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Record W4401056664 · doi:10.1016/j.outlook.2024.102228

“In the end, we had to leave”: Truth-telling to unsettle whiteness in nursing academia

2024· article· en· W4401056664 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Outlook · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsFraser HealthBrandon University
Fundersnot available
KeywordsNursingPsychologySociologyMedicine

Abstract

fetched live from OpenAlex

Nursing is renowned for its high ethical standards and is considered one of the most trusted professions globally, yet it has deep historical ties to Eurocentric and white supremacist ideologies. These entrenched ideologies in nursing raise significant concerns regarding equity, diversity, and inclusion within the profession as they shape nursing education, research, and practice. Western nursing institutions are deeply engrained in a system designed to center and uphold whiteness, which frequently serves to safeguard dominant groups in power while detrimentally affecting faculty from underrepresented backgrounds. Consequently, faculty members from underrepresented groups depart academia due to systemic racism and inadequate institutional accountability and support. To decenter whiteness in nursing, we have shared our experiences to underscore how systems of oppression marginalize underrepresented faculty in nursing academia.

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.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.637
Threshold uncertainty score0.860

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.058
GPT teacher head0.466
Teacher spread0.408 · 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