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Record W2540398413

Indigenous Health Research: Theoretical and Methodological Perspectives

2012· article· en· W2540398413 on OpenAlexvenueno aff
Adele Vukic, David Gregory, Ruth Martin‐Misener

Bibliographic record

VenueCanadian Journal of Nursing Research · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousReciprocity (cultural anthropology)Participatory action researchSociologyTraditional knowledgeRelevance (law)Corporate governanceSpace (punctuation)Possession (linguistics)Community-based participatory researchCitizen journalismHonourEnvironmental ethicsEngineering ethicsPolitical sciencePublic relationsSocial scienceLawAnthropologyEngineeringManagementEcology
DOInot available

Abstract

fetched live from OpenAlex

Nurse researchers schooled in Euro-Western traditions are learning the importance of Indigenous knowledge systems and research methodologies. Two-eyed seeing is an example of how Indigenous knowledge systems can influence the conduct of research. Two-eyed seeing and the opening of ethical space for the co-creation of knowledge are in keeping with Aboriginal traditions and honour the blending of Aboriginal and Western understandings of moral governance. The authors explain how community-based participatory research and the principles of ownership, control, access, and possession help to integrate two-eyed seeing and ethical space in shaping nursing research to address health priorities with Aboriginal peoples. These concepts respect diverse Indigenous knowledge systems and methodologies, and, importantly, position them as central to Indigenous research. This stance is consistent with that of scholars who advocate for Indigenous research that supports the principles of respect, relevance, reciprocity, and responsibility.

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)0.111
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.585

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1110.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0110.012
Science and technology studies0.0110.078
Scholarly communication0.0260.016
Open science0.0060.014
Research integrity0.0090.013
Insufficient payload (model declined to judge)0.0030.000

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 head0.437
GPT teacher head0.571
Teacher spread0.134 · 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.

Study designTheoretical or conceptual
DomainMethods
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

Citations29
Published2012
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Nursing ResearchSame topicIndigenous Health, Education, and RightsFrench-language works237,207