“If I Do not Go to Work, They Will Die!” Dual Roles of Older-Adult Personal Support Workers’ Contributions During the COVID-19 Pandemic
Bibliographic record
Abstract
Abstract When COVID-19 devastated older-adult organizations (long-term care homes and retirement homes), most public attention was directed toward the older-adult residents rather than their service providers. This was especially true in the case of personal support workers, some of whom are over the age of 55, putting them in two separate categories in the COVID-19 settings: (1) a vulnerable and marginalized group who are disproportionately impacted by COVID-19; and (2) essential healthcare workers. Since the current disaster-driven research, practice, and policy have primarily focused on generalized assumptions that older-adults are a vulnerable, passive, and dependent group rather than recognizing their diversity, expertise, assets, and experiences, this study aimed to identify their contributions from the perspective of older-adult personal support worker (OAPSW). This qualitative study conducted in-depth interviews, inviting 15 OAPSWs from the Greater Toronto Area, Canada. This study uncovered the OAPSWs’ contribution at three levels: individual (enhancing physical health, mental health, and overall well-being), work (improving working environment and service and supporting co-workers), and family (protecting their nuclear and extended families). The outcomes inform the older-adult research, practice, policy, public discourse, and education by enhancing the appreciation of older-adults’ diverse strengths and promoting their engagement and contributions in disaster settings.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".