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Record W4282581837 · doi:10.1097/ans.0000000000000428

Access Denied

2022· article· en· W4282581837 on OpenAlexaffabout
Tara C. Horrill, Donna Martin, Josée G. Lavoie, Annette Schultz

Bibliographic record

VenueAdvances in Nursing Science · 2022
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of ManitobaResearch ManitobaUniversity of British ColumbiaManitoba Health
Fundersnot available
KeywordsMEDLINEMedicineInternet privacyMedical emergencyComputer sciencePolitical scienceLaw

Abstract

fetched live from OpenAlex

Inequitable access to oncology care is a significant issue among Indigenous Peoples in Canada; however, the perspectives of oncology nurses have not been explored. Guided by an interpretive descriptive methodology, we explored nurses' perspectives on access to oncology care among Indigenous Peoples in Canada. Nurses described the health care system as "broken" and barriers to accessing oncology care as layered and compounding. Lack of culturally safe care was articulated as a significant issue impacting equitable access, while biomedical discourses were pervasive and competed with nurses' attempts at providing culturally safe and trauma- and violence-informed care by discounting the relational work of nurses.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.452
Teacher spread0.428 · 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 designObservational
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

Citations9
Published2022
Admission routes2
Has abstractyes

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