Prestige and Stratification of the Academic Careers of University Presidents
Bibliographic record
Abstract
One of the factors involved in academic career stratification may be the prestige gained from graduating from a high-ranking university (Bedeian et al., 2010; Sweitzer & Volkwein, 2009). Future academics accumulate cultural capital as they move through schools and/or departments that are highly regarded in the field of higher education (Bourdieu, 1988; DiMaggio & Mohr, 1985). In the process, academics acquire cumulative advantage, experience differing degrees of career success, including appointments of varying status and prestige. This thesis examines the unfolding of this process in the career of university presidents. The question guiding this thesis is: What is the relationship between the status of universities where presidents earned their terminal degrees (TDs) and the status of the institutions that they lead, when controlling for other relevant variables? This exploratory quantitative study is presented as two academic articles for publication: one on Canadian university presidents and one on American university presidents. Data for this thesis were collected on 314 presidencies between 1980 and 2021 at 78 Canadian public universities and 630 presidencies from a stratified random sample of 291 American institutions. Terminal degree prestige and recent role prestige were found to be positively related to presidential university prestige in both Canada and the United States. As well, racialized presidents were more likely to lead Canada’s more prestigious institutions and more likely to lead less prestigious American institutions, while women presidents in the United States were most likely found leading high and low-prestige institutions compared to mid-range ones; there was no statistically significant relationship between gender and presidential university prestige in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".