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Record W2282852760 · doi:10.26443/ijwpc.v1i1.51

Using Popular Nursing Literature Critique to Help Nursing Students Explore Their Perceptions of Disability

2014· article· en· W2282852760 on OpenAlexaffvenue
Charles Anyinam, Sue Coffey

Bibliographic record

VenueInternational Journal of Whole Person Care · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsOntario Tech UniversityGeorge Brown College
Fundersnot available
KeywordsDisadvantagePerceptionNursingCurriculumPsychologyHealth careLearning disabilityAffect (linguistics)IndividualismMedicineMedical educationPedagogyDevelopmental psychology

Abstract

fetched live from OpenAlex

Objectives: Disabled people have a history of disadvantage, discrimination, and disempowerment that continues to present day. Despite strong critique and activism by disabled people, popular understandings of disability as necessarily tragic, medically based, and individualistic requiring ‘fixing’ persist among health professionals. Recent research demonstrates that health professional students often harbour negative attitudes that may directly affect their relationships with and care provided to disabled clients (Sabin & Akyol, 2010; Scullion, 1999). Further, personal accounts and research evidence suggests that the relationship between healthcare providers and disabled people is often unsatisfactory (Sabin & Akyol, 2010; Seccombe, 2007; Scullion, 1999).Methods: Nursing education has a responsibility to ensure that nursing practice with disabled people is enabling rather than disabling (Scullion, 1999a, 1999b, 2000; Sabin & Akyol, 2010). A key strategy is to imbed within curricula opportunities for students to engage in the processes of critical thinking towards and analysis of disability and the experiences of disabled people. This poster describes an approach to teaching-learning in which critique of ‘popular culture’ nursing literature is used to support student exploration of messaging about disability.Results and Conclusions: The purpose and description of the assignment, authors’ experiences, and outcomes for both teachers and learners will be presented. Application beyond nursing to other health professions will be described.ReferencesSabin, H. & Akyol, A. D. (2010). Evaluation of nursing and medical students' attitudes towards people with disabilities. Journal of Clinical Nursing, 19, 2271­2279.Scullion, P. A. (1999). Conceptualizing disability in nursing: Some evidence from students and their teachers. Journal of Advanced Nursing, 29, 648­657.Scullion, P. A. (2000). Enabling disabled people: Responsibilities of nursing education. British Journal of Nursing, 9(15), 1010-1015.Seccombe, J. A. (2007). Attitudes towards disability in an undergraduate nursing curriculum: A literature review. Nurse Education Today, 27, 459­465.

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)0.023
metaresearch head score (Gemma)0.055
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 score0.023
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.055
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0090.010
Scholarly communication0.0100.008
Open science0.0020.012
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0070.002

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 head0.052
GPT teacher head0.448
Teacher spread0.397 · 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".

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Citations0
Published2014
Admission routes2
Has abstractyes

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