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Record W2588732282 · doi:10.1017/s1368980017000088

Low-income adults’ perceptions of farmers’ markets and community-supported agriculture programmes

2017· article· en· W2588732282 on OpenAlexaff
Elizabeth W. Cotter, Carla Teixeira, Annessa Bontrager, Kasharena Horton, Deyanira Soriano

Bibliographic record

VenuePublic Health Nutrition · 2017
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsQueen's University
Fundersnot available
KeywordsThematic analysisFocus groupNutrition EducationPerceptionAgricultureBusinessEconomic growthHealth equityGerontologyMarketingEnvironmental healthPsychologyMedical educationPolitical sciencePublic relationsMedicineQualitative researchGeographyHealth careSociologyEconomicsSocial science

Abstract

fetched live from OpenAlex

OBJECTIVE: To better understand low-income adults' attitudes towards participating in farmers' markets, community-supported agriculture (CSA) and nutrition education programming. DESIGN: Focus groups were held with a diverse sample of adults. Interviews were transcribed verbatim and analysed using thematic analysis. SETTING: Three affordable housing communities in Washington, DC, USA. SUBJECTS: Participants included twenty-eight residents of the three affordable housing communities. RESULTS: Four major themes emerged across groups, along with several sub-themes within each theme. These included: (i) perceptions of farmers' markets (benefits, barriers, current participation and knowledge); (ii) perceptions of CSA (benefits, barriers and questions/concerns); (iii) need/interest in additional programming (nutrition education, non-nutrition education, qualities of programming and perceived barriers); and (iv) current health knowledge and behaviours (dietary behaviours, health recommendations and health concerns). CONCLUSION: Adults living in urban, affordable housing communities desire access to healthy foods, but are limited by cost. Programmes could have a higher likelihood of success if they accept benefits like SNAP (the Supplemental Nutrition Assistance Program), are heavily marketed and incorporate culturally relevant nutrition education components.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0110.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.118
GPT teacher head0.426
Teacher spread0.308 · 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 designObservational
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

Citations84
Published2017
Admission routes1
Has abstractyes

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