MétaCan
Menu
Back to cohort
Record W7029385747

Investigation of health promotion programs on food and nutrition in rural and First Nations communities of Northwestern Ontario [research project] / by Stephanie Collins.

2017· other· en· W7029385747 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typeother
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsHealth promotionPublic healthParticipatory action researchRural areaRural healthCitizen journalismPromotion (chess)Intervention (counseling)Face (sociological concept)
DOInot available

Abstract

fetched live from OpenAlex

Purpose: To discover the status of health promotion programs based on food and nutrition
\nin rural and First Nations communities in Northwestern Ontario, and the challenges,
\nsuccesses, and methodologies behind providing them. Background: Rural communities
\ntypically have lower health status than urban communities, and Aboriginals have lower
\nhealth status than non-Aboriginals in Canada. Contributing factors for these disparities
\nare discussed with a particular emphasis on the role of food and nutrition. Results: There
\nare many programs involving food or nutrition in this area. Programs proved successful
\nin using participatory models for intervention planning and delivery, having adequate
\ntraining and ongoing support for interveners, delivering clear messages, using a rural
\nlens, and using an Aboriginal focus. There were many challenges for health
\nprofessionals, often surrounding food security, cost, and availability of food. Challenges
\ndid not always have solutions. More research is needed on the theoretical base of
\nprograms, and the challenges that face communities, their processes, and resulting health
\nconsequences in Northwestern Ontario specifically.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.910
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.134
GPT teacher head0.326
Teacher spread0.191 · 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 designNot applicable
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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueKnowledge Commons (Lakehead University)Same topicGender, Security, and ConflictFrench-language works237,207