Law and Learning 'from the Field': The Pedagogical Relevance of Collaborative Teacher-Student Empirical Legal Research
Bibliographic record
Abstract
Le présent article explore la valeur pédagogique et la pertinence de faire de la recherche empirique en éducation juridique. Les auteures sont une professeure et une étudiante en droit qui ont collaboré dans une étude empirique sur les femmes et la polygamie. Chaque auteure raconte : (1) ses attentes et ses expériences concernant ce projet de recherche; (2) comment la collaboration dans la recherche empirique a modifié la structure de la relation étudiante-professeure; et (3) sa perception de la façon dont l’importance de la recherche empirique peut être reconnue dans le cadre de l’éducation juridique. L’analyse met en lumière le fait que des phénomènes similaires peuvent donner lieu à une compréhension et à des interprétations différentes, selon la perspective et la situation de chacun et de chacune. De plus, elle souligne l’importance d’intégrer les idées et les opinions des étudiants et des étudiantes dans la conception et l’exercice de l’enseignement.
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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 | 0.047 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.031 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".