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Arthritis-Related Occupational Therapy: Making Invisible Ruling Relations Visible Using Institutional Ethnography

2012· article· en· W2029320963 on OpenAlexaff
Birgit Prodinger, Lynn Shaw, Debbie Laliberté Rudman, Elizabeth Townsend

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2012
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of Prince Edward IslandDalhousie UniversityWestern University
Fundersnot available
KeywordsOccupational therapyPositivismEthnographyHealth careEveryday lifePower (physics)MedicineSociologyMedical educationPublic relationsNursingPsychologyPhysical therapyEpistemologyPolitical science

Abstract

fetched live from OpenAlex

Introduction: Occupational therapists' intention of enabling women with rheumatoid arthritis to participate in everyday life is fraught with challenges in everyday practice. Method: Inspired by institutional ethnography, this paper aims to make explicit how the work of occupational therapists in an outpatient rheumatology hospital setting is governed within invisible, ruling relations. An analytical description of the first author's clinical experience was a standpoint from which to explicate how occupational therapy is coordinated to the ruling relations of the Austrian health care system. Findings: Occupational therapy practice and research are ruled within a positivist, body-focused, medical apparatus, which renders largely invisible occupational therapists' knowledge of enabling people to engage in occupations that are meaningful to them. Conclusion: Occupational therapists have professional power that can be asserted by strategically using occupational therapy specific knowledge and language in textually mediated practices, from assessments and case files to media images, to give greater visibility and influence to the profession's work of enabling occupation.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.324
GPT teacher head0.506
Teacher spread0.183 · 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 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

Citations12
Published2012
Admission routes1
Has abstractyes

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