Bibliographic record
Abstract
*This contribution has not been peer-reviewed. When the COVID-19 pandemic moved law classes online, the University of Saskatchewan College of Law admitted an additional twelve students. These students had the lowest index scores in their class. This paper reviews their first year academic performance, compares it to other students admitted in the same year, and concludes that at least at the margin, applicants’ index score is not an accurate predictor of academic success. The author recommends that admissions committees use additional criteria, at least for applicants at the margin. Lorsque la pandémie de COVID-19 a entraîné la mise en ligne des cours de droit, la faculté de droit de l’université de Saskatchewan a admis douze étudiants supplémentaires. Ces étudiants avaient les notes d’index les plus basses de leur classe. Dans cet article, nous examinons leurs performances académiques en première année, les comparons à celles d’autres étudiants admis la même année et concluons qu’au moins à la marge, le score d’index des candidats n’est pas un prédicteur précis de la réussite académique. L’auteur recommande aux comités d’admission d’utiliser des critères supplémentaires, au moins pour les candidats marginaux.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.502 | 0.417 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".