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theevilp0ptart
hmwk_exchange

Statistics 101 Project

“To test our hypotheses, we began with a 20 percent random sample (n = 418) of tenured and tenure-track faculty employed at Research I universities.^ Sampling faculty at Research I universities ensures a conservative test of the hypotheses in two ways. First, the women in the sample have careers that mirror men's more closely than a subset Gendered Academic Careers • 1279 from a broader array of institutions: they did not withdraw before gaining academic employment (Preston 2004; Rosser 2004; Sonnert and Holton 1995) and did not enter less prestigious institutional settings, such as teaching colleges, as women tend to do (Grant and Ward 1991), Second, we are able to account for many resource-based influences on productivity and visibility, such as research funds and assistance, even after statistically controlling for department prestige. Although this sample is limited to scholars whose entire academic histories are available, a series of t-tests suggests that this sub-sample (n = 248) does not differ from the initial sample in terms of gender or the extent of specialization - the two key explanatory variables.^ Focusing this investigation on the disciplines of sociology and linguistics also adds to the stringency of hypothesis tests, for in these disciplines, more than in the natural sciences, women have been incorporated to a greater extent. This is evident in an increasingly equitable gender distribution of recent PhDs over time: in 1973, less than 15 percent of the professionally young (PhD within the past 10 years), full-time, academic labor force in the social and behavioral sciences was women; this increased to 45 percent by 1995. This contrasts with much lower levels of integration in the natural science and engineering, where in 1995, women only constituted 20 percent and 11 percent, respectively (National Research Council 2001). Low levels of gender segregation in sociology and linguistics allow for sub-sample sizes large enough to test for gender differences. While many previous studies of gender inequality in academe have focused on a single discipline (Keith et al. 2002; Long 1992), we examined two disciplines because processes of gender stratification differ across disciplines (Prpic 2002), and the social sciences and the humanities have been neglected by the sociology of science (Guetzkow, Lamont and Mallard 2004). Although the two disciplines also differ in age (sociology is older) and size (sociology is larger), they both sit at the crossroads of several different disciplines and are inherently diverse fields, making an investigation of specialization particularly informative. To collect data on this sample of linguists and sociologists, we relied on various secondary sources, CVs and a web-based survey conducted in Spring 2004. With these data, we constructed measures of four key constructs: gender, the extent of research specialization, productivity and visibility.”

I need help understanding the material above in the quotations. They talk about a 20 percent random sample. However, they do not go into what their sampling frame is other than the following: “1. Research I universities award 50 or more doctoral degrees per year in at least 15 disciplines, and are now referred to as extensive research universities (Carnegie Foundation for the Advancement of Teaching 2001}. To construct our sampling frame, we identified faculty members from university and department websites, disciplinary guides to graduate programs, and professional association membership directories. 2. Although our sub-sample has a larger proportion of sociologists than the initial sample, we do not stress disciplinary differences in this paper.” Should I assume that the sampling frame is all scholars who are on have tenure or are on a tenure track at Research I universities.

Well this is confounded by the subset they discuss. Is the subset a used in the study from the “broader institutions?” Is the sub-sample they discuss having t-tests the same as the subset? Also, it seems they have completely different totals, which is discussed here: “Table 2 describes the sample of scholars during the first 20 years of their careers. Our total sample of individuals at year 1 is 230, which includes142 sociologists and 88 linguists. The gendered age structure in academia is reflected in the fact that women constitute 38 percent of the sample in the first year, but only 20 percent in year 20. On average, specialization tends to increase over time in the sample, specific within the first 10 years, Men, on average, are more specialized than women at the beginning and end of their careers. The average woman has fewer articles (raw and weighted) and citations than the average man, across all time points. Differences, and a growing gap, are especially apparent over time in terms of visibility, while the gap for productivity is relatively small. Figures 1-3 demonstrate this difference over time for men and women, with each line representing predicted publications (raw or weighted) and citations using only time and time as predictors.” Where is this coming from
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