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Choice‐Making in Vocational Activities Planning: Recommendations from Job Coaches

2010· article· en· W2096494479 on OpenAlexaff
Virginie Cobigo, Yves Lachapelle, Diane Morin

Bibliographic record

VenueJournal of Policy and Practice in Intellectual Disabilities · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec à Trois-RivièresQueen's University
FundersDen Sociale Fond
KeywordsVocational educationPsychologyProcess (computing)Action (physics)Service (business)Intellectual disabilityApplied psychologyMedical educationMarketingPedagogyBusinessMedicineComputer science

Abstract

fetched live from OpenAlex

Abstract Choice in the job seeking process may lead to increased satisfaction with the chosen job, and improve attention, performance, and motivation. Consequently, providing opportunities to express choices and interests while planning vocational activities is a key factor in achieving employment outcomes. Despite their commitment to promoting choice‐making, service providers encounter important barriers to understanding the vocational interests of persons with intellectual disabilities who may have difficulty expressing their choices verbally. Methods of recording choices expressed through nonverbal means of communication are therefore needed. Such a method was designed and field‐tested. Interviews were conducted with participating job coaches to assess its practical value and provide recommendations pertinent to its implementation and dissemination. This step is crucial to the knowledge‐to‐action process since it tailors research findings to make them meaningful to daily practice. The authors present results relevant to improving choice‐making opportunities in the job seeking and planning process of persons with intellectual disabilities. The results demonstrate the need for training to enable support staff to embed choice‐making opportunities in the daily life of persons with intellectual disabilities.

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)0.002
metaresearch head score (Gemma)0.250
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.250
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.123
GPT teacher head0.463
Teacher spread0.340 · 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.

Study designQualitative
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

Citations8
Published2010
Admission routes1
Has abstractyes

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