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Record W7065372274

The dynamics of police legitimacy among young people

2014· report· en· W7065372274 on OpenAlexaboutno aff

Bibliographic record

VenueResearch Portal (Queen's University Belfast) · 2014
Typereport
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsNorthern irelandSample (material)Quarter (Canadian coin)LegitimacyPerceptionDynamics (music)Suicide prevention
DOInot available

Abstract

fetched live from OpenAlex

Surveys conducted in Northern Ireland generally find that young people with overtly negative views of the police are a minority, albeit a substantial one (Byrne, Conway, & Ostermeyer, 2005; Hamilton, Radford, & Jarman, 2003). One of the most comprehensive studies of young people’s experiences and perceptions of the police in Northern Ireland was conducted by Hamilton, Radford and Jarman (2003). More respondents in their sample of 16-24 year olds agreed than disagreed that the police were professional, helpful and there to protect them. However this still left around one quarter of young people who were very dissatisfied with the police. Although Hamilton et al.’s sample was not a random sample, so such frequencies should be treated with caution, their general findings are largely replicated by the 2007 Young Persons Behaviour and Attitudes Survey (YPBAS), which takes a random sample of schools in Northern Ireland, and a random sample of classes within those schools. The YPBAS found that while 48 percent were either satisfied or very satisfied with ‘the way police in Northern Ireland do their job’, 24 percent were either not very or not at all satisfied.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.015
GPT teacher head0.292
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2014
Admission routes1
Has abstractyes

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