Replacing the Canadianization Generation: An Examination of Faculty Composition from 1977 through 2017
Bibliographic record
Abstract
Amid growing numbers of doctoral graduates entering an increasingly competitive global academic job market, concerns about equity in the hiring process and the value of the Canadian Ph.D. are mounting. Grounded within the historical context of the Canadianization Movement, we examine the doctoral credentials of 4,934 U15 social science faculty between 1977 and 2017 to understand the ebb and flow of incoming and outgoing faculty across the country's academic field. Our trend analyses reveal an overall increase in the proportion of Canadian-trained faculty hires with the noted exceptions of Canada's top three universities who display a strong presence of high-status American-trained faculty throughout. Results from the contemporary period, between 1997 and 2017, reveal a time of retirement during which outgoing Canadian-trained faculty are replaced with increasing proportions of American-trained academics.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.018 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".