Changing GEARS: Development and Validation of Gendered Emerging-Adult Rehabilitative Strengths Measures
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,027 | 0,051 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».