DE LA CLARTÃ Ã LâARBITRAIRE : LE CONTRÃLE DE LA QUESTION ET DES RÃSULTATS RÃFÃRENDAIRES PAR LE PARLEMENT CANADIEN
Bibliographic record
Abstract
La Llei de claredat planteja greus problemes, tant en termes de contingut (les seves disposicions són imprecises, excessives, arbitràries, possiblement siguin contràries al principi d’igualtat política entre votants, etc.), com en termes de la forma en què va ser adoptada. Promulgada unilateralment pel Parlament federal, la llei està vulnerant, en alguns aspectes, la facultat que tenen les assemblees legislatives provincials per organitzar eleccions i referèndums a escala provincial i, en alguns altres aspectes, la competència exclusiva del poder constituent per modificar, d’acord amb la Part V de la Constitució de 1982, les normes supralegislatives –escrites o no– que conformen el dret constitucional canadenc. Malgrat que diversos autors han criticat o elogiat l’adopció de la Llei de claredat, aquest estudi té com a objectiu qüestionar, no tant l’oportunitat política d’aquesta llei, sinó la seva constitucionalitat. En l’examen de les discrepàncies existents entre els requisits esmentats pel Tribunal Suprem del Canadà en referència a la secessió del Quebec de 1998 i els establerts per la Llei de claredat, el nostre propòsit és demostrar que la modificació de normes supralegislatives per recomanació del Tribunal Suprem pertany al poder constituent i no pas al Parlament federal.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.023 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.020 | 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".