Of Boys and Men is a new book about how the outcomes of American men and boys are lagging in several ways. Most of it concerns aggregate trends that are irrefutable, such as the gender gap in college graduation. But books like these are often useful for testable hypotheses rather than reliable facts. Case in point: Reeves makes the odd claim that "men are hard to help":
[A] startling number of social programs seem to work well for girls and women, but not for boys and men — among which are a student-mentoring scheme in Fort Worth, Texas; a school-choice program in Charlotte, North Carolina; an income boost to low-wage earners in New York City; and many more.
The failure of these programs to help boys and men is a big problem, given that in many cases they are the ones who need the most help. But the problem rarely receives any attention, not least because almost nobody knows about it. (source)
I was startled when I read this because it seemed like such a textbook example of cherry-picking. Of the many studies out there we should probably have priors that the effects are about even on average. Reeves cites around eight individual evaluations that found larger benefits for females compared to males, but he never points to any attempt at aggregation.
The cited studies cover four broad areas:
- Free college tuition with other supports (Kalamazoo Promise and Stay the Course at Tarrant County College in Forth Worth, Texas)
- Pre-school programs (a study of the Abecedarian, Perry, and the early Training Project and one of Project READS in North Carolina)
- Mentoring programs and boarding schools (just mentions that they are in New Hampshire, Baltimore, and Washington, D.C.)
- Wage subsidies (the Paycheck Plus pilot)
These all find the effect difference that Reeves claims to have discovered. The problem is that “men are harder to help” doesn’t seem to be true in general. For each of the four areas, I looked for meta-analyses or similar studies that estimated gender differences in the treatment effects:
- Free college tuition: a rigorous trial of the Susan Thompson Buffett Foundation, which gives large grants to Nebraska high schoolers planning to attend public colleges in the state, finds if anything larger impacts on men compared to women. A meta-analysis discussing this question finds a mix favoring men, women, or neither and concludes that there's not enough evidence to say.
- Pre-school programs: there was already a meta-analysis of this looking at all trials of early childhood interventions. There’s no clear advantage for girls. Papers citing the meta-analysis also show a tilt towards bigger effects for boys.
- Mentoring programs: a meta-analysis of 70 studies finds larger effects for those with a higher proportion of men. A smaller meta-analysis focused on disruptive behavior problems finds the same.
- Wage subsidies: Here he is perhaps right. Evaluations targeted at women tended to have larger effects in the most recent meta-analysis I could find, but by a small margin.
This isn't meant to be an exhaustive evaluation of the question, but men do not seem to be harder to help and the evidence presented by Reeves is underwhelming. It’s a little disappointing that this easily checkable claim made it into the book.
Seems the evidence considered here doesn't stack up, but I have a hunch that there's something real to the idea that men are harder to help than women.
My experience managing and leading men and women in the workplace is that, when offered the same sort of help, women are, on average, more receptive of help than men. I can't recall a female employee outright rejecting training or coaching on how to get better at something we both agree they need to get better at, but I have seen male employees do this. (n~=50 over my career, approximately 10 women and 40 men)
My theory is that men, more so than women, are resistive to help that may seem to lower their status. Men are willing to accept help if they think the person offering it is clearly higher status than them because then it raises their status by association, but they reject it otherwise. I'm sure women exhibit this behavior too, but for as often as I've seen it in men I would have expected to see this happen with at least 1 female employee.
Of course I'm also the constant here in my data, so maybe there's something about me that makes the difference here.