Vieillissement de la population : menace ou opportunité ?, établir les faits : la démographie et les stéréotypes
Bibliographic record
Abstract
Au cours des prochains mois, l’Observatoire quebecois du loisir se penchera sur le vieillissement de la population, phenomene majeur qui affectera les decisions en matiere de loisir, de sport et de culture. Trois bulletins exploreront la question. Ce present bulletin traite du phenomene et des prejuges qui l’accompagnent; le deuxieme l’abordera sous l’angle des consequences sur les services publics en loisir, sport et culture; et le troisieme exposera des pratiques de quelques villes hors Quebec qui se sont donne des politiques de gouvernance et de services aux aines. Le 12 mai prochain, dans le cadre des differents moyens utilises par l’Observatoire et ses partenaires pour saisir les tendances qui affecteront les services publics de loisir, un colloque reunira des acteurs en loisir qui prendront connaissance et discuteront des facons de faire des uns et des autres et de quelques villes exemplaires pour accueillir les aines contribuant au developpement des communautes et pour adapter leurs services aux attentes des personnes âgees.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".