answer one question, but not both, has the advantage that seeing one question doesn’t influence their answer to the second question, but the disadvantage of lower statistical power. Respondents also provided their ages, which I’ve summarized below. Republicans were a bit older than Democrats.
Table 2: Age of sample, by gender and party affiliation
Statistical analysis was done using a linear regression (lm in R). The response variable was the 1–7 rating of acceptability; the predictor variables were scenario (men on car insurance, women on health insurance), gender of the respondent (man, woman), and party affiliation of the respondent (Republican or Democrat).
The ANOVA table of the output is provided below. The most relevant results are the significant main effect of scenario (charging men more for car insurance was rated as more acceptable than charging women more for health insurance) and the significant scenario:gender and scenario:party interactions (both party and gender affect the disparity in ratings, as explained above). The non-significant scenario:gender:party interaction is also relevant; it means that the disparity exhibited by each party + gender combination is predicted by the separate effects of party and gender. In other words, the scenario ratings difference of Democrat women is largely predicted by the separate effects of “Democrat” and “woman” rather than something special about Democrat women (and similarly for Republican women, Republican men, and Democrat men).
This survey-based study finds evidence that feminist women (and non-feminist men, to a lesser extent) view women more favorably than men, and that women view mothers more favorably than fathers (with no effect of feminism). See the discussion and conclusion below for interpretations and implications of these findings.
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.