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Record W1578424762

An Analysis of Young Offender Case Management Factor Items in Saskatchewan

2012· dissertation· en· W1578424762 on OpenAlexfundaboutno aff
Melinda Lee Baum

Bibliographic record

VenueoURspace (University of Regina) · 2012
Typedissertation
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsnot available
FundersFaculty of Graduate Studies and Research, University of AlbertaCanadian Institutes of Health Research
KeywordsRecidivismResponsivityContext (archaeology)PsychologySample (material)Library scienceEngineeringComputer scienceClinical psychologyGeography
DOInot available

Abstract

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The Level of Service Inventory Saskatchewan Youth Ed. (LSI SK Youth Ed.) is a risk assessment tool designed to be used with young offenders to determine the level of service necessary to reduce offending and inform case planning. There are eight vulnerable areas known to be criminogenic identified in the assessment that inform key areas for intervention and treatment in each offender’s case plan. The assessment also appends three sections of supplementary information (case management factor items) that might assist or affect case planning in the eight areas. The three sections consist of: 1) attributes or personal characteristics of the offender, such as anger management deficits or poor social skills; 2) static items that may play a prominent role in case management such as a history of fire-setting or gang involvement; and 3) social, economic and health issues such as homelessness or depression. The case management factors might indicate additional psychological or psychiatric assessment for the offender, or alert case managers of potential safety precautions for the young person (i.e. history of suicide attempts) or for those working with the offender (i.e. violence). Minimally, case management factors are an indication of the need to adapt or supplement treatment strategies and/or programming determined by the risk/need areas identified in the assessment. The case management factors are the subject of this research. Forty-two supplementary case management factors in the three subset categories of the risk assessment tool (LSI SK Youth Ed.) were analyzed. These variables were identified from 540 risk assessments of young offenders in Saskatchewan. The validity of the assessment tool was first established by finding a statistically significant relationship between recidivism and risk level. Results suggest that the risk assessment tool is a valid tool to measure the likelihood of recidivism in young offenders. Next forty-two case management factors were surveyed for frequency to see how often the factor occurs in the young offender sample (range) to assist justice agencies by identifying the ‘macro-needs’ of a young offender group in terms of program or intervention services. The scope or depth of the factors was tested for association to recidivism and risk level placement. Results determined that ten of those 42 factors were statistically significant in relation to recidivism and are considered criminogenic. Twenty-five of the case management factors had a statistically significant relationship to risk level placement. Ten of the 25 factors associated with risk level placement were those associated with recidivism. Those ten factors are more criminogenic than the remaining 15 of the twenty five factors associated with risk level placement because recidivism is actually re-offending and risk level placement is a prediction of re-offending. Nevertheless, statistically significant associations for the 15 factors associated with risk level placement that were not also associated with recidivism are criminogenic (though less so than associations to recidivism). Variables not associated to either recidivism or risk level placement, might be considered a non-criminogenic need, and would still be important considerations in a case plan and would require multi-agency intervention. This is the first study of its kind to discover the range and scope of case management factors. Further research is needed to corroborate findings and to understand how programs can be individualized, and then to study the effectiveness those interventions and programs.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.143
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.007
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.019
GPT teacher head0.281
Teacher spread0.262 · 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

Citations0
Published2012
Admission routes2
Has abstractyes

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