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Record W7024730549

Situation tables as the new crime prevention: theoretical underpinnings, strengths, weaknesses, and best practices

2018· dissertation· en· W7024730549 on OpenAlexaboutno aff

Bibliographic record

Venuee-scholar@UOIT (University of Ontario Institute of Technology) · 2018
Typedissertation
Languageen
FieldSocial Sciences
TopicCrime, Deviance, and Social Control
Canadian institutionsnot available
Fundersnot available
KeywordsBest practiceTable (database)Law enforcementHarmEnforcementCriminal justiceCrime preventionMental healthBest interestsHarm reduction
DOInot available

Abstract

fetched live from OpenAlex

Change in police calls-for-service has resulted in a shift in the role of police through the years. Specifically, the increase in mental health calls for police services has created the Community Safety and Well-Being (CSWB) model. The CSWB model seeks to prevent social disorganization through proactive community efforts. Situation Tables are a risk-driven, collaborative model in Ontario that falls under the CSWB model. Drawing on in-depth interviews from Situation Table coordinators and other participants, this thesis found that risk, collaboration, and harm reduction are the theoretical underpinnings of the Situation Table. Interestingly, participants identified Situation Tables as an alternative to incarceration in that they proactively address criminal risk factors and offer social services rather than engaging in law enforcement action. In addition, this thesis offers recommendations and best practices for the participation and implementation of Situation Tables as a learning tool for current and future Situation Table participants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.305
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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