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Record W2800879653 · doi:10.1007/s10926-018-9770-1

Acceptability and Feasibility of a Shared Decision-Making Model in Work Rehabilitation: A Mixed-Methods Study of Stakeholders’ Perspectives

2018· article· en· W2800879653 on OpenAlexafffund
Marie‐France Coutu, France Légaré, Marie‐José Durand, Dawn Stacey, Marie-Élise Labrecque, Marc Corbière, Lesley Bainbridge

Bibliographic record

VenueJournal of Occupational Rehabilitation · 2018
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of British ColumbiaInstitut universitaire en santé mentale de MontréalInstitut Universitaire en Santé Mentale de QuébecUniversity of OttawaHôpital Saint-François d'AssiseOttawa HospitalHôpital Charles-Le MoyneUniversité du Québec à MontréalUniversité de Sherbrooke
FundersFonds de Recherche du Québec - SantéInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsStakeholderRehabilitationFocus groupThematic analysisHealth psychologyWork (physics)Process managementProcess (computing)Applied psychologyPsychologyQualitative researchBusinessMedicineComputer scienceNursingEngineeringPublic relationsPublic healthMarketingPhysical therapyPolitical science

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.210
metaresearch head score (Gemma)0.255
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.974

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2100.255
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0080.007
Scholarly communication0.0110.007
Open science0.0030.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.141
GPT teacher head0.523
Teacher spread0.382 · 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.

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

Citations11
Published2018
Admission routes2
Has abstractno

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