Bibliographic record
Abstract
Abstract The goal of this paper is to quantify both the output and the impact of the past decade's scholarly research carried out by those academics currently employed by Canadian business schools, using journal paper counts and citation analysis. We find that the per capita paper output in Canadian business schools is relatively low and is declining. We also find that there are significant differences across Canadian business schools, and that the paper and citation credits are highly variable, with a few “stars” producing most of the impact. Résumé Dans cet article nous essayons de mesurer le rendement et l'impact de la recherche académique dans les écoles canadiennes d'affaires pendant la dernière décennie, en utilisant le comptage des articles publiés et le nombre de citations dans un ensemble des revues spécialisées. Nous constatons que la production des articles par les écoles canadiennes est relativement basse et que la tendance va en empirant. De plus, nous constatons qu'il y a des différences significatives parmi les écoles canadiennes en termes de production académique, avec quelques chercheurs responsables pour la majorité de la production totale.
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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 | 0.004 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.025 | 0.039 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".