Table 2 Regression models to predict the racial diversity-association effect in the co-authorship networks

From: Gender and racial diversity socialization in science

Model

c1

c2

(Intercept)

−0.127***

−5.908***

 

(0.003)

(0.040)

Institutional prestige

0.032***

0.131***

 

(0.001)

(0.014)

Number of early junior co-authors

−0.001***

-0.014***

 

(0.000)

(0.000)

Racial diversity by field

0.181***

0.482***

 

(0.005)

(0.052)

Racial diversity by country

0.880***

5.611***

 

(0.002)

(0.023)

High racial diversity in early co-authors

0.123***

0.651***

 

(0.001)

(0.006)

  1. Under linear regression (model c1), the dependent variable is the crude racial diversity among junior co-authors of individual researchers in the established period. Under logistic regression (model c2), the dependent variable is a binary coding of whether individual researchers in the established period have a high racial diversity among junior co-authors compared with the null model. The key variable is the racial diversity in early co-authors, which uses the raw racial diversity in model c1 and a binary coding relative to the null model in model c2. Two-sided t-tests are used for multiple comparisons. Robust standard errors are given in parentheses. ***P < 0.001.
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