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Record W4388941462 · doi:10.3389/fresc.2023.1334054

Editorial: Equity, diversity, and inclusion in rehabilitation sciences

2023· editorial· en· W4388941462 on OpenAlexaff
Adria Quigley, Hellen Myezwa, Caitlin McArthur

Bibliographic record

VenueFrontiers in Rehabilitation Sciences · 2023
Typeeditorial
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsNova Scotia Health AuthorityDalhousie University
Fundersnot available
KeywordsEquity (law)Inclusion (mineral)Diversity (politics)RehabilitationSociologyPolitical scienceSocial scienceMedicineAnthropologyPhysical therapy

Abstract

fetched live from OpenAlex

Editorial on the Research Topic Equity, diversity, and inclusion in rehabilitation sciencesEquity, Diversity, and Inclusion have become critical issues in the field of rehabilitation sciences (1).Like many other professions, physiotherapists, occupational therapists and other rehabilitation providers are reckoning with the ongoing impacts of colonialism, racism, stigmatization, and discrimination that form part of the fabric of our health care systems (2-10).Now, perhaps more than ever, there is a demand for equitable and timely access to rehabilitation.Incorporating principles of equity, diversity, inclusion, and accessibility into education, clinical practice, and research are essential for addressing the unique needs of rehabilitation clients.There is also a call to integrate anti-oppressive and anti-racist frameworks into rehabilitation care.Strategies that promote accessible and affordable participation, health promotion, technology, and interdisciplinary collaboration in rehabilitation are needed.Intersectionality is a concept that highlights how various aspects of an individual's identity (such as race, gender, sexuality, class and disability) can intersect and interact to create unique experiences of discrimination, advantage or disadvantage, or privilege (11).Within the context of rehabilitation science, we need to understand these concepts and illuminate how to better serve equity-deserving groups.We are pleased to serve as guest associate editors for the Research Topic: Equity, Diversity, and Inclusion in Rehabilitation Sciences.While it is not possible to address all aspects of Equity, Diversity, and Inclusion in one issue, this Research Topic may be thought of as the beginning of the conversation.What is missing from the Research Topic is an examination of the impact of gender, sexual orientation, race and religion, and socioeconomic status on rehabilitation service delivery and outcomes.We hope that this Research Topic will inspire focus on these areas as they pertain to rehabilitation.We are fortunate to have nine articles included in this Research Topic, five of which are original research articles (Jiancaro et al., Sekome et al., Ibáñez-Carrasco et al., Chumo et al., Claus et al.), two are perspective articles (Lurch et al., Dorsey Holliman et al.), and two are brief research reports (Fricke et al., Oancea-Matei et al.). From these nine articles, two main themes emerged. The first theme is the importance of knowledge transfer of Equity, Diversity, and Inclusion principles within the rehabilitation sciences professions. Lurch and colleagues provided an introduction to African philosophies and how these ways of thinking may challenge Western biomedical approaches to health care (Lurch et al.).The authors argue that the default physiotherapy identity, curricula, and practices are derived from Western epistemologies which have devalued other ways of knowing.Lurch et al. describe

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)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.049
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.036
Meta-epidemiology (narrow)0.0060.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0050.002
Science and technology studies0.0050.003
Scholarly communication0.0100.006
Open science0.0040.002
Research integrity0.0160.016
Insufficient payload (model declined to judge)0.0490.024

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 head0.040
GPT teacher head0.393
Teacher spread0.353 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations4
Published2023
Admission routes1
Has abstractyes

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