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Record W4378384344 · doi:10.1515/9780228000310

Youth Squad

2019· book· en· W4378384344 on OpenAlexaffabout
Tamara Myers

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2019
Typebook
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Starting in the 1930s, urban police forces from New York City to Montreal to Vancouver established youth squads and crime prevention programs, dramatically changing the nature of contact between cops and kids. Gone was the beat officer who scared children and threatened youth. Instead, a new breed of officer emerged whose intentions were explicit: befriend the rising generation. Good intentions, however, produced paradoxical results. In Youth Squad Tamara Gene Myers chronicles the development of youth consciousness among North American police departments. Myers shows that a new comprehensive strategy for crime prevention was predicated on the idea that criminals are not born but made by their cultural environments. Pinpointing the origin of this paradigmatic shift to a period of optimism about the ability of police to protect children, she explains how, by the middle of the twentieth century, police forces had intensified their presence in children's lives through juvenile curfew laws, police athletic leagues, traffic safety and anti-corruption campaigns, and school programs. The book describes the ways that seemingly altruistic efforts to integrate working-class youth into society evolved into pervasive supervision and surveillance, normalizing the police presence in children's lives. At the intersection of juvenile justice, policing, and childhood history, Youth Squad reveals how the overpolicing of young people today is rooted in well-meaning but misguided schemes of the mid-twentieth century.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.929
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.025
GPT teacher head0.234
Teacher spread0.209 · 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
GenreOther

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
Published2019
Admission routes2
Has abstractyes

Explore more

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