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Record W4382023455 · doi:10.3389/fresc.2023.1175531

Challenging power and unearned privilege in physiotherapy: lessons from Africa

2023· article· en· W4382023455 on OpenAlexaff
Stephanie Lurch, Saul Cobbing, Verusia Chetty, Stacy Maddocks

Bibliographic record

VenueFrontiers in Rehabilitation Sciences · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsSt. Paul's HospitalUniversity of British ColumbiaUniversity Health NetworkMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsPrivilege (computing)SolidarityRehabilitationPower (physics)GlobeHealth careWhite privilegeMainstreamCurriculumDiversity (politics)SociologyPublic relationsMedical educationPolitical scienceMedicineNursingEngineering ethicsPedagogyGender studiesLawEngineeringPhysical therapyRacismPolitics

Abstract

fetched live from OpenAlex

Power and unearned privilege in the profession of physiotherapy (PT) reside in the white, Western, English-speaking world. Globally, rehabilitation curricula and practices are derived primarily from European epistemologies. African philosophies, thinkers, writers and ways of healing are not practiced widely in healthcare throughout the globe. In this invited perspectives paper, we discuss the philosophies of Ubuntu and Seriti, and describe how these ways of thinking, knowing, and being challenge Western biomedical approaches to healthcare. We believe implementing these philosophies in the West will assist patients in attaining the health outcomes they seek. Further we call for Western professionals and researchers to stand in solidarity with their African counterparts in order to move towards a diversity of practitioners and practices that help to ensure better outcomes for all.

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)0.009
metaresearch head score (Gemma)0.009
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 score0.011
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.018
Scholarly communication0.0070.010
Open science0.0010.011
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.000

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 head0.044
GPT teacher head0.386
Teacher spread0.341 · 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
Published2023
Admission routes1
Has abstractyes

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