Collective advocacy in the age of neoliberalism: Getting political in an interdisciplinary law clinic
Bibliographic record
Abstract
Background: In a context of neoliberal policies where social, health and legal services are increasingly scarce, legal or interdisciplinary clinics can play a pivotal role in defending the rights of the most marginalized, in addition to training students on the structural and political dimension of the law and social-work practices. Purpose: Based on students’ experiences of collective advocacy at the Outaouais Interdisciplinary Social Law Clinic Law Clinic, this article explores the nature and impact of learning through community engagement and collective advocacy. Methodology: A case study conducted through semi-structured interviews with 9 clinic students and analyzed using an inductive approach. Findings/Conclusions: The learning experiences transform students’ conception of justice, by integrating the basic needs of all community members along with ending oppressive police and judicial practices, but also the role they wish to play as future professionals for social justice. Implications: These findings demonstrate the importance of addressing the political dimension of higher education.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.033 | 0.028 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.012 | 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".