2x2 contingency table, $d$ statistic? I am reading The Fluctuating Female Vote: Politics, Religion, and the Ovulatory Cycle. (It shows up in several of Gelman's papers as an example of how not to do statistics.) Among the reported findings are a number of what seem to be chi-squared tests for independence using a 2x2 contingency table, for example:

Women in relationships, however, were more likely to vote for Romney
at if they were in the high- fertility group (M = 40.4%) than if they
were in the low-fertility group (23.4%), $\chi^2(1, N = 134) = 4.44$, $p = .035$, $d = 0.37$.

I am curious about the last statistic, $d=0.37$. What is $d$ here, and how is it calculated?

The paper is available here. (I don't know if the authors have permission to post it.) ResearchGate link
Here's my conjecture about that d statistic:
Other places in the paper they report the d statistic when comparing two groups by F-test or t-test.
One possibility is that the statistic reported for the chi-square test is really a phi statistic, but it got changed to "d" during copyediting.
Another possibility is that they used some formula to convert phi to d so that the effect sizes would be on a uniform scale. (FYI: there's some discussion on that conversion here: CrossValidated link ).
