The Police Foundation’s Rise: Implications of Public Policing’s Dark Money
Bibliographic record
Abstract
A new kind of organization has emerged in public policing across the United States and Canada: the ‘police foundation’. The foundation’s private, nonprofit legal status allows it to engage in private fundraising activities that police, as public bodies, cannot. In many municipalities, police foundations raise funds directed toward police procurement practices and operations. We discuss reasons for and detail the rise and growth of these foundations as they have modeled the New York Police Department’s Foundation and changes in that foundations’ expenditures over time, and examine the key claim that police foundations reduce corruption by maximizing transparency. We draw from literature on financial obfuscation and explore controversies centered on police foundation solicitation and use of private funds in North America. Conceptualizing these private entities as shell corporations that permit transactions in dark money, we raise questions about police foundation transparency. We conclude by discussing the implications for public policy as well as police transparency across North America.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.033 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".