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Record W2168802880 · doi:10.3109/07380577.2014.921751

Becoming Occupation-Based: A Case Study

2014· article· en· W2168802880 on OpenAlexaboutno aff
Camille Skubik-Peplaski, Dana Howell, Anne Harrison

Bibliographic record

VenueOccupational Therapy In Health Care · 2014
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyPsychological interventionRehabilitationIntervention (counseling)PsychologyStroke (engine)Physical therapyMedicineClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

This descriptive case study illustrates the experiences of a 55-year-old male with a chronic disability resulting from a stroke, living in the community and a clinician's trial using occupation-based interventions predominately in a rehabilitation setting. The participant engaged in occupation-based interventions three times a week for 5 weeks guided by the Canadian Occupational Performance Measure (COPM). Data were collected through semi-structured interviews during the intervention sessions and journal entries made by the therapist. Results suggested occupation-based interventions facilitated a transformation for both the client and the therapist by enhancing the participant's occupational performance and the ability to resume previous roles. The therapist's belief in the power and value of occupation-based practice was reinforced and validated, particularly in the rehabilitation of an individual with chronic stroke.

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0120.005
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.202
GPT teacher head0.551
Teacher spread0.349 · 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 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

Citations6
Published2014
Admission routes1
Has abstractyes

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