Inequality of opportunity in selection procedures limits diversity in higher education: An intersectional study of Dutch selective higher education programs

Table 2. Demographic data recorded for each applicant and their parents. Variable Values Rationale Appplicant data Sex 0 = Male The known male:female ratio differences in some fields of study [45] 1 = Femalea Year of birth Recoded in 3 categories to create groups of sufficient size for logistic regression analysis: The known higher performance of older students (>21 years), compared to younger students, in Dutch medical education [46]. 0 = 1999 or earlier 1 = 2000–2001 2 = 2002 or later Migration background Statistics Netherlands original values are based on country of birth of the person, or the country of birth of parents. Each country has its own value, which we recoded in 5 categories for the descriptive statistics: Earlier research showed the inequality of opportunity in selection to Dutch university health professions education programs for applicants with a Turkish, Moroccan, Surinamese and Dutch Caribbean migration background [13]. In this research, applicants with an Indonesian migration background constituted a group of similar size, with a similar (post-)colonial migration history as Surinamese and Dutch Caribbean migrants. 0 = No migration background 1 = Turkish/Moroccan migration background 2 = Surinamese/Dutch Caribbean/Indonesian migration background 3 = EU/EEA/Swiss (European) migration background 4 = Other migration background. These were recoded in 3 categories for the regression analyses: 0 = No migration background 1 = Turkish/Moroccan/Surinamese/Dutch Caribbean/ Indonesian (TMSDI) migration background 2 = Other migration background (OMB) migration

background Country of birth 0 = Born in The Netherlands 1 = Born abroad Degree of urbanity of postal code, of address in 2015 Based on average number of addresses per km2 of the area: Urban areas may offer more opportunities to build one’s CV and engage in extracurricular activities, which may be (an element of) a selection instrument used in The Netherlands [47]. A Canadian study showed lower performance in a multiple mini interview of applicants who graduated from a rural high school [32]. 1. Very strong (2500 or more) 2. Strong (1500–2499); 3. Average (1000–1499); 4. Weak (500–999); 5. Not at all (less than 500) Recoded in 3 categories to create groups of sufficient size for logistic regression analysis: 0 = (Very) strongly urban 1 = Averagely urban 2 = Weakly/not urban Parental data Income percentile of parent with highest income Scale of 1–100, recoded in 3 categories to create groups of sufficient size for logistic regression analysis: The known barriers of low SES in the education field in general or in access to higher education, and the disproportionate share of students from high-income families among health professions education students [48–50]. Income and assets percentiles, rather than their values in euros, were included because percentiles indicate the relative position one occupies compared to the rest of the population. 0 = Percentile 1–70 1 = Percentile 71–90 2 = Percentile 91–100 Household assets percentile b Scale of 1–100, recoded in 3 categories to create groups of sufficient size for logistic regression analysis: 0 = Percentiles 1–40

1 = Percentiles 41–80 2 = Percentiles 81–100 (Continued) PLOS ONE Inequality of opportunity in Dutch selection procedures limits diversity in higher education PLOS ONE | https://doi.org/10.1371/journal.pone.0292805 October 13, 2023 9 / 24