A Survey of Comparative Methodologies: The Constant Presence and Silent Rise of Intent and History in Constitutional Adjudication
Bibliographic record
Abstract
This article studies how different courts around the world have used intent-based methods of constitutional interpretation that privilege formal legislative history, similar to some versions of originalism in the United States. It also analyzes how these interpretive approaches have produced progressive results in many instances. This generates three lessons. First, that intent-based methods of constitutional interpretation are not an exclusive U.S. phenom- enon. Two, that originalism is not inherently conservative nor reactionary. And third, that a comparative approach can yield important methodological lessons that may be useful for courts and scholars around the world. In par- ticular, this article offers a survey of judicial experiences in countries with different constitutional experiences, such as Australia, Canada, India, Turkey, Malaysia, Singapore, Alaska, Chile and Germany.
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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 | 0.061 | 0.139 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.024 |
| Science and technology studies | 0.006 | 0.026 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".