LOOKING FOR QUALITY: THE EMPIRICAL DEBATE IN ACCESS TO JUSTICE RESEARCH
Bibliographic record
Abstract
Access to Justice remains one of the most contested issues on the law-and-society agenda. There has been continuing conceptual debate over its meaning, its objectives, and its success. Of late, attention has turned to efforts to measure the impact and efficacy of different initiatives aimed at improving individuals’ access to justice. Along with a broader turn toward empirical studies in law, there have been renewed efforts within the access to justice field to develop a more compelling and convincing methodology by which to assess and evaluate these different initiatives.
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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 | 0.122 | 0.349 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.012 | 0.023 |
| Science and technology studies | 0.009 | 0.096 |
| Scholarly communication | 0.026 | 0.059 |
| Open science | 0.006 | 0.013 |
| Research integrity | 0.010 | 0.020 |
| 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".