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Record W2128274933 · doi:10.5014/ajot.57.1.17

Professional Tensions in Client-Centered Practice: Using Institutional Ethnography to Generate Understanding and Transformation

2003· review· en· W2128274933 on OpenAlexaff
Elizabeth Townsend, Lynn Langille, Debra Ripley

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2003
Typereview
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEthnographySociologyOccupational therapyMental healthContext (archaeology)Public relationsInstitutionParticipant observationEngineering ethicsMedical educationPsychologyMedicineSocial sciencePolitical sciencePsychotherapistPsychiatryAnthropology

Abstract

fetched live from OpenAlex

For almost 20 years, occupational therapists have advocated client-centered practice. Yet client-centered practice is fraught with tensions that arise outside the practice of individual occupational therapists. This paper is guided by two questions: What produces professional tensions in client-centered practice? and What understanding and change might be generated using institutional ethnography? The sociological theory and method of institutional ethnography are described using data from an ongoing investigation of mental health services as a social institution. Illustrated are the research aim, research questions, and institutional analysis that distinguish institutional ethnography from conventional ethnography. Two professional tensions are associated with attempts to fulfill client-centered practice in mental health. One is that of working at cross-purposes with the prevailing hierarchical structure; the other tension is that of being celebrated yet subordinated in the medical and management hierarchies of health services. Although client-centered practice is difficult to do, the authors recommend institutional ethnography as a research approach to generate understanding and transformation of the context and practice of occupational therapy.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.621
GPT teacher head0.606
Teacher spread0.015 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations60
Published2003
Admission routes1
Has abstractyes

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