La nécessité des approches interdisciplinaires et collaboratives pour évaluer l’impact de la COVID-19 sur les personnes âgées et le vieillissement: déclaration conjointe de l’ACG / CAG et de la RCV / CJA
Bibliographic record
Abstract
La pandémie de la COVID-19 et l'état d'urgence publique qui en a découlé ont eu des répercussions significatives sur les personnes âgées au Canada et à travers le monde. Il est impératif que le domaine de la gérontologie réponde efficacement à cette situation. Dans la présente déclaration, les membres du conseil d'administration de l'Association canadienne de gérontologie/Canadian Association on Gerontology (ACG/CAG) et ceux du comité de rédaction de La Revue canadienne du vieillissement/Canadian Journal on Aging (RCV/CJA) reconnaissent la contribution des membres de l'ACG/CAG et des lecteurs de la RCV/CJA. Les auteurs exposent les voies complexes par lesquelles la COVID-19 affecte les personnes âgées, allant du niveau individuel au niveau populationnel. Ils préconisent une approche impliquant des équipes collaboratives pluridisciplinaires, regroupant divers champs de compétences, et différentes perspectives et méthodes d'évaluation de l'impact de la COVID-19.
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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 | 0.204 | 0.215 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".