Bibliographic record
Abstract
A long tradition of research shows job loss to be socially toxic to the health and well-being of individuals and families. In today's economy, seniority no longer means job security, as lay-offs of older workers from their career jobs are increasingly common, but often unexpected by those forced out of work. Older dual-earner couples are in double jeopardy of job lay-offs. What contributes to the resilience of women and men in their fifties and sixties confronting the crisis of job loss, as individuals and as couples? With years of adulthood before them, what ‘encores’ do they seek? We build on a combined ecology of the life-course and stress process framework to theorize four strategic adaptations of older working couples confronting displacement from one or both partners' jobs, drawing on qualitative data to illustrate how they promote resilient life-course fit: (a) changing the situation, (b) redefining the situation, (c) altering relationships, and (d) managing rising strains and tensions. We theorize and find three key resources conducive to and reinforced by a resilient encore of fit: control or mastery over one's life, social connections and support (within the couple but also with others in one's social network), and making a meaningful contribution (through paid work, civic engagement, or family work). Introduction A number of demographic trends – including delays in the labor force participation of younger workers, the aging of the large baby-boom cohort, changes in retirement and Social Security policies and programs – are encouraging longer labor force participation among older people, as well as new scholarly and policy interest in the growing proportion of older workers.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".