Bibliographic record
Abstract
In the absence of surveys on how police officers vote, studying professional ideologies, which are an expression of a form of politicization of ordinary police officers, which is an integral part of their professional socialization, allows us to approach political orientations in the world of the police. Using a questionnaire survey of 5,221 police officers of all ranks, we identified ideological dissension on how the job of police officer is conceived. The analysis was based on a latent class analysis, which brings to light three opinion classes: repressive, median and preventive. These three profiles allow us to distinguish police officers by their responses to the questions of what the primary tasks of the police are, which groups should be monitored, who the police should choose as partners, and the causes of delinquency. Analysis of the social and professional attributes of police officers in each of the three opinion classes then reveals the preponderance of professional characteristics over socio-demographic variables in the three classes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.996 | 0.986 |
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; both teacher heads agree on what is shown here.
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".