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1643 andrew gelman stats-2012-12-29-Sexism in science (as elsewhere)


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Introduction: Solomon Hsiang sends along this from Corinne Moss-Racusin, John Dovidio, Victoria Brescoll, Mark Graham, and Jo Handelsman: Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. . . . In a randomized double-blind study . . . science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. . . . I hate to talk about things like this since presumably I’m a beneficiary. But now that I’ve climbed the ladder myself I suppose I’m not at any risk. I don’t know anything much about lab manager positions—that’s more something you’d see in a biology department—but I do


Summary: the most important sentenses genereted by tfidf model

sentIndex sentText sentNum sentScore

1 Solomon Hsiang sends along this from Corinne Moss-Racusin, John Dovidio, Victoria Brescoll, Mark Graham, and Jo Handelsman: Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. [sent-1, score-0.978]

2 science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. [sent-8, score-1.872]

3 Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. [sent-9, score-1.367]

4 These participants also selected a higher starting salary and offered more career mentoring to the male applicant. [sent-10, score-1.024]

5 I hate to talk about things like this since presumably I’m a beneficiary. [sent-14, score-0.176]

6 But now that I’ve climbed the ladder myself I suppose I’m not at any risk. [sent-15, score-0.422]

7 I don’t know anything much about lab manager positions—that’s more something you’d see in a biology department—but I do know that I’ve hired more men than women as postdocs. [sent-16, score-0.8]

8 If I were forced to hire in equal numbers it would be annoying but I suppose I could do it. [sent-17, score-0.535]


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tfidf for this blog:

wordName wordTfidf (topN-words)

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Introduction: Solomon Hsiang sends along this from Corinne Moss-Racusin, John Dovidio, Victoria Brescoll, Mark Graham, and Jo Handelsman: Despite efforts to recruit and retain more women, a stark gender disparity persists within academic science. . . . In a randomized double-blind study . . . science faculty from research-intensive universities rated the application materials of a student—who was randomly assigned either a male or female name—for a laboratory manager position. Faculty participants rated the male applicant as significantly more competent and hireable than the (identical) female applicant. These participants also selected a higher starting salary and offered more career mentoring to the male applicant. . . . I hate to talk about things like this since presumably I’m a beneficiary. But now that I’ve climbed the ladder myself I suppose I’m not at any risk. I don’t know anything much about lab manager positions—that’s more something you’d see in a biology department—but I do

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Introduction: Lee Seachrest points to an article , “Life expectancy and disparity: an international comparison of life table data,” by James Vaupel, Zhen Zhang, and Alyson van Raalte. This paper has killer graphs. Here are their results: In 89 of the 170 years from 1840 to 2009, the country with the highest male life expectancy also had the lowest male life disparity. This was true in 86 years for female life expectancy and disparity. In all years, the top several life expectancy leaders were also the top life disparity leaders. Although only 38% of deaths were premature, fully 84% of the increase in life expectancy resulted from averting premature deaths. The reduction in life disparity resulted from reductions in early-life disparity, that is, disparity caused by premature deaths; late-life disparity levels remained roughly constant. The authors also note: Reducing early-life disparities helps people plan their less-uncertain lifetimes. A higher likelihood of surviving to old age

3 0.13108103 571 andrew gelman stats-2011-02-13-A departmental wiki page?

Introduction: I was recently struggling with the Columbia University philophy department’s webpage (to see who might be interested in this stuff ). The faculty webpage was horrible: it’s just a list of names and links with no information on research interests. So I did some searching on the web and found a wonderful wikipedia page which had exactly what I wanted. Then I checked my own department’s page , and it’s even worse than what they have in philosophy! (We also have this page, which is even worse in that it omits many of our faculty and has a bunch of ridiculously technical links for some of the faculty who are included.) I don’t know about the philosophy department, but the statistics department’s webpage is an overengineered mess, designed from the outset to look pretty rather than to be easily updated. Maybe we could replace it entirely with a wiki? In the meantime, if anybody feels like setting up a wikipedia entry for the research of Columbia’s statistics faculty, that

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Introduction: Blogger Echidne pointed me to a recent article , “The Distance Between Mars and Venus: Measuring Global Sex Differences in Personality,” by Marco Del Giudice, Tom Booth, and Paul Irwing, who find: Sex differences in personality are believed to be comparatively small. However, research in this area has suffered from significant methodological limitations. We advance a set of guidelines for overcoming those limitations: (a) measure personality with a higher resolution than that afforded by the Big Five; (b) estimate sex differences on latent factors; and (c) assess global sex differences with multivariate effect sizes. . . . We found a global effect size D = 2.71, corresponding to an overlap of only 10% between the male and female distributions. Even excluding the factor showing the largest univariate ES [effect size], the global effect size was D = 1.71 (24% overlap). Echidne quotes a news article in which one of the study’s authors going overboard: “Psychologically, men a

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