The Canada Research Chairs Program and Social Science Reward Structures
Bibliographic record
Abstract
Les auteurs analysent les comptes rendus des publications et des citations des Chaires de recherche du Canada en sociologie, en science politique et en économie au cours des cinq années pendant lesquelles le programme s'est poursuivi. Ils les comparent à des échantillons aléatoires de comptes rendus de publications et de citations qui ne sont pas le fruit des Chaires de recherche du Canada dans leur discipline respective pour tester leur qualité professionnelle. Les données et les analyses démontrent que les membres de ces Chaires de recherche constituent une population hétérogène ayant peu de «vedettes» authentiques et dont plusieurs personnes présentent des comptes rendus de publications et de citations semblables ou inférieurs à ceux de leurs collègues qui ne sont pas membres des Chaires de recherche du Canada. Les auteurs explorent la monotonie institutionnelle, l'appropriation institutionnelle ainsi que la périphéricité et l'organisation disciplinaire canadiennes en tant qu'explications possibles de ces résultats. This article analyzes the publishing and citation records of Canada Research Chairs (CRCs) in sociology, political science, and economics over the first 5 years of the program. Publication and citation records of CRCs are compared with random samples of non‐CRCs in their respective disciplines as empirical tests of professional strength. The data and analyses suggest that CRCs are a heterogeneous population with a few obvious “stars” and many with publishing and citation records similar or inferior to their non‐CRC peers. Institutional flatness, institutional appropriation, and Canadian peripherality and disciplinary organization are explored as possible explanations for these results.
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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 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".