Retirement Financial Insecurity for Men and Women in Canada: The Impact of Life Course Work and Income Instability
Bibliographic record
Abstract
Abstract Financial security is critical to overall well-being in retirement. Life course disruptions in work due to unemployment or disability may have lasting impacts on financial security in later life, and these effects may or may not be ameliorated by old age security programs and retirement benefits. Women are known to be particularly vulnerable for financial hardship in later life, making their life course experiences especially important in understanding financial well-being in retirement. We examine the Canadian Longitudinal and International Study of Adults (LISA) to assess later life financial insecurity in retirement, including 20 years of data on labor force experiences across adulthood drawn from linked tax records (N=2,353; N=1,079 men and N=1,274 women). The Canadian context is a useful complement to studies in the US due to its diverse and relatively generous public support programs, in addition to personal savings options for retirement. We find that among men, financial insecurity is tied to years reporting unemployment, where for women this outcome is more strongly linked to reports of disability and income assistance across adulthood. Although public and private retirement benefits do not offset these associations for either gender, receipt of income supplements reduce subjective financial insecurity among women. Among men, personal savings have the most robust effect in reducing financial insecurity. Our results suggest that in Canada, with its relatively generous provision of retirement support, life course work and health instability have lasting but differential effects for men and women in retirement.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".