Changing GEARS: Development and Validation of Gendered Emerging-Adult Rehabilitative Strengths Measures
Bibliographic record
Abstract
There are currently no self-report strength measures designed for justice-involved (JI), emergingadult (EA) men and women.This dissertation is part of a proposed program of research to attain that goal, and contribute to current fundamental work on gendered research and strengths in a correctional context.Study 1 involved meta-analytic review of studies measuring strengths in relation to offending outcomes, using samples of justice-involved clients disaggregated by gender.Eligible studies (k = 19) involving gender-disaggregated samples of justice-involved women (aggregate n = 1,699, 54.4% adolescents) and men (aggregate n = 6,556, 72.4% adolescents) were collected.From the final study set, 32 strengths were assessed in men and boys, 18 (56%) of which were significantly related to desistance.Comparatively, of 16 strengths assessed in women or girls, 10 (63%) were related to desistance.Strengths with the largest effects were 'Network' and 'Mental health' for women, and 'Motivation' and 'Regulation' for men.In Study 2, forensic professionals (N = 25) rated the ability of strengths from Study 1 to predict desistance for justice-involved men and women, and suggested additional items that were not included.Of the 37 strength items proposed to professionals, 10 items were rated as probably having predictive utility toward desistance for JI women and men.'Cognitive regulation' showed gender-salience in men, whereas 'Emotional support' and 'Dependent children' showed gendersalience in women.Strengths from Study 1 and suggested by professionals in Study 2 constituted an item pool for Study 3.This pilot study used methods of criterion and construct validity to form gendered measures for emerging-adult men and women.Three-factor, 16-item measures were derived for men and women, respectively, each demonstrating strong psychometric properties. GENDERED STRENGTHS FOR JUSTICE-INVOLVED POPULATIONS Baglole xvGlossary CNV: Criminal, non-violent behaviour, as assessed by item in the Antisocial Behaviours Scale (ABS). CV: Criminal, violent behaviour, as assessed by item in the Antisocial Behaviours Scale (ABS).Desistance: An ongoing process of intent and action toward cessation from offending.Emerging adults (EAs): Refers to young adults, specifically those within the age range from 18 to 25 years old.External factor: Variables, such as strengths, that derive from outside the self; examples include parental warmth and instrumental support. Gender-neutral:In forensic assessment, variables, such as strengths, that have predictive utility (i.e., are empirically related to desistance) in both genders equally.Gender-responsive: Umbrella term for gender-salient and -specific variables. Gender-salient:In forensic assessment, variables, such as strengths, that have predictive utility in both genders, yet higher utility (i.e., has a stronger statistical relationship with desistance) in one gender versus another. Gender-specific:In forensic assessment, variables, such as strengths, that have predictive utility (i.e., are empirically related to desistance) in one gender only. Interaction model theory:The idea that strengths should be conceived as discrete from risks, offering unique information.Strengths here can co-exist with risks and even interact in predictions of recidivism or desistance likelihood.Internal factor: Variables, such as strengths, that derive from inside the self; examples include self-esteem and cognitive regulation. GENDERED STRENGTHS FOR JUSTICE-INVOLVED POPULATIONS Baglole xviJustice-involved/ justice-involved clients (JI/JICs): Individuals who have encountered the justice system through previous charges, convictions, and detainment. NAB: No antisocial behaviour, as assessed by items on the Antisocial Behaviours Scale (ABS). NCA: Non-criminal antisociality, as assessed by items on the Antisocial Behaviours Scale (ABS).Opposite poles theory: The idea that strengths are operationalized as merely the opposite (absence or inverse) of pre-existing risk factors, and so do not add any additional information during forensic risk assessment.Promotive factor: Variables with direct effect on outcome; reduces likelihood of offending.Protective factor: Variables with direct effect on risk, and indirect effect on outcome; reduces effect of specific risk. Quality of life:A state of being, wherein an individual perceives positive experiences and satisfaction in their own life.Recidivism: An event wherein a justice-involved individual engages in further criminal offending.Rehabilitation: A process by which JICs are guided towards desistance outcomes.Resilience: A process of overcoming adverse circumstances and achieving positive outcomes.Risk: An element in one's life that corresponds with an increased likelihood of offending.Strength: An element in one's life that is positive, prosocial and adaptive; in regards to offending outcomes, strengths may promote criminal desistance. Trichotomization model theory:The idea that strengths and risks lie at opposite ends of a continuum with a neutral centre, so that each side buffers against the other; strengths are not superfluous because they differ in valence from risks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".