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Record W7132981725

Cancer prevention and cultural continuity for Métis Peoples in Canada: a scoping review protocol

2023· other· W7132981725 on OpenAlexaboutno aff
Jennifer R. Sedgewick, Sheila Laroque-Bear, Vicky Duncan, Gary Groot, Marlin Legare, Maria Diaz Vega, José Diego Marques Santos, Tracey Carr

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2023
Typeother
Language
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousGrey literatureConsistency (knowledge bases)Promotion (chess)Health promotionMental healthProtocol (science)Cancer prevention
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Within Canada, cancer incidence has been significantly increasing among Métis people compared to the non-Indigenous population. Further, Métis people experience lower cancer survival rates due to barriers with accessing healthcare. One aspect shown to improve Métis physical and mental health is connecting to culture, as it is an important to the individual and community well-being for Métis people. Therefore, cultural continuity has the potential to be successfully integrated into cancer prevention and health promotion strategies in Canada. This scoping review aims to identify the literature on cultural continuity for Métis people and its role in health promotion and cancer prevention in Canada. Methods and Analysis: This study will follow methodological guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews and draw from other established frameworks and guidelines for scoping reviews. We will conduct electronic searches on Medline, PubMed, Embase, PsychInfo, and I-Portal (the University of Saskatchewan’s Indigenous Studies Database). We will also hand-search specific journals related to our review question. Finally, a grey literature search will include unpublished data from Indigenous health and governmental websites, as well as online search engines. After piloting a data extraction form that will be used to ensure consistency in themes and elements throughout the data, two reviewers will independently select articles and extract the data. Ethics: No primary data will be collected in this review; therefore, the review is exempt from research ethics approval. Dissemination: The results of this review will be shared with project partners (Métis Nation – Saskatchewan and the Saskatchewan Cancer Agency) and will be submitted for peer review publication. Our findings will be presented at relevant national and international meetings.

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)0.100
metaresearch head score (Gemma)0.068
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.910
Threshold uncertainty score0.528

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1000.068
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0110.010
Bibliometrics0.0200.018
Science and technology studies0.0090.006
Scholarly communication0.0110.007
Open science0.0070.007
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0570.011

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 head0.027
GPT teacher head0.347
Teacher spread0.320 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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
Published2023
Admission routes1
Has abstractyes

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