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Record W2783421907 · doi:10.1007/s10610-017-9365-y

Do Flood Mitigation and Natural Habitat Protection Employment Reduce Youth Offending?

2018· article· en· W2783421907 on OpenAlex
Michael A. Long, Rebecca Oswald, Paul B. Stretesky, Sarah Soppitt

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEuropean Journal on Criminal Policy and Research · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
FundersNorthumbria University
KeywordsMillQuarter (Canadian coin)Sample (material)PsychologyWork (physics)Political scienceDemographic economicsEngineeringGeographyEconomics

Abstract

fetched live from OpenAlex

The present study examines the association between employment and offending for a sample of young offenders who are paid to work in a pilot programme known as the Skill Mill. First, we analyse a sample of 39 youths over a period of 10 years (40 quarters) to determine whether Skill Mill employed youth are more likely to desist from offending than a control group of youth who are not employed in the Skill Mill. Those youths employed by the Skill Mill committed 1.12 fewer offences per quarter than the control group (p < 0.001). In addition, offending rates among the Skill Mill youths decreased by 0.99 offences per quarter after they began work (p < 0.001). Next, we review results from semi-structured interviews with current Skill Mill employees and their supervisor that helps to unpack why the Skill Mill has been successful in promoting desistance. We conclude that programmes like the Skill Mill can mark an important turning point, and more specifically, a hook for change in the lives of young offenders.

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)0.004
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.000
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 head0.138
GPT teacher head0.424
Teacher spread0.286 · 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