Interdisciplinary and Collaborative Approaches Needed to Determine Impact of COVID-19 on Older Adults and Aging: CAG/ACG and<i>CJA</i>/<i>RCV</i>Joint Statement
Bibliographic record
Abstract
The COVID-19 pandemic and subsequent state of public emergency have significantly affected older adults in Canada and worldwide. It is imperative that the gerontological response be efficient and effective. In this statement, the board members of the Canadian Association on Gerontology/L'Association canadienne de gérontologie (CAG/ACG) and the Canadian Journal on Aging/La revue canadienne du vieillissement (CJA/RCV) acknowledge the contributions of CAG/ACG members and CJA/RCV readers. We also profile the complex ways that COVID-19 is affecting older adults, from individual to population levels, and advocate for the adoption of multidisciplinary collaborative teams to bring together different perspectives, areas of expertise, and methods of evaluation in the COVID-19 response.
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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 | 0.057 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.005 | 0.024 |
| Research integrity | 0.016 | 0.024 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".