UNCOVERING THE LOCAL SOCIAL RELATIONS OF UNPAID OVERTIME WORK OF SOCIAL WORKERS IN NON-PROFIT SOCIAL SERVICE ORGANIZATIONS
Bibliographic record
Abstract
This study seeks to uncover the local social relations of unpaid overtime work of social workers working in non-profit social service organizations in Ontario. Previous research has identified unpaid overtime work performed by social workers as an ongoing labour issue. For example, Baines, MacKenzie Davis, & Saini (2009) found that 71% of social workers surveyed were ‘donating’ one-six hours of time to their jobs a day. Institutional ethnography is used as a theoretical and methodological framework for this inquiry. Accordingly, this research project focuses on uncovering knowledge about the social organization of unpaid overtime work. This knowledge may be useful for those seeking to make specific changes to the organization of the work of social workers to further prevent or eliminate unpaid overtime work. During this study, three Ontario social workers were interviewed about their jobs and unpaid overtime, and provided further written information over email. One particular account of a problematic, or topic for IE research, was not formulated in this thesis as originally intended. However, three accounts of the everyday experience of unpaid overtime work of social workers are presented and could each be used to formulate a problematic for future IE research into this topic. Potential threads of ruling which are visible in the local setting are discussed, with particular emphasis on the ruling relations of non-payment of overtime work. Other potential threads of ruling identified and discussed include the social organization of ‘an endless workload’ and the social organization of social work ethics.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".