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Record W3102448394 · doi:10.1177/1177180120970941

Engaging Indigenous peoples in research on commercial tobacco control: a scoping review

2020· review· en· W3102448394 on OpenAlexafffund
Kelley Lee, Julia Smith, Sheryl Thompson

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2020
Typereview
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsSimon Fraser University
FundersFirst Nations Health AuthorityInstitute of Aboriginal Peoples Health
KeywordsIndigenousMainstreamCommunity engagementTobacco controlPsychological interventionPublic relationsProject commissioningSociologyPublishingPolitical scienceEngineering ethicsMedicinePublic healthLawNursingEcology

Abstract

fetched live from OpenAlex

Commercial tobacco products are a leading contributor to health disparities for many Indigenous peoples. Mainstream interventions developed for non-Indigenous peoples have been found less effective at addressing these disparities. Meaningful engagement is needed to develop effective measures but there are limited understandings of what engagement means in practice. We conduct a scoping review of studies self-reporting engagement with Indigenous peoples; assess their engagement against ethics guidelines concerning research involving Indigenous peoples and writings of Indigenous scholars; and draw lessons for advancing practice. We found engagement of Indigenous peoples in tobacco control research is practiced in varied ways—who conducts the research, who is engaged with, for what purpose, at what research steps, and what approaches are applied. Engagement ranges from limited to deeper commitment to research as decolonizing practice. Critical reflection along five questions can advance research practice for this purpose.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.001
Science and technology studies0.0040.000
Scholarly communication0.0010.001
Open science0.0040.000
Research integrity0.0000.003
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 head0.172
GPT teacher head0.505
Teacher spread0.333 · 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
GenreReview

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

Citations7
Published2020
Admission routes2
Has abstractyes

Explore more

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