Enquête sur la santé dans les collectivités canadiennes, 2005 : Cycle 3.1, Composante HSS2
Bibliographic record
Abstract
Le fichier de microdonnées à grande diffusion de l'Enquête sur la santé dans les collectivités canadiennes (ESCC) fournit des données à l'échelle des régions sociosanitaires ou regroupements de régions sociosanitaires du Canada. Les données sont recueillies dans toutes les provinces et tous les territoires, auprès de plus de 130 000 personnes vivant dans un ménage.<p> Le fichier contient des renseignements sur des sujets très variés, dont l'activité physique, la taille et le poids, l'usage du tabac, l'exposition à la fumée secondaire, la consommation d'alcool, l'état de santé général, les problèmes de santé chroniques, les blessures et l'utilisation des services de santé, ainsi que les caractéristiques sociodémographiques, le revenu et la situation d'activité de la population.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".