THE CONCERNS OF CANADIAN WOMEN ACADEMICS: WILL FACULTY SHORTAGES MAKE THINGS SETTER OR WORSE?
Bibliographic record
Abstract
ABSTRACT. The purpose of this article is to apply a gender analysis to a predicted trend in Canadian academic life, the expected decline in numbers over the coming decades as new numbers do not keep pace with retirements of the baby-boom generation. The first section develops the notion of a gender analysis and gives a brief summary of my own research on Canadian women academics. The next section describes the faculty shortage problem and its likely impact on Canadian higher education. Then the two topics are brought together by questioning how the shortages might impact upon the concerns of women academics. Here I imagine three scenarios based on different ways governments and universities might respond to the issue. The article concludes with a consideration of what a gender analysis has told us about the predieted shortage problem. LES INQUIETUDES DES FEMMES CANADIENNES POSSEDANT DES DIPLOMES UNIVERSITAIRES; LA PENURIE DANS LES FACULTES AMELIORERA-T-ELLE OU AGGRAVERA-T-ELLE LES CHOSES? RESUME. Le but de cet article est d'appliquer une analyse des questions de parite a une tendance prevue dans la vie universitaire, soit le declin attendu dans les facultes au cours des prochaines decennies en raison des departs a la retraite de la generation des baby-boomers. La premiere section explore en detail l'idee d'une analyse des donnees en fonction du sexe et contient un bref sommaire de ma propre recherche sur les femmes universitaires canadiennes. La section suivante decrit le «probleme de penurie dans les facultes» et ses repercussions possibles sur l'enseignement superieur au Canada. Les deux sujets sont ensuite reunis afin d'analyser de quelle facon la penurie peut se repercuter sur les preoccupations des femmes universitaires. J'elabore trois scenarios fondes sur differentes solutions que peuvent envisager les gouvernements et les universites pour resoudre ce probleme. Dans sa conclusion, l'article se concentre sur ce qu'une analyse des questions de parite nous renseigne sur la penurie prevue dans les facultes.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.031 | 0.012 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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".