Bibliographic record
Abstract
Purpose – This paper aims to explore the ways in which social supports can promote enduring attachments to work and improve overall well-being of disadvantaged workers, within the context of social purpose enterprises. Design/methodology/approach – With coordinators, managers and directors as informants, this mixed-methods study uses a survey and interviews to establish the availability and importance of different social supports found in social purpose enterprises across Canada, and to explore the reasons for such support mobilization and the influences that determine whether social supports are sought or accepted. Findings – Findings substantiate the prevalence and importance of work-centred social supports. Social supports can promote more sustainable attachment to work by addressing work process challenges, ameliorating workplace conflict, attending to non-vocational work barriers and building workers’ self-confidence and self-belief. The source of a support, as well as the relationship between support providers and recipients, contributes to whether supports will be beneficial to recipients. Research limitations/implications – Future studies require corroboration directly from the employees and training participants of social purpose enterprises. The limitations on the sampling and the survey response rate may limit generalizability of findings. Practical implications – Findings contribute to knowledge on more effective social support provision for improved work outcomes and overall well-being of employees and training participants. Originality/value – Applying theory from social support research brings greater clarity to the potential of work-centred supports for addressing both vocational and non-vocational barriers to employment and job training for disadvantaged 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".