Un débat entre statisticiens du xixe siècle : comment obtenir la nécessaire collaboration de la population à l’exercice du recensement ?
Bibliographic record
Abstract
Obtenir la collaboration de la population lors d’une enquête statistique implique dans l’esprit de la plupart des statisticiens d’État, une obligation de répondre. En 2010, au Canada, le gouvernement conservateur avait aboli de fait l’obligation de répondre au questionnaire long du recensement de 2011, suscitant une vive controverse. Cet article remonte aux sources des débats sur l’obligation dans les pays occidentaux. Nous montrons que la Commission centrale de statistique de Belgique, dès les années 1840, et les Congrès internationaux de statistique, dès leur première occurrence en 1853, ont longuement discuté les divers aspects du problème et que ce n’est qu’en 1860 qu’une norme internationale est établie et qu’une sorte de sagesse statistique est dégagée : obliger quand c’est nécessaire et en tenant compte des normes culturelles et constitutionnelles, sans nécessairement le dire explicitement et tout en sanctionnant le moins possible.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.078 | 0.156 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".