Le facteur linguistique en situation de démocratie numérique dans un contexte de bilinguisme officiel : le cas de la ville de Moncton (N.-B.)
Bibliographic record
Abstract
Cet article examine les effets de la prise en charge administrative de l’aspect linguistique dans l’instauration des outils de démocratie digitale de la municipalité de Moncton, une ville canadienne officiellement bilingue (français-anglais). Par une étude de cas abordée avec une approche qualitative, il souligne le caractère paradoxal de l’enjeu du bilinguisme, lequel est exprimé comme résolu en revêtant un caractère purement technique au travers de la traduction, alors même qu’il cristallise des tensions politiques, mais aussi des tensions sociales d’inclusion. Dans un cadre interdisciplinaire alliant sociolinguistique et administration publique, il propose une réflexion critique sur les présupposés linguistiques dans la conception des outils de démocratie digitale, et interroge le traitement de ces enjeux et leurs impacts dans l’effectivité et les mécanismes de ces outils.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".