Bibliographic record
Abstract
This book addresses the age-old tension between law and politics by examining whether the personal beliefs of judges come into play in adjudicating on issues of religious freedom, sex discrimination, and social and economic rights. Decisions by the Supreme Courts of India, Japan, Canada, the United States, Ireland, Israel, the Constitutional Courts of Germany, Hungary, South Africa, and the European Court of Human Rights on such controversial issues as government funding of religious schools, abortion, same-sex marriages, women in the military, and rights to basic shelter and life-saving medical treatment are evaluated and compared. The book develops a radical alternative to the conventional view that judges decide these cases by engaging in an essentially interpretative, and thus subjective, act, relying ultimately on their personal beliefs and political opinions. The book shows that it is possible to exercise impartiality and objectivity in judicial review, based on the principle of proportionality, which acts as an ultimate rule of law and is fully compatible with the ideals of democracy and popular sovereignty. Controversially, the book concludes that although this method of judicial review originated in the United States, American judges generally appear to be far less inclined to this conception of constitutional adjudication than their counterparts in Europe, Africa, and Asia.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".