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Record W4411161845 · doi:10.1177/0032258x251350967

Predicting police contact: Exploring the impact of legal cynicism on residents’ willingness to contact the police

2025· article· en· W4411161845 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Police Journal Theory Practice and Principles · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCynicismCriminologyPsychologySocial psychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Research on legal cynicism – the perception that the law and law enforcement officers are illegitimate , unresponsive , and ill-equipped – reveals a complex and heavily nuanced relationship between civilians’ perceptions of the police and their engagement with police services. While legal cynicism is said to reduce civilian crime reporting, it has not always been shown to dissuade civilians from contacting the police for help. Drawing upon data from the United States 2020 Police-Public Contact Survey, this study establishes legal cynicism as a facet of residents’ cultural repertories about the law and the legal system (i.e., a ‘toolkit’ residents draw on to guide their behaviour). Legal cynicism predisposes an unwillingness to contact the police for help in the future. This study grounds past scholarship by utilizing a specific measure for the three facets of legal cynicism, offers critical insight into the evolution of legal cynicism, and argues for practitioners to expand upon procedural justice strategies to improve police-community relations.

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.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.100
GPT teacher head0.418
Teacher spread0.318 · 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