Complaints‐Based Entrepreneurialism: Worker Experiences of the Employment Standards Complaints Process in Ontario, Canada
Bibliographic record
Abstract
In Ontario, workers who face unfair working conditions have the option of filing an official complaint with the Ministry of Labour. Complaints making is characterized as a widely available, easily accessible, and free-of-cost avenue for workers who may have experienced a violation of the law. However, interviews with Ontario workers who have filed complaints tell a different story. This paper is based on a community-university project on the enforcement of the Employment Standards Act in Ontario. We draw on 36 interviews with workers employed in precarious jobs in Sudbury, Toronto, and Windsor, who filed complaints to the Ministry. Workers characterize the complaints process as rife with bureaucratic complexity, risk, and unsuccessful payouts. Their experiences shed light on the efficacy of complaint-based approaches that are often promoted as a form of "bottom-up" enforcement of employment standards (ES). We demonstrate that the current ES complaints system requires workers to enact neoliberal entrepreneurialism (rather than agentic or collective entrepreneurialism) creating a highly stressful, enormously time-consuming, and demoralizing experience. We document the increasingly individualized and contradictory avenues through which workers must act as entrepreneurs to navigate and self-advocate when their rights have been violated. We argue that the current complaint processes limit the potentially empowering impact of this strategy.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.047 | 0.025 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".