The Practitioner’s Bookshelf: Tenth Anniversary Recommendations
Bibliographic record
Abstract
Abstract With this tenth anniversary issue of the Journal of Human Rights Practice, we are launching ‘The Practitioner’s Bookshelf’—a new feature of the JHRP Review section containing brief reviews of recent publications of particular interest to human rights practitioners. In this instalment, James Loeffler (University of Virginia), Noah Weisbord (Queen’s University, Canada), and Brian Phillips (JHRP) discuss three books they consider to be among the most significant contributions to the literature of human rights practice to have appeared during the JHRP’s first decade.
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 | 0.013 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.028 | 0.020 |
| Insufficient payload (model declined to judge) | 0.133 | 0.089 |
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".