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Record W2400825061 · doi:10.1111/1747-0080.12284

Exploring nutrition capacity in Australia's charitable food sector

2016· article· en· W2400825061 on OpenAlexaff
Kate Wingrove, Liza Barbour, Claire Palermo

Bibliographic record

VenueNutrition & Dietetics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsKensington Health
Fundersnot available
KeywordsFood insecurityExploratory researchQualitative researchBusinessCapacity buildingResource (disambiguation)MarketingFood securityPublic relationsEconomic growthPolitical scienceAgricultureSociologyGeographyEconomics

Abstract

fetched live from OpenAlex

AIM: The primary aim of this study was to explore the capacity of community organisations within Australia's charitable food sector to provide nutritious food to people experiencing food insecurity. A secondary aim was to explore their capacity to provide food in an environment that encourages social interaction. METHODS: This qualitative research used an exploratory case study design and was informed by a nutrition capacity framework. Participants were recruited through SecondBite, a not-for-profit food rescue organisation in Australia. Convenience sampling methods were used. Semi-structured interviews were conducted to explore the knowledge, attitudes and experiences of people actively involved in emergency food relief provision. Transcripts were thematically analysed using an open coding technique. RESULTS: Nine interviews were conducted. The majority of participants were female (n = 7, 77.8%) and worked or volunteered at organisations within Victoria (n = 7, 77.8%). Results suggest that the capacity for community organisations to provide nutritious food to their clients may be limited by resource availability more so than the nutrition-related knowledge and attitudes of staff members and volunteers. CONCLUSIONS: Australia's charitable food sector plays a vital role in addressing the short-term needs of people experiencing food insecurity. To ensure the food provided to people experiencing food insecurity is nutritious and provided in an environment that encourages social interaction, it appears that the charitable food sector requires additional resources. In order to reduce demand for emergency food relief, an integrated policy approach targeting the underlying determinants of food insecurity may be needed.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.709
GPT teacher head0.445
Teacher spread0.263 · 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 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

Citations11
Published2016
Admission routes1
Has abstractyes

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