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Record W3174312537 · doi:10.17269/s41997-021-00480-0

The First Nations Food, Nutrition and Environment Study (2008–2018)—rationale, design, methods and lessons learned

2021· article· en· W3174312537 on OpenAlexafffundvenueabout
Hing Man Chan, Karen Fediuk, Malek Batal, Tonio Sadik, Constantine Tikhonov, Amy Ing, Lynn Barwin

Bibliographic record

VenueCanadian Journal of Public Health · 2021
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsInuit Tapiriit KanatamiAssembly of First NationsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchIndigenous Services Canada
KeywordsParticipatory action researchCitizen journalismData collectionNonprobability samplingSystematic samplingGeographyEnvironmental resource managementEnvironmental healthSocioeconomicsEconomic growthEnvironmental protectionPolitical scienceSociologyMedicineSocial scienceEnvironmental sciencePopulation

Abstract

fetched live from OpenAlex

Abstract Objective To describe the rationale, the participatory nature of the methodology, and the lessons learned during the First Nations Food, Nutrition and Environment Study (FNFNES), a community-based participatory research project implemented in eight Assembly of First Nations regions, which includes the entirety of Canada south of the 60thparallel. Methods FNFNES respected the First Nations principles of Ownership, Control, Access and Possession (OCAP®) ( https://fnigc.ca/ocap ). A random sampling strategy based on an ecosystem framework comprising 11 ecozones was adopted to collect representative nutritional and environmental health results for all First Nations adults living on-reserve south of the 60thparallel. Data collection occurred during the fall months from 2008 to 2016. Respective First Nations were involved in the planning and implementation of data collection for the five principal components: household interviews, tap water sampling for metals, surface water sampling for pharmaceuticals, hair sampling for mercury, and traditional food sampling for contaminants. Results A total of 6487 adults from 92 First Nations participated in the Study (participation rate 78%). A higher percentage of females (66%) participated than males (34%). The average age of males and females was similar (44 and 45 years, respectively). This study offers a novel body of coherent and regionally representative evidence on the human dimension of the ongoing environmental degradation affecting First Nations. Conclusion FNFNES serves as a good example of participatory research. We encourage public health professionals to develop policy and programs building on the participatory dimension of the research as well as on its results. The information collected by the FNFNES is also important for community empowerment, environmental stewardship and the general promotion of good health by and for First Nations 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 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)0.126
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.666

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1260.061
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0040.006
Scholarly communication0.0040.003
Open science0.0040.004
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.002

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 head0.238
GPT teacher head0.440
Teacher spread0.202 · 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 designQualitative
DomainMethods
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

Citations36
Published2021
Admission routes4
Has abstractyes

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