On Encountering Life and Learning With/out the Text: Reflections on Bańkowski and Del Mar
Bibliographic record
Abstract
This chapter provides the theoretical and practical context that informs a component designed and delivered in the first-year orientation curriculum at the University of Victorias Faculty of Law. The exercises are drawn from the work of Augusto Boal, as it has been taught to me by several practitioners of Theatre of the Oppressed, including Boal himself, and adapted particularly for the unique setting of the law school environment. The sense that there is a crisis in how law schools and the legal profession are addressing issues of legal ethics and professionalism in Canada seems to be widely shared. The chapter explores how this theoretical approach to pedagogy can be translated into a context, in this case a Canadian law school, in which the idea of oppression translates in different and complicated ways. Of concern is the continued marginalization in the study and practice of law experienced by students on the basis of their lived diversities.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.046 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.007 | 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".