Snowbirds and snowflakes: Mobility and aging across the Canada‐United States border
Bibliographic record
Abstract
Changes brought about by globalization such as the growth of the travel industry and increasing interconnectivity between places have opened up new lifestyle options for Canadian retirees. Commonly called “snowbirds,” thousands of Canadian retirees choose to spend their winters in warm destinations outside Canada, with most going to localities in the southern United States. Most snowbirds visit the same place every year and spend many years going back and forth between Canada and their chosen winter destination. Drawing on insights from both life‐course theory and the new mobilities paradigm, this paper considers how the cross‐border snowbird phenomenon links to wider processes related to aging. Qualitative interviews were conducted with retirees wintering in various communities in southern Florida. The findings of the study highlight the importance of understanding both aging and mobility as processes that intersect in variable ways over time to influence new geographies of aging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".