Trends in the residential mobility of seniors in Canada, 1961–2006
Bibliographic record
Abstract
This article examines residential mobility for seniors 65 years of age and older in Canada using census data from 1961–2006. We addressed three questions. First, have seniors been increasingly likely to change their residential location within Canada or alternatively become increasingly likely to age‐in‐place? Second, has the in‐migration of seniors to Canada from other countries become more pronounced over the years? Third, does the residential mobility of seniors vary by age and sex? We used census data to calculate the percentages of seniors who changed their residence in the five‐year periods prior to each of the 1961–2006 censuses and the percentages of seniors who moved in the previous year for the 1991–2006 censuses. We calculated the percentages of seniors making local moves, longer distance moves within the same province, moves from one province to another, and moves to Canada from another country. We found that rates of residential mobility for seniors tended to increase in the 1961–1981 period but have been lower and relatively consistent from 1986–2006. We found no evidence to suggest a pattern of sustained increase in residential mobility of seniors. We conclude that Canadian seniors tend to age‐in‐place and that when seniors do change residence, the likelihood of residential mobility decreases with the distance of the move and decreases with age. Nevertheless, the likelihood of changing residence may increase for seniors 75+ years of age who need assistance and are at risk of institutionalization. We found that senior women were more likely to change residence locally than senior men. Finally, we found that from 1961 to 2006 between 0.8 percent and 1.4 percent of seniors had migrated to Canada in the five years prior to each census from other countries and that this pattern has fluctuated over the past half century with no clear trend.
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 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 | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; a candidate call from one teacher head, 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".