Science Advances

Supplementary Materials

This PDF file includes:

  • Table S1. Data summary for collected tenure-track faculty from each discipline.
  • Table S2. Statistical measures of inequality by discipline.
  • Fig. S1. An example graph A, the two minimum violation rankings (MVRs) on these vertices, both with Sp(A) = 3, and a “consensus” hierarchy, in which the position of each u is the average of all positions that u takes in the MVRs.
  • Fig. S2. Bootstrap distributions (smoothed) for the fraction of unviolated edges r in the empirical data (filled) and in a null model (dashed), in which the in- and out-degree sequences are preserved but with the connections between them otherwise randomized, and those for the empirical data.
  • Fig. S3. Prestige uncertainty versus prestige, shown as the SD of the estimated distribution versus the distribution mean, for (A) computer science, (B) business, and (C) history.
  • Fig. S4. Changes in rank from doctoral institution u to faculty institution v, for each edge (u, v) in (A) computer science, (B) business, and (C) history.
  • Fig. S5. Changes in rank from doctoral institution u to faculty institution v, for each edge (u, v) in (A) computer science, (B) business, and (C) history, divided by male versus female faculty for u in the top 15% of institutions (top panels) or in the remaining institutions (bottom panels).
  • Fig. S6. Ratio of the median change-in-rank, from doctoral institution u to faculty institution v, for men versus women, for faculty receiving their doctorate from the “most prestige” institutions, showing that elite women tend to place below their male counterparts in computer science and business (ratio < 1).
  • Fig. S7. Changes in rank from doctoral institution u to faculty institution v, for each edge (u, v) in (A) computer science, (B) business, and (C) history, divided by faculty who have held one or more postdoctoral positions versus those that held none, for u in the top 15% of institutions (top panels) or in the remaining institutions (bottom panels).
  • Fig. S8. Centrality measures versus prestige rank.
  • Fig. S9. Placement accuracy for assistant professors.
  • Fig. S10. Prestige scores for the top 60 institutions for (A) computer science, (B) business, and (C) history.
  • Fig. S11. Centrality versus prestige rank for (A) computer science, (B) business, and (C) history departments, where centrality is defined as the mean geodesic distance (also known as closeness) divided by the maximum geodesic distance (diameter).
  • Fig. S12. Relative change in rank from doctoral to current institution for all Full, Associate, and Assistant Professors in (A) computer science, (B) business, and (C) history.
  • Fig. S13. Geographic structure of faculty hiring.
  • References (34–49)

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Other Supplementary Material for this manuscript includes the following:

  • Dataset 1: Business Faculty-Hiring Network Edges.
  • Dataset 2: Business Faculty-Hiring Network Vertex Attributes.
  • Dataset 3: Computer Science Faculty-Hiring Network Edges.
  • Dataset 4: Computer Science Faculty-Hiring Network Vertex Attributes.
  • Dataset 5: History Faculty-Hiring Network Edges.
  • Dataset 6: History Faculty-Hiring Network Vertex Attributes.

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