The Public Debate on the Port of Religious Signs by the Representatives of The State in Québec (2007‑2018). Between Agreement and Disagreement
Bibliographic record
Abstract
El artículo hace el examen de la evolución del debate apreciado en Quebec desde más de una decena de años sobre el puerto de signos religiosos por los representantes del Estado poniendo en evidencia cómo osciló entre acuerdo y desacuerdo. El análisis muestra que los desplazamientos del debate son determinados por la introducción en su pecho de infra-debates que se refiere en cuestiones subyacentes que modifican los contornos y, a falta de seres plenamente aclarados, lo oscurecen. The article examines the evolution of the debate held in Quebec for more than ten years on the port of religious symbols by the representatives of the State by highlighting how it oscillated between agreement and disagreement. The analysis shows that the movements of the debate are determined by the introduction within it of infra‑debates on underlying questions which modify it outlines and, for lack of completely clarified beings, confuse it. L’article fait l’examen de l’évolution du débat tenu au Québec depuis plus d’une dizaine d’années sur le port de signes religieux par les représentants de l’État en mettant en évidence comment il a oscillé entre accord et désaccord. L’analyse montre que les déplacements du débat sont déterminés par l’introduction en son sein d’infra-débats portant sur des questions sous-jacentes qui en modifient les contours et, à défaut d’être pleinement explicités, l’obscurcissent.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".