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Record W4291019234 · doi:10.3928/01484834-20220602-04

Reiterating a Need for Antiracism Praxis in Nursing and Psychiatric Nursing Education

2022· article· en· W4291019234 on OpenAlexaffabout
Candice Waddell-Henowitch, Madeleine Kruth, Heather M. Stephen

Bibliographic record

VenueJournal of Nursing Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Competency in Health Care
Canadian institutionsBrandon University
Fundersnot available
KeywordsPraxisRacismPrivilege (computing)Nurse educationNursingWhite privilegeNursing researchNursing careTeam nursingQualitative researchMedicinePsychologySociologyPolitical scienceGender studies

Abstract

fetched live from OpenAlex

Background: The reemergence of the Black Lives Matter movement in 2020 reinforced the need for antiracist and decolonizing praxis in all areas, including nursing education, the burden for which has fallen predominantly on visible minorities. To enact the needed change within health care systems and nursing education, White nurses must recognize their privilege and become active participants in the conversations and change. Method: This two-phase qualitative study explored nursing and psychiatric nursing students' experiences of racism and antiracism education at a small western Canadian university. Results: Anonymous qualitative surveys ( n = 24) and structured interviews ( n = 9) with nursing and psychiatric nursing students highlighted the difficulties and complexities of recognizing racism and a present lack of antiracism praxis in educational and health care settings. Conclusion: Nursing educators must reevaluate structural and behavioral aspects of nursing education to support genuine antiracism praxis. [ J Nurs Educ . 2022;61(8):439–446.]

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.946

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.443
Teacher spread0.403 · 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.

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
Published2022
Admission routes2
Has abstractyes

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