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Record W4313524050 · doi:10.1177/11771801221145562

“We need to work hand in hand”: supporting cancer survivorship care with First Nations and Métis peoples in Canada via video

2023· article· en· W4313524050 on OpenAlexaffabout
Roanne Thomas, Wendy Gifford, Jennifer Poudrier, Alysson Rheault, Shirin M. Shallwani

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsUniversity of SaskatchewanUniversity of Ottawa
Fundersnot available
KeywordsIndigenousThematic analysisCeremonySpiritualityParticipatory action researchSurvivorship curveCitizen journalismHealth carePsychologyNursingPublic relationsMedicineSociologyPolitical scienceQualitative researchCancerGeographyAlternative medicine

Abstract

fetched live from OpenAlex

There is a lack of access to culturally safe and individualized cancer survivorship care and awareness of the unique challenges and strengths that Indigenous persons living with cancer (PLCs) face. This study aimed to explore the experiences and needs of First Nations and Métis PLCs across Canada. From 2014 to 2016, we engaged 87 participants who were either PLCs or caregivers (CGs) from five communities across Canada—Gitxsan and Kenora, British Columbia; Ottawa, Ontario; and Akwesasne and Kahnawake, Quebec—using participatory arts-based methods. Following the thematic analysis of participants’ photographs, journal entries, and stories, we created a video exploring the themes of spirituality and ceremony, finding strength together, the land and nature, creating and sharing, and navigating health care. Participants’ feedback on the video supports the use of video as a knowledge translation tool that may promote meaningful dialogue around the cancer experiences of Indigenous peoples in Canada.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.166
GPT teacher head0.502
Teacher spread0.336 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations2
Published2023
Admission routes2
Has abstractyes

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