Constitutionally Conforming Interpretation – Comparative Perspectives
Bibliographic record
Abstract
This is the first part of a 2-volume set that presents an in-depth investigation into the canon of constitutionally conforming interpretation. These volumes address the fundamental issues the canon raises in the national, supranational and international contexts. In volume 1, experts from 19 jurisdictions, including Brazil, Canada, India, the UK, and the USA, present reports which give concise overviews of the approaches and debates on constitutionally conforming interpretation. These reports cover the structural background, the conditions of application, as well as issues of competence. Further aspects discussed are its perceived normativity and popularity in everyday legal practice. Together with volume 2, which explores the canon’s use and theoretical impact beyond the national context in a comparative and critical manner, this book fills an important gap in legal scholarship and sets the stage for cross-national discourse.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.061 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| 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".