Workfare under Ontario Works: Making Sense of Jobless Work
Bibliographic record
Abstract
Abstract Ontario Works is a provincial income assistance programme of last resort, operating under a workfare policy structure. Based on interviews with clients and staff (case managers, supervisors, managers and administrators), as well as an examination of policy directives, this article explores the work of workfare including claims making, training and resocialization, and employment internships. This article asks particularly how the work of workfare and the complex and costly workfare infrastructure is justified in the face of its failure to lead to employment. Findings include a contrast between the official story of an employment‐focused programme and workers' reports of spending far more time on eligibility than employment readiness. In addition, applying Gramsci's notion of ‘common sense’, an argument is developed that the normative justification for workfare is based not on the effectiveness of workfare programmes, but on the belief that clients need to exchange their work for welfare and self‐improvement so that they appear ‘employment ready’ even if not employed.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.042 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.004 |
| 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".