Community crime prevention and crime watch groups as online private policing
Bibliographic record
Abstract
Purpose This paper aims to examine the online communications, symbolism and imagery of 35 community crime prevention and crime watch groups across Canada to explore how these groups organize themselves and assess the resulting community actions. Design/methodology/approach Contributing to digital criminology, gathering data from open access platforms such as Facebook and online platforms such as websites, the authors analyse communications from community crime prevention and crime watch groups in 12 Canadian cities. The authors used qualitative content analysis to explore the types of posts to assess trends and patterns in types of ideas communicated and symbolized. Findings Whilst such groups bring the community together to help promote community safety, the groups may also encourage stereotyping, shaming and even vigilantism through misrepresenting the amount of crime occurring in the community and focusing on fear. The authors demonstrate how crime prevention becomes sidelined amongst most of the groups, and how intense crime reporting and the focus on fear derail actual community development. Research limitations/implications The current study is limited to two years of posts from each group under examination. Interviews with members of online community crime prevention and crime watch groups would provide insights into the lived experience of regular users and their reasons for interacting with the group. Practical implications Given some of the vigilante-style the actions of such groups, the authors would suggest these groups pose a governance problem for local governments. Originality/value Community crime prevention and crime watch groups are not a new phenomenon, but their activities are moving online in ways that deserve criminological research. The authors contribute to the field of digital criminology by researching how online communications shape community crime prevention organizations and how ideas about regulation of crime and social control circulate online. The authors also explain how this community crime prevention trend may contribute to issues of vigilantism and increased transgression.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".