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Record W2567100941

Response Papers / Documents de réponse - Coming Together

2013· article· en· W2567100941 on OpenAlexvenueno aff
Natalie Clark, Patrick Walton, Julie Drolet, Tara Tribute, Georgia Jules, Talicia Main, Mike Arnouse

Bibliographic record

VenueCanadian Journal of Nursing Research · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsParticipatory action researchIndigenousNarrativeSociologyCitizen journalismFocus groupAction researchExploratory researchPsychologyPedagogyPolitical scienceSocial scienceAnthropology
DOInot available

Abstract

fetched live from OpenAlex

The goal of this exploratory community-based participatory action research project was twofold: to determine how urban Aboriginal youth identify their health needs within a culturally centred model of health and wellness, and to create new knowledge and research capacity by and with urban Aboriginal youth and urban Aboriginal health-care providers. A mixed-method approach was employed to examine these experiences using talking circles and a survey. The study contributes to anticolonial research in that it resists narratives of dis(ease) put forth through neocolonial research paradigms. A key focus was the development of strategies that address the aspirations of urban Aboriginal youth, laying foundations upon which their potential in health and wellness can be nurtured, supported, and realized. The study contributes to a new narrative of the health of urban Aboriginal youth within a culturally centred and culturally safe framework that acknowledges their strong connection to their Indigenous lands, languages, and traditions while also recognizing the spaces between which they move.

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)0.019
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.415
Threshold uncertainty score0.834

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.082
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.006
Science and technology studies0.0030.001
Scholarly communication0.0090.006
Open science0.0030.007
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.4150.304

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 head0.060
GPT teacher head0.421
Teacher spread0.361 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2013
Admission routes1
Has abstractyes

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