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Record W2119321222 · doi:10.1177/1049732306297905

Learning From the Grandmothers: Incorporating Indigenous Principles Into Qualitative Research

2007· article· en· W2119321222 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueQualitative Health Research · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIndigenousGeneral partnershipQualitative researchNova scotiaSociologyCompetence (human resources)Context (archaeology)Traditional knowledgeEngineering ethicsMedical educationPsychologyMedicinePolitical scienceSocial scienceSocial psychologyGeographyEngineeringEthnology

Abstract

fetched live from OpenAlex

In this article, the author describes the process she undertook to incorporate Indigenous principles into her doctoral research about the midlife health experiences of elder Aboriginal women in Nova Scotia, Canada. By employing qualitative methods within the context of an Indigenous worldview, she gained knowledge of and developed competence in Aboriginal health research. The emergent partnership among Aboriginal community research facilitators, participating Mi'kmaq women, and the researcher provided many opportunities for the researcher to incorporate the paradigmatic and methodological traditions of Western science and Indigenous cultures. The application of these principles to this study might provide a useful example for other health researchers who are attempting to incorporate diverse methodological principles.

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)0.660
metaresearch head score (Gemma)0.146
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.6600.146
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0190.015
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.009
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 head0.858
GPT teacher head0.756
Teacher spread0.102 · 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