Bibliographic record
Abstract
Around the globe, clinical legal education [CLE] narratives resonate with a desire to promote social justice and the vindication of human rights. Yet scholarship exploring CLE’s accomplishment of these aims is scant and generally focuses only on student outcomes. This literature appears to be based not on theory and results, but hope: the hope that changed students will change the world. To invest on hope alone is unwise, particularly when all stakeholders face financially precarious times. In this context, this article argues that the existing focus on student outcomes is disproportionate and unhelpful. The existing narrow focus on student outcomes marginalizes other stakeholders and creates significant blind spots in program evaluation. This article proposes a broader analysis that would ask what value systems and power distribution CLE programs themselves create or reinforce, focusing on both the immediate impact of CLE programming and reinforcing the values human rights education seeks to inculcate by incorporating these into the structure of CLE programs themselves.
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 | 0.303 | 0.322 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.018 | 0.012 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".