The “Vulnerability” Discourse in Times of Covid-19: Between Abandonment and Protection of Canadian Francophone Older Adults
Bibliographic record
Abstract
The Covid-19 pandemic has been particularly difficult for older Canadians who have experienced age discrimination. As the media can provide a powerful channel for conveying stereotypes, the current study aimed to explore how Canadian Francophone older adults and the aging process were depicted by the media during the first wave of the Covid-19 pandemic, and to examine if and how the media discourse contributed to ageist attitudes and behaviors. A content analysis of two French Canadian media op-eds and comment pieces (n = 85) published over the course of the first wave of the pandemic was conducted. Findings reveal that the aging process was mainly associated with words of decline, loss, and vulnerability. More so, older people were quasi-absent if not silent in the media discourse. Older adults were positioned as people to fight for and not as people to fight along with in the face of the pandemic. The findings from this study enhance the understanding of theories and concepts of the Theory of Social Representations and the Stereotype Content Model while outlining the importance of providing older people with a voice and a place in the shaping of public discourse around aging. Results also illustrate the transversality and influence of ageism in this linguistic minority context.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".