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Record W6980608588

Closing the loop of food systems: analyzing compost within community bounds

2023· article· en· W6980608588 on OpenAlexaboutno aff

Bibliographic record

VenueUTC Scholar (University of Tennessee at Chattanooga) · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Waste Reduction and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsCompostFood wasteClosing (real estate)Work (physics)Order (exchange)Argument (complex analysis)Environmental justiceNatural (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

The aim of this thesis is to construct a philosophical and ecological argument that places great value on localized food systems in terms of waste. This composition develops the claim that building composting infrastructure on a community scale will curb the global climate crisis and enhance the interconnectedness humans have within themselves, each other, and the natural world. The first prong of this thesis entails a theoretical framework we must function under in order to implement such radical food revolutions in our communities informed by Buddhist principles. This proceeds an international case study of the composting infrastructure of Fort Albany First Nation, Canada; Rwinkwavu, Rwanda; Havana, Cuba; Surabaya, Indonesia; and Dhaka, Bangladesh which emphasize the Indigenous, health-informed, war-related, colonial, and economic dimensions of compost in their respective communities. Following this, a national case study investigates community composting in Chicago, Illinois; Palmas de Mar, Puerto Rico; New York City, New York; Tucson, Arizona; and Sarasota, Florida under the lens of class, business, gender, education, and environmental justice within local food waste. The final case study of this thesis examines the systems of food waste within the author’s hometown and the work that she contributed to building food system resiliency in terms of compost in her community.

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)0.002
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.034
GPT teacher head0.214
Teacher spread0.180 · 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 designBench or experimental
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueUTC Scholar (University of Tennessee at Chattanooga)Same topicFood Waste Reduction and SustainabilityFrench-language works237,207