Legislative Capacity and Human Rights in the Age of Populism–Two Challenges for Legislated Rights: Discussion of Legislated Rights – Securing Human Rights Through Legislation
Bibliographic record
Abstract
In Legislated Rights: Securing Human Rights Through Legislation, the authors seek to challenge the judicial-centered approach to the protection of human rights that has characterized legal scholarship in the last 50 years. This period has been referred to as the ‘global expansion of judicial power’ by scholars such as Tate and Vallinder,1 who edited an important volume in 1997 that considered the growth of judicial protections of human rights since the end of the Second World War. Although Tate and Vallinder were not the first to consider the role of the courts in the protection of human rights, their edited volume captures the academic...
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.068 |
| Scholarly communication | 0.015 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.015 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 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".