Tipping points: what participants found valuable in labour market training programmes for vulnerable groups
Bibliographic record
Abstract
Graham JR, Jones ME, Shier M. Tipping points: what participants found valuable in labour market training programmes for vulnerable groups Int J Soc Welfare 2010: 19: 63–72 © 2009 The Author(s), Journal compilation © 2009 Blackwell Publishing Ltd and the International Journal of Social Welfare. This article is based on face‐to‐face and focus group interviews with 72 people who have experienced ongoing difficulties integrating into Canadian labour markets, and who had completed a labour market training programme. Participants were representative of at least one (and often several) categories that inhibited labour market integration: low socio‐economic status, Aboriginal status, single parenthood, criminal justice history and being disabled. The major finding: respondents associated life skills rather than labour‐market skills with success in overcoming personal barriers to securing and maintaining employment. Life skills involved developing life meaning and interpersonal skills related to personal cognition and behaviours. Valued cognitions identified by participants were gaining a new perspective on life and realising that the past impacts the present. Valued behaviours identified by participants included actions associated with understanding personal characteristics and motivations, and building positive social support and social capital. These insights provide theoretically rich considerations for labour market training programmes and could considerably influence labour market policies and practices, particularly since most training programmes and policies are geared toward human capital (i.e. labour‐market skills) accumulation.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".