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Record W1998273839 · doi:10.1300/j076v31n01_11

Need Structure, Leisure Motivation, and Psychosocial Adjustment Among Young Offenders and High School Students

2000· article· en· W1998273839 on OpenAlexaff
Katherine B. Starzyk, John R. Reddon, Jon Friel

Bibliographic record

VenueJournal of Offender Rehabilitation · 2000
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsAlberta Hospital EdmontonQueen's University
Fundersnot available
KeywordsPsychosocialPsychologyPersonalityClinical psychologyScale (ratio)AggressionHarmDepression (economics)AutonomyDevelopmental psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

The Personality Research Form-E (PRF-E; 20 need structure scales), the Holden Psychological Screening Inventory (HPSI; 3 psychosocial adjustment scales), and the Leisure Motivation Scale (LMS; 4 leisure motivation scales) were administered to 60 young offenders and 50 high school students. Significant between sample differences in means resulted for the HPSI Psychiatric, Social, and Depression Symptomatology scales; the PRF-E Affiliation, Aggression, Autonomy, and Harm Avoidance content scales; and the LMS Social scale. Statistically significant correlations resulted between the LMS and 19 of the 20 PRF-E content scales as well as the HPSI Depression and Social Symptomatology scales. It is concluded that young offenders, as compared to high school students, are significantly less well adjusted and have different leisure motivations and personality needs. It is likely that need structure impacts directly on psychosocial adjustment as well as indirectly through leisure motivation.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.013
GPT teacher head0.287
Teacher spread0.274 · 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

Citations12
Published2000
Admission routes1
Has abstractyes

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