Referee report. For: A critical discourse analysis of the Quebec media’s portrayal of older adults in residences and long-term care homes pre- and peri-COVID-19 [version 1; peer review: 1 approved with reservations]
Bibliographic record
Abstract
Background: How we discuss older adults can influence our perceptions of aging and age-related policies, particularly during times of crisis. Ageist discourse in the media impacts how society views older adults and how older adults view themselves . Negative stereotypes have been associated with negative health outcomes and can exacerbate the adverse events faced by older adults during a pandemic. This study examined the Quebec media’s portrayal of older adults living in long-term care (LTC) homes before and during the first wave of COVID-19. Methods: The first confirmed COVID-19 case in Quebec was on 27 February 2020. The Factiva database was searched for newspaper articles that were published three months before (pre) and three months after (peri) the first confirmed case. Articles had to include the terms: older adults, LTC, and/or residence. Articles were excluded if they did not discuss direct or indirect impacts in the lives of people living in LTC ( i.e. , only discussed statistics of COVID-19 cases). After screening, 208 articles were retained, and critical discourse analysis was conducted. Results: The media discourse regarding older adults in LTC homes revealed a lack of resources ( i.e. , insufficient staff) and negative health outcomes for older adults ( i.e. , bed sores) in both the pre- and peri-COVID-19 articles. Negative and positive elements emerged from the peri-COVID-19 discourse, including increased social isolation of those in LTC, government action and advocacy (by health care practitioners and family) to support those in LTC homes. Conclusions: Existing systemic problems were exacerbated by the pandemic and this impacted older adults in LTC homes negatively. Despite this, the peri-COVID-19 discourse suggests meaningful change at the societal and policy levels to improve outcomes for future generations of older adults who reside in LTC homes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.012 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.315 | 0.059 |
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".