Using candidacy theory to explore unemployed over‐50s perceptions of suitability of a welfare to work programme: A longitudinal qualitative study
Bibliographic record
Abstract
Welfare to work interventions seek to move out-of-work individuals from claiming unemployment benefits towards paid work. However, previous research has highlighted that for over-50s, particularly those with chronic health conditions, participation in such activities are less likely to result in a return to work. Using longitudinal semi-structured interviews, we followed 26 over-50s during their experience of a mandated welfare to work intervention (the Work Programme) in the United Kingdom. Focusing on their perception of suitability, we utilise and adapt Candidacy Theory to explore how previous experiences of work, health, and interaction with staff (both in the intervention, and with healthcare practitioners) influence these perceptions. Despite many participants acknowledging the benefit of work, many described a pessimism regarding their own ability to return to work in the future, and therefore their lack of suitability for this intervention. This was particularly felt by those with chronic health conditions, who reflected on difficulties with managing their conditions (e.g., attending appointments, adhering to treatment regimens). By adapting Candidacy Theory, we highlighted the ways that mandatory intervention was navigated by all the participants, and how some discussed attempts to remove themselves from this intervention. We also discuss the role played by decision makers such as employment-support staff and healthcare practitioners in supporting or contesting these feelings. Findings suggest that greater effort is required by policy makers to understand the lived experience of chronic illness in terms of ability to RTW, and the importance of inter-agency work in shaping perceptions of those involved.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 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".