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Record W2979805039 · doi:10.11124/jbisrir-d-19-00069

Food security in African Canadian communities

2019· article· en· W2979805039 on OpenAlexaffabout
Keisha Jefferies, Gail Tomblin Murphy, Melissa Helwig

Bibliographic record

VenueThe JBI Database of Systematic Reviews and Implementation Reports · 2019
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsNova Scotia Health AuthorityDalhousie UniversityKellogg's (Canada)
Fundersnot available
KeywordsFood securityIndigenousFocus groupInclusion (mineral)Food insecurityPopulationImmigrationGrey literaturePolitical scienceGeographySociologyEnvironmental healthMedicineBusinessSocial scienceMEDLINEMarketingAgriculture

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study is to synthesize and describe the evidence relating to food security among African Canadian communities to inform future research and health policy concerning people of African descent. INTRODUCTION: Food security denotes the timely access to nutritionally and culturally appropriate foods by individuals, families, groups, and communities. In Canada, there are vulnerable groups who experience higher rates of food insecurity, including immigrant and senior populations as well as Indigenous communities. While there is evidence describing food security among these vulnerable groups, food security among African Canadian communities remains poorly understood. The African Canadian community is an integral component of the Canadian population, yet there is a limited understanding of food security among this group. INCLUSION CRITERIA: This review will focus on the African Canadian population and food security, which encompasses food access, nutrition, and culturally appropriate foods. Evidence obtained from qualitative, quantitative, mixed methods studies, as well as dissertations and gray literature will be considered for inclusion. METHODS: This scoping review will be conducted in accordance the JBI scoping review methodology. A comprehensive search strategy developed by a librarian scientist will be used to locate and retrieve relevant sources. A screening tool will be used to screen titles and abstracts as well as the full text of included sources. Data will then be extracted by two independent reviewers, synthesized, and presented narratively, including tables and figures where appropriate.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.217
GPT teacher head0.472
Teacher spread0.256 · 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
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

Citations6
Published2019
Admission routes2
Has abstractyes

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