Policing Work: Emotions and Violence in Institutional Work
Bibliographic record
Abstract
We merge research on institutional policing with the growing interest in violence in organization studies to explore how citizen enforcement of regulations can evoke emotion and even, under certain circumstances, turn violent. We draw on long interviews to explore how fly fishing guides enforce catch-and-release fishing regulations in the absence of the state. Our primary theoretical contribution is the development of the policing work construct, including a typology of different policing tactics. Therein, we unpack how emotional thresholds explain shifts away from peaceful enforcement tactics fostered by everyday emotions and towards violent tactics reinforced by extraordinary emotions and a desire for vengeance. We also reflect on the constitutive role of violence in policing work, shedding light on vigilantes as a veiled yet crucial line of defense for enforcing institutions. Finally, we show that institutional custodianship can be claimed by ordinary citizens, motivated by their deep connection to and guardianship of an institution’s integrity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".