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Record W3026382105 · doi:10.1108/jcrpp-01-2020-0002

Public perceptions of police crime control in South Korea

2020· article· en· W3026382105 on OpenAlexaboutno aff
Ben Brown

Bibliographic record

VenueJournal of Criminological Research Policy and Practice · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPolicing Practices and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsFear of crimeMetropolitan policePublicityVictimisationPsychologyMetropolitan areaPerceptionCriminologyOriginalityCrime controlHomicideQuarter (Canadian coin)Poison controlSocial psychologyInjury preventionGeographyPolitical scienceCriminal justiceEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to examine public perceptions of police efforts to control crime in South Korea. Design/methodology/approach The data were gathered from surveys administered to college students in the Seoul-Gyeonggi Province metropolitan area. Logistic regression analyses were performed to assess the impact of gender, fear of crime and perceived risk of victimization on diffuse and specific perceptions of police performance. Findings The respondents did not view the police favorably. Fewer than half the respondents reported that the police do a good job of controlling drunk driving, approximately a quarter reported that the police do a good job of controlling burglary and investigating homicide and roughly a fifth reported believing that the police effectively control crime. Violent victimization and fear of violent victimization had a significant negative impact on confidence in the police. Practical implications The data suggest that informing the public about the low risk of violent victimization and other publicity campaigns designed to reduce fear of violence may foster confidence in the police. Originality/value This study identifies subtle similarities and differences in the structure of public perceptions of the police between Eastern and Western nations. Additionally, the data indicate there is a need for greater specificity in measures of public perceptions of the police.

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)0.007
metaresearch head score (Gemma)0.083
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.454
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.083
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.642
GPT teacher head0.563
Teacher spread0.079 · 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 designQualitative
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

Citations2
Published2020
Admission routes1
Has abstractyes

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