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Record W2507447101 · doi:10.1177/1539449216665117

Ethical Tensions Related to Systemic Constraints

2016· article· en· W2507447101 on OpenAlexaffabout
Evelyne Durocher, Elizabeth Anne Kinsella, Lisa McCorquodale, Shanon Phelan

Bibliographic record

VenueOTJR Occupational Therapy Journal of Research · 2016
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsUniversity of AlbertaFanshawe CollegeWestern University
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

Ethical tensions arise daily in health care practice and are frequently related to health care system structures or policies. Collective case study methodology was adopted to examine ethical tensions reported by occupational therapists practicing in different settings in Southwestern Ontario, Canada. Inductive analysis involving multiple layers of coding was conducted. This article focuses on tensions related to systemic constraints. Participants reported ethical tensions related to balancing client priorities with those of health care services. Four themes related to systemic constraints were identified including imposed practices, ineffective processes, resource limitations, and lack of services. Therapists' aims could be seen to align with an "ethic of care" and were seen to be in tension in light of systemic constraints. The findings raise issues related to occupational justice, particularly related to occupational alienation in occupational therapy practice, and open conversations related to neoliberalist health care agendas.

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)0.112
metaresearch head score (Gemma)0.148
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.593

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1120.148
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0180.056
Scholarly communication0.0120.008
Open science0.0020.016
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0020.000

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 head0.378
GPT teacher head0.611
Teacher spread0.233 · 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

Citations44
Published2016
Admission routes2
Has abstractyes

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