“We Never Refer to Ourselves as a Lobby Group Because ‘Lobby Group’ Has a Different Connotation”: Voluntary Police Associations and the Framing of Their Interest Group Work
Bibliographic record
Abstract
The police, like other groups in civil society, have a vested interest in the outcome of government policy deliberations. Collectively, they often attempt to advance policy agendas through several lobbying techniques that suggest that their voluntary associations could be properly understood as interest groups. And yet, there is often ambivalence or a deep reluctance on the part of police organizations to characterize their politicking as interest group work. In the present article, we draw on interviews, media reports and various other materials to elucidate some of the rhetorical strategies used to recast police interest-group work. Further, we explain the reluctance of police leader groups to be seen as overtly political and contrast this to attitudes held by police rank-and-file groups that more openly characterize their interest group work as “lobbying.” The overall goal of this article is to contribute to a surprisingly thin literature on the politics of the police.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.059 |
| Scholarly communication | 0.011 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".