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Microenterprise Options for People With Intellectual and Developmental Disabilities: An Outcome Evaluation

2010· article· en· W2171317542 on OpenAlexaboutno aff
James W. Conroy, C. Ferris, Ron Irvine

Bibliographic record

VenueJournal of Policy and Practice in Intellectual Disabilities · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Scale (ratio)Quality of life (healthcare)Work (physics)PsychologyIntellectual disabilityGerontologyQuality (philosophy)Point (geometry)MedicineGeographyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Opportunities for community employment of people with intellectual and developmental disabilities are limited, and have not improved over the past quarter century of interest and effort. This report provides the findings from an outcome study of this issue. Twenty‐seven people with intellectual and developmental disability, residents in Kent County, Michigan, USA, chose to engage in microenterprise and became the basis of this study. We measured changes in the qualities and quantities of work life. Participants reported enhanced quality of work life in most of the 17 areas. Their overall “scale score” significantly increased by 26 points on a 100‐point scale. The support workers' data revealed significantly enhanced quality of work life in 5 of 14 areas, and their overall scale increase of 6 points approached statistical significance. Preliminary findings are regarded as encouraging, particularly because statistics on competitive and supported employment have not improved in 25 years. Microenterprise offers an alternative that promises to be satisfying, meaningful, enjoyable, and may cost significantly less to implement than traditional sheltered workshops and adult day activity centers.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.090
GPT teacher head0.437
Teacher spread0.347 · 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

Citations33
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Policy and Practice in Intellectual DisabilitiesSame topicDisability Education and EmploymentFrench-language works237,207