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Record W2912962941 · doi:10.3148/66.4.2005.246

<i>Collective Kitchens in Canada:</i> A Review of the Literature

2005· review· en· W2912962941 on OpenAlexaffvenueabout
Rachel Engler‐Stringer, Shawna Berenbaum

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2005
Typereview
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsUniversity of SaskatchewanUniversité de Montréal
Fundersnot available
KeywordsPromotion (chess)Public relationsQuality (philosophy)DignityPsychologySociologyMarketingPolitical scienceBusiness

Abstract

fetched live from OpenAlex

PURPOSE: Collective kitchens are community-based cooking programs in which small groups of people cook large quantities of food. They have developed over the past 20 years, and hundreds of groups have been formed across the country. However, collective kitchens described in the literature vary considerably in structure, purpose, and format. The purpose of this review is to synthesize research on this topic. METHODS: Articles and theses were collected through searches of major databases, and synthesized to improve understanding of current information, and of continuing gaps in the knowledge of collective kitchens in Canada. RESULTS: The limited published research on collective kitchens suggests that social and learning benefits are associated with participation. Some indication exists that participants also find the food cooked to be high quality, culturally acceptable, and acquired in a manner that maintains personal dignity. Whether collective kitchens have an impact on food resources as a whole is unclear, as research has been limited in scale. CONCLUSIONS: The role of collective kitchens in community building and empowering participants often is noted, and bears further investigation. Dietitians and nutritionists have a unique opportunity to facilitate the health promotion and food security benefits of collective kitchens.

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)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.498
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.007
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 head0.357
GPT teacher head0.564
Teacher spread0.207 · 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
GenreReview

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

Citations40
Published2005
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Dietetic Practice and ResearchSame topicFood Security and Health in Diverse PopulationsFrench-language works237,207