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Record W4410475285 · doi:10.1080/13218719.2025.2470621

Evaluating the role of strengths and protective factors for youth with FASD and criminal legal system involvement: a scoping review

2025· review· en· W4410475285 on OpenAlexafffund
Chantel Ritter, Kaitlyn McLachlan, Muhammad Usman Anwar Baig, Meghan McMurtry, Margaret N. Lumley

Bibliographic record

VenuePsychiatry Psychology and Law · 2025
Typereview
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsMcMaster Children's HospitalUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyApplied psychologySocial psychologyCriminology

Abstract

fetched live from OpenAlex

Youth with fetal alcohol spectrum disorder (FASD) are overrepresented in the criminal legal system (CLS). There is greater recognition among scholars, policymakers, and professionals of the importance of strengths-based approaches for this population. The current scoping review (preregistered on the Center for Open Science; DOI: 10.17605/OSF.IO/6WAZE) aimed to determine what strengths and protective factors have been investigated for youth with FASD in the CLS, and how these have been identified, defined, and measured. Results identified an emerging body of literature of 16 peer reviewed articles. Strengths were often nested within deficit-based conversations and included individual (e.g. kindness), relational (e.g. caregiver support), and broader contextual level strengths (e.g. early diagnosis). To foster consistency, understanding, and better support this group, future research should purposefully incorporate strengths and protective factors into research and intervention frameworks and improve conceptual clarity when describing strengths and protective factors in this population.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.306
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.050
GPT teacher head0.408
Teacher spread0.358 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes2
Has abstractyes

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