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Record W4412426982 · doi:10.1177/10522263251356445

Employing Strength: A Scoping Review of Customized Employment Practices to Support Inclusive Employment for People with Intellectual Disabilities

2025· review· en· W4412426982 on OpenAlex
Jennifer Christianson‐Barker, Alex Franzius, Rachel A. Mills, Arielle Lomness, Rachelle Hole

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Vocational Rehabilitation · 2025
Typereview
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusCanadian Institute for Health InformationUniversity of British Columbia
Fundersnot available
KeywordsCINAHLPsycINFOIntellectual disabilityScopusSupported employmentPsychologyMEDLINEUnemploymentWeb of sciencePublic relationsBusinessApplied psychologyPolitical scienceEconomic growthEconomicsPsychiatryPsychological interventionEngineering

Abstract

fetched live from OpenAlex

Background Inclusive employment offers advantages for both employers and individuals with intellectual disabilities. However, high unemployment rates persist for people with intellectual disabilities, underscoring the need for alternative approaches. Customized employment (CE) has emerged as a promising strategy by tailoring job opportunities to align with individual strengths and employer requirements. Objective This review answers the question, “What does the literature say about the use of customized employment practices to facilitate paid employment for people with intellectual disabilities?” Methods We conducted a scoping review of the literature. Eight databases were searched, including APA PsycInfo, Medline, CINAHL, Scopus, Web of Science, Business Source Ultimate, Social Services Abstracts and Social Science Abstracts. Results Fifty-seven articles were deemed relevant to the research question, revealing clear trends and key characteristics of CE. The literature suggests that CE can lead to improved employment outcomes, greater self-determination and independence, and increased employer satisfaction. However, lack of evaluative measures has led to inconsistencies in delivery and quality of support. CE practices may demand more time and higher costs compared to other types of supported employment. Conclusions When implemented effectively, CE practices can be a valuable method for supporting individuals with intellectual disabilities in securing inclusive employment.

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.

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)0.006
metaresearch head score (Gemma)0.100
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.536
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.100
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.082
GPT teacher head0.486
Teacher spread0.404 · 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