La mention de la méthodologie des sondages électoraux dans les quotidiens québécois de 1979 à 1997
Bibliographic record
Abstract
Faute de réglementation gouvernementale, la capacité autorégulatrice des médias et un marché concurrentiel permettent-ils d’améliorer la présentation de la méthodologie des sondages électoraux? L’analyse de 390 comptes rendus de sondages électoraux publiés de 1979 à 1997 révèle que le nombre d’informations méthodologiques transmises est demeuré stable après une légère hausse entre 1979 et 1984. L’identité du commanditaire, la nationalité du sondeur, l’intervention d’experts dans le travail journalistique et l’unité territoriale sur laquelle porte le sondage influencent la présentation de la méthodologie. En conclusion, l’autorégulation et la concurrence n’améliorent pas la qualité de la présentation de la méthodologie en raison des intérêts et des contraintes des entreprises de presse, des journalistes et des firmes de sondage.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".