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Record W1550204453 · doi:10.1177/117718011501100206

It's in Our Blood: Indigenous women's knowledge as a critical path to women's well-being

2015· article· en· W1550204453 on OpenAlexaff
Janice Cindy Gaudet, Diane Caron-Bourbonnais

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsIndigenousRigourExperiential knowledgeParticipatory action researchMedicalizationSociologyGender studiesCommunity-based participatory researchTraditional knowledgeExperiential learningInstitutionalisationPower (physics)PsychologyAnthropologyPedagogyEpistemology

Abstract

fetched live from OpenAlex

The research reported in this article sought to shed light on the North, Central and South American indigenous moon time teachings related to the menstrual cycle of women. The historical institutionalization, medicalization and colonization of indigenous women's practices have devalued and almost destroyed this knowledge. This study explored the question of whether or not lost indigenous knowledge of women's power can be reclaimed for women's health and well-being. A qualitative participatory research methodology was adopted, based on an indigenous paradigm and scholarly rigour and including protocols acceptable to an Ojibwe grandmother, Isabelle Meawasige, who shared her knowledge and experience. The experiential knowledge gained and the meanings expressed by female participants in a circle sharing facilitated by the principal author are presented and discussed. The results of this research reveal optimistic possibilities to co-create health and well-being for the participants, grounded in what is both visible and invisible within indigenous women's culture.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science 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 score0.277
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.366
Teacher spread0.345 · 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

Citations8
Published2015
Admission routes1
Has abstractyes

Explore more

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