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Record W2293911644 · doi:10.14288/1.0088889

Cooking from the bottom-up: an exploration into the use of Vancouver's community kitchens as an empowerment tool

2009· article· en· W2293911644 on OpenAlexaboutno aff
Carrie Lee Chung

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldArts and Humanities
TopicArchitecture, Design, and Social History
Canadian institutionsnot available
Fundersnot available
KeywordsEmpowermentSociologyGeographyEconomic growthEconomics

Abstract

fetched live from OpenAlex

The purpose of this thesis was to explore the effectiveness of community kitchens as an empowerment tool. This thesis observes the ways in which community kitchens empower their participants, how they are being used to foster community development, and the opportunities and constraints in using community kitchens as an empowerment tool. The research questions are addressed in a variety of ways. First, a comprehensive literature review was undertaken to define the meaning of empowerment and community development as used by this thesis. Secondly, a multiple case study approach involving participant observation, key informant interviews and a survey was conducted to examine these questions. A total of seven community kitchens were involved in the case studies. The research suggests that community kitchens do empower participants but at an individual level. Participants learn skills such as cooperation, cooking and socialisation, and are empowered through self-help and by gaining confidence and self-esteem. At a community level, efforts have been made to empower the community and contribute to community building processes but with limited output. In some community kitchens, community development initiatives (such as volunteering to cook for a larger community) are in place but community kitchens as a whole has a minimal effect in creating community. Community kitchens, however, are effective at empowering individuals which is considered the first step to community empowerment.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.499
Threshold uncertainty score0.999

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 studies0.0020.001
Scholarly communication0.0000.001
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 head0.044
GPT teacher head0.204
Teacher spread0.160 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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