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Record W6926486910 · doi:10.25384/sage.c.5368304

Predictive Properties of a General Risk-Need Measure in Diverse Justice Involved Youth: A Prospective Field Validity Study

2021· other· en· W6926486910 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2021
Typeother
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRecidivismPredictive validitySalience (neuroscience)Sample (material)Risk assessmentEconomic JusticeConstruct validityMeasure (data warehouse)Test validity

Abstract

fetched live from OpenAlex

The current investigation was a prospective field validity study examining the discrimination and calibration properties of a general risk-need tool (Level of Service Inventory–Saskatchewan Youth Edition [LSI-Sk]) in a diverse sample of 284 court adjudicated youths, rated by their youth workers on the measure and followed up an average of 9.3 years. The overall risk level and need total demonstrated moderate predictive accuracy for general, violent, and nonviolent recidivism in the aggregate sample, although area under the curve (AUC) magnitudes fluctuated among gender and Indigenous ethnocultural subgroups. Variability in AUC values for the measure’s eight criminogenic need domains further reflected greater salience of certain needs among subgroups. Finally, clinician rated level of gang involvement incrementally predicted recidivism to varying degrees after controlling for overall risk and need. Implications for responsible use of risk assessment tools as part of individualized and gender/ethnoculturally responsive risk assessment practices with youth are discussed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.688
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.223
GPT teacher head0.281
Teacher spread0.058 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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