Funding Frontiers: Public Policing, ‘User Pays’ Policing and Police Foundations
Bibliographic record
Abstract
Introduction Public police and security agencies in Western countries must be funded to operate. Such resources are required to pay for personnel and technologies. For decades, this funding is assumed to have come from state revenues, generated through taxes and dispersed by various levels of government. Rarely have public agencies been funded directly by private sources. For private corporate security units, the converse is also true: funding has traditionally come directly from the organisation of which they are a part, namely private corporations. These units do not receive public monies for their operations. Yet it is in the public realm where funding arrangements are adopting a different appearance on policing and security frontiers. This chapter explores new and neglected funding frontiers of policing and security provision. First, we discuss what is aptly called ‘user pays’ policing and related funding arrangements (Ayling and Shearing, 2008; Lippert and Walby, 2014). This is followed by a detailed account of several kinds of users and their understandings of these practices. We next identify some emerging trouble on this frontier, as well as looking at how it is being problematised and governed. One source of trouble in the US, as well as a means of responding to problems stemming from these arrangements, has been the emergence of for-profit ‘user pay’ brokers. We call these brokers ‘vampires’ on the frontier, because they siphon off a percentage of the pay destined in some departments to public police, to cover their underlying costs. We then explore an equally significant funding broker: the public police foundation (Walby et al, 2017). We elaborate on foundation practices in the US and Canada, and include a discussion about foundations and police museum narratives as they concern funding frontiers. To generate further insights about funding frontiers, we compare these developments in North America to the current funding context in the UK. The chapter concludes by raising questions about ‘user pays’ and foundation arrangements for public accountability and transparency in Western countries. ‘User pays’ policing: tollbooths on the funding frontier Many police departments in North America and beyond now offer ‘user pays’ public policing. This kind of policing is happening in Canada, the US, as well as in Australia (Robertson, 2013) and the UK (Barrett, 2016).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".