‘You’re Investing in People … It’s Not a Race. It’s Not a Rush’: Youth Care Worker Emotional Labour in Inner-City Neighbourhoods Across Canada
Bibliographic record
Abstract
Emotional labour (EL) is the practice of managing expressions in a given work setting. Using the concept of EL, we aim to understand how youth care workers supporting marginalized youth manage work-related stress and the emotions experienced by young people. The youth supported by these workers experience the effects of secondary prisonization (i.e., indirect exposure to punishment), requiring them to engage in extensive EL. Drawing from qualitative interviews and participant-generated visual data, we show that EL is a crucial part of support work that is not yet well recognized. With the participant-generated visual data, we reveal how emotions are processed and managed. EL enables workers to continue to advocate for the needs and well-being of young people even at times of distress and austerity, at the expense of being exposed to secondary prisonization. Explaining how secondary prisonization extends beyond immediate family members and affects youth care workers at a tertiary level, we argue that one way of investing in the community (rather than expanding the criminal justice system) is by taking the importance of EL in support work seriously and providing better resources for these workers, who present real opportunities and safety for inner-city youths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".