The allocation of responsibility for later life: Canadian reflections on the roles of individuals, government, employers and families
Bibliographic record
Abstract
Set against the backdrop of an ageing population and the discourse surrounding old age, risk and the welfare state, this paper draws on 51 semi-structured life-history interviews to examine how mid- and late-life Canadians discuss and allocate responsibility for the provision of social, financial and medical supports in later life. Whatever their personal circumstances, most individuals articulated sentiments of personal responsibility for later life. Individual planning and preparation were defined as necessary to secure against the perceived individual and collective risks associated with becoming and being old. The role of the state was intimately connected to individual responsibility, as ‘deserving’ citizens were understood to have legitimate claims to state-supported pensions, health care and social programmes. Although some participants cited the provision of pensions, the least consensus concerned employers' responsibilities. Meanwhile, with the exception of emotional support, most participants had minimal expectations of their relatives or family members. Most rejected the notion that family members should provide housing, financial support or personal care. It is concluded that individual perceptions of risk and responsibility have profound connections to state support, public policy and normative patterns of familial and employer assistance in later life.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.054 | 0.019 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| 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".