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Record W2460956744 · doi:10.1177/1043659616659348

Urban First Nations Men: Narratives of Positive Identity and Implications for Culturally Safe Care

2016· article· en· W2460956744 on OpenAlexaffabout
Celina Carter, Jennifer Lapum, Lynn F Lavallée, Lori Schindel Martin, Jean‐Paul Restoule

Bibliographic record

VenueJournal of Transcultural Nursing · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsIdentity (music)NarrativeReflexivityGender studiesColonialismSymbol (formal)Cultural safetyNursingPsychologySociologyMedicineHealth carePolitical scienceAnthropology

Abstract

fetched live from OpenAlex

PURPOSE: Dominant discourse contains negative stereotypical images of First Nations males that are steeped in colonialism. These racialized images can influence First Nations men's sense of self as well as the care that nurses deliver. The objective was to (a) explore practices that support positive First Nations identity and (b) provide suggestions for practicing culturally safe care. DESIGN: The theory of Two-Eyed Seeing guided this study. Data were collected via two semistructured interviews and Anishnaabe Symbol-Based Reflection from three First Nations men living in Toronto, Canada. FINDINGS: Having mentors, knowing family histories, and connecting with healthy Aboriginal communities fostered positive First Nations identities for participants. IMPLICATIONS: There is potential to advance nursing practice by enacting creative means that may support client's positive First Nations identity and well-being. Nursing education that focuses on strength-based and decolonizing frameworks, as well as reflexive practices that promote culturally safe care, is needed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
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 head0.018
GPT teacher head0.347
Teacher spread0.329 · 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.

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

Citations23
Published2016
Admission routes2
Has abstractyes

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