‘Not everybody can do this job’: a qualitative inquiry into emotional labour from RCMP detachment services assistants
Bibliographic record
Abstract
Many police organisations employ and rely on public servants to complete specialised tasks with their organisations. The Royal Canadian Mounted Police (RCMP) regularly hires public servants known as Detachment Services Assistants (DSAs) to take on various support roles. As part of DSAs’ many clerical and administrative responsibilities, these workers must often perform emotional labour across different job tasks, which in turn, can be a personal yet occupationally mandated source of stress and strain. In the current study, we draw from semi-structured interviews with DSAs (n = 54) to investigate the different situations in which DSAs undertake emotional labour, the various styles of emotional labour DSAs perform, and the negative toll emotional labour places on DSAs in their workplace. Our research aims to contribute to the broader emotional labour literature on policing and the niche police literature on public servants, a form of civilian staff, employed by the RCMP.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".