COVID-19: Pandemic Risk, Resilience and Possibilities for Aging Research
Bibliographic record
Abstract
The COVID-19 global crisis is reshaping Canadian society in unexpected and profound ways. The significantly higher morbidity and mortality risks by age suggest that this is largely a "gero-pandemic," which has thrust the field of aging onto center stage. This editorial emphasizes that vulnerable older adults are also those most affected by COVID-19 in terms of infection risk, negative health effects, and the potential deleterious outcomes on a range of social, psychological, and economic contexts - from ageism to social isolation. We also contend that the pathogenic analysis of this pandemic needs to be balanced with a salutogenic approach that examines the positive adaptation of people, systems and society, termed COVID-19 resilience. This begs the question: how and why do some older adults and communities adapt and thrive better than others? This examination will lead to the identification and response to research and data gaps, challenges, and innovative opportunities as we plan for a future in which COVID-19 has become another endemic infection in the growing list of emerging and re-emerging pathogens.
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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 | 0.014 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".