EMPLOYMENT SUPPORT SERVICE PROVISION FOR OLDER WORKERS: BOUNDARIES SHAPED THROUGH INDIVIDUALIZATION
Bibliographic record
Abstract
Western economies increasingly promote extended formal labour force engagement across the lifespan. Older workers – persons aged 50 and older – are induced to continue working through policy changes such as increasing age thresholds for pension eligibility or financial penalties for early workforce exit. Such measures presume people’s abilities to choose to continue working, but barriers to sustainable, secure employment disproportionately impact older workers. Front-line support service providers who assist out-of-work older workers must negotiate contemporary individualizing policies and discourses while recognizing their collective experience of difficulty within the labour market. In this presentation, we draw on data from a collaborative ethnographic study that uses governmentality, street-level bureaucracy, and critical occupational science as theoretical frames to understand long-term unemployment in Canada and the United States. Through a critical discourse analysis of qualitative interviews, participant observation field notes, and focus group interviews with 22 front-line service providers, we attend to how service providers negotiated conflicting discursive positions: despite positioning older workers as an ‘at risk’ group, service providers located barriers to employment in individual characteristics such as workers’ attitudes, expectations, or skills. Moreover, service providers proposed activation-based, individualized strategies – such as crafting age-neutral resumes or enhancing computer literacy – as solutions to older workers’ joblessness. As such, dominant discourses aligned with neoliberal individualizing and activating strategies set limits on attention to ageism and other systemic barriers collectively faced by aging workers within service provision practices, bounding how later life long-term unemployment is addressed and inadvertently contributing to precarity.
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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 | 0.009 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.022 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".