Altering consumer practices, facing uncertainties, and seeking stability: Canadian news media framings of international retirement migrants during the COVID‐19 pandemic
Bibliographic record
Abstract
International retirement migration involves the seasonal relocation of older adults to destinations abroad. For Canadians, this is typically done to escape winter at home in favour of warmer weather elsewhere. In this paper, we explore how Canadian newspapers chronicled the changes associated with managing the COVID‐19 pandemic in Canada, including border measures and calls to avoid non‐essential travel, and how they impacted international retirement migrants and their movements. We specifically present the findings of a framing analysis conducted of 187 newspaper articles published in 2020, identified through the Canadian Newsstream Database. The framing analysis identified three ways in which Canadian international retirement migrants were discussed in relation to the pandemic and the changed spatio‐temporal realities that affected their transnational movements. First, they are a group who altered their consumer practices, which had economic impacts at home and in their usual seasonal destinations. Second, they are a group who faced considerable uncertainty with regard to travel and movement, among other things, as the pandemic unfolded in 2020. Finally, Canadian international retirement migrants sought stability in a number of ways, both in terms of their social networks and living arrangements at home and abroad.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".