Bibliographic record
Abstract
With 2006 Canadian census data, this paper examines the determinants of retirement in Canada among people aged 50 to 80 years old. Retirement is defined in two ways: fully retired (individuals who leave the labour force completely), and partly or fully retired (individuals who did not work or worked less than 26 weeks during the previous year). Geographical, socio-demographic, immigration and educational characteristics are taken into account in the regression models that explain retirement. Those factors are examined both for males and females and for immigrants and non-immigrants. The study finds that people who live in well-developed and growing areas are less likely to choose retirement. Similarly, people who are single are more likely to retire than couples or widows; however, females who live in a couple are more likely to retire than males in the same situation. In general, females show a higher probability to retire than males, potentially because of the different family responsibilities. Immigrants are less likely to choose retirement due to their relatively low income levels and because of the requirement for receiving retirement pensions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".