Bibliographic record
Abstract
In this article, I identify and critique the technocentric approach to lawyering skills that is prevalent in discourse about clinical legal education. The technocentric approach views legal practice as apolitical and uncontested, and tends to preclude alternative and critical visions of legal practice. I argue that clinical legal education should not be primarily understood as a vehicle by which to transfer a set of pre-determined technical lawyering skills to students. Rather, I argue that clinical legal education should be viewed as an opportunity for students to learn, through critical reflection upon experience, about the contested, contextual, and political nature of legal practice, and to begin to develop skills that reflect this critical understanding. I draw on critical pedagogical theories and provide examples from the clinical law program at the University of Saskatchewan College of Law to suggest directions for this approach.
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 | 0.029 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.002 |
| Science and technology studies | 0.008 | 0.071 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".