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Record W4284677348 · doi:10.1136/bmjopen-2021-055452

Inclusion of young people with disabilities in the future of work: forecasting workplace, labour market and community-based strategies through an online and accessible Delphi survey protocol

2022· article· en· W4284677348 on OpenAlexafffundabout
Arif Jetha, Kay Nasir, Dwayne Van Eerd, Monique A. M. Gignac, Kathleen A. Martin Ginis, Emile Tompa

Bibliographic record

VenueBMJ Open · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsMcMaster UniversityUniversity of British Columbia, Okanagan CampusPublic Health OntarioInternational Collaboration On Repair DiscoveriesUniversity of British ColumbiaInstitute for Work & HealthUniversity of Toronto
FundersEmployment and Social Development CanadaArthritis SocietyGovernment of Canada
KeywordsDelphi methodInclusion (mineral)Work (physics)MedicineDelphiProtocol (science)Public relationsIndependent livingService providerService (business)Medical educationGerontologyMarketingPsychologyBusinessPolitical scienceAlternative medicineComputer scienceSocial psychologyEngineering

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.009
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.564
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.206
GPT teacher head0.455
Teacher spread0.248 · 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 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

Citations8
Published2022
Admission routes3
Has abstractyes

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