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Record W2067545714 · doi:10.1080/13691058.2015.1009170

‘Women are supposed to be the leaders’: intersections of gender, race and colonisation in HIV prevention with Indigenous young people

2015· article· en· W2067545714 on OpenAlexafffundabout
Vanessa Oliver, Sarah Flicker, Jessica Danforth, Erin Konsmo, Ciann Wilson, Randy Jackson, Jean‐Paul Restoule, Tracey Prentice, June Larkin, Claudia Mitchell

Bibliographic record

VenueCulture Health & Sexuality · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsMcGill UniversityWomen's and Gender Studies et Recherches FéministesUniversity of OttawaYork UniversityNative Youth Sexual Health NetworkUniversity of TorontoMcMaster University
FundersCanadian Institutes of Health Research
KeywordsIndigenousGender studiesOppressionColonialismRace (biology)ColonisationResistance (ecology)SociologyHuman sexualityPolitical scienceHistoryEcology

Abstract

fetched live from OpenAlex

Focusing on gender, race and colonialism, this paper foregrounds the voices of Indigenous young people, their histories of oppression, their legacies of resistance and the continuing strengths rooted in Indigenous peoples, their cultures and their communities. Exploring the relationship between gender and colonialism, the paper speaks to the lived realities of young people from Indigenous communities across Canada. Over 85 young people participated in six different Indigenous community workshops to create artistic pieces that explored the connections between HIV, individual risk and structural inequalities. In the course of the research, Indigenous young people, and young Indigenous women in particular, talked about how gender intersects with race and colonisation to create experiences that are, at times, especially difficult for them. In this paper, young people discuss the ways in which colonialism has demeaned women's roles and degraded women's sexuality, and how continuing cultural erasure and assimilationist policies impact on their lives and on their bodies.

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)0.003
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 score0.826
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.085
GPT teacher head0.377
Teacher spread0.292 · 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
Published2015
Admission routes3
Has abstractyes

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