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Record W2883426502 · doi:10.5751/es-10274-230314

Food as a daily art: ideas for its use as a method in development practice

2018· article· en· W2883426502 on OpenAlexvenueno aff
L. Jamila Haider, Frederik J. W. van Oudenhoven

Bibliographic record

VenueEcology and Society · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsnot available
Fundersnot available
KeywordsHospitalitySpace (punctuation)SociologyMarketingAestheticsBusinessEnvironmental ethicsGeographyArtComputer scienceTourismPhilosophyArchaeology

Abstract

fetched live from OpenAlex

Food is the only art form that is also a basic need. It requires knowledge and labor for cultivation and cooking and offers a space where tastes, hospitality, and other cultural values are expressed and created. As a daily practice in agricultural societies, food is a holistic concept that incorporates ideas of health, spirituality, community, technology, and trade, and connects the most marginalized with the most powerful. Conventional international development aid is dominated by a limited number of relatively narrow ideas informed by scientific processes: progress, economic growth, market development, and agricultural production. Such ideas are often at odds with endogenous ideas about development and often work against biological and cultural diversity. Here, we reflect on our experiences documenting the food culture of the Pamiri people of Afghanistan and Tajikistan. We trace the trajectory of ideas about development, local and foreign, and explore how at different stages in those trajectories, the qualities of food can help promote local perspectives, challenge dominant power relationships, and challenge scientific practices to incorporate these perspectives better. We show how, as a method and a daily art form, food helps nurture an "ecology of ideas" in which traditional knowledge and science can come together to create locally meaningful solutions toward development and sustainability.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.266
Threshold uncertainty score0.241

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.035
GPT teacher head0.298
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2018
Admission routes1
Has abstractyes

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