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Record W4401215739 · doi:10.6000/1929-4409.2024.13.17

Metropolitan Policing in Crisis

2024· article· en· W4401215739 on OpenAlexvenueno aff
Matt Clement

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsAuthoritarianismMetropolitan areaMetropolitan policeLegislationTheme (computing)Government (linguistics)CriminologySociologyGeorge (robot)Political scienceSocial movementMedia studiesLawPoliticsDemocracyHistory

Abstract

fetched live from OpenAlex

Ever since the killing of George Floyd in May 2020, there has been a growth in social movements resisting aspects of policing in the US and the UK. In the UK it has evolved in particular directions in response to various controversies in policing and a growing mood to resist increasingly authoritarian legislation emerging from government, in part to repress the very movements they are bringing forth. This paper was delivered as part of an ESRC-funded ‘Festival of Social Science’ run at Royal Holloway University of London in November 2023 under the theme ‘Is it a crime to protest?’ and reflects on these trends as well as reviewing the need for a more critical turn in Criminology and Sociology.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0050.003
Open science0.0010.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0260.003

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 head0.442
Teacher spread0.342 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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