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Record W2808617647 · doi:10.15273/jue.v7i2.8414

Getting the Lead Out: Urban Chicken Keeping as Transformative Neo-Agrarianism

2017· article· en· W2808617647 on OpenAlexvenueno aff
Sydney Giacalone

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicUrban Agriculture and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPolitical ecologyAgrarian societySubsistence agricultureEnvironmental ethicsEthnographySociologyUrban agricultureCapitalismPolitical economyAgriculturePolitical scienceEcologyBiologyLawAnthropology

Abstract

fetched live from OpenAlex

This ethnographic study explores how the discovery of lead contamination in urban chicken flocks in the Boston area unsettles postindustrial optimism and neo-agrarian romanticism, producing new openings for multispecies relationships. Within rising popular and political attention to food systems, urban chicken keeping stands as a uniquely positioned subset of urban agriculture. Through ethnography with chicken keepers, policy makers and businesses in Boston and Somerville, Massachusetts in the summer of 2016, my research investigated how urban chicken keeping might transform keepers’ thinking about food systems and animal relationships. The unexpected discovery of lead in chickens’ blood and eggs revealed keepers’ increasingly entangled relationships with the history of the soil they and their birds live upon, exposing what Marx (1981) termed the “metabolic rift” at the heart of industrial capitalist approaches to subsistence. With lead breaking the imagined simplicity of urban agriculture and the linear progression of modern cities, responses in urban chicken keeping reveal space for new ways of thinking about collective metabolism, multispecies living, food politics, and the bodies wrapped up in these material legacies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.672
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0070.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.039
GPT teacher head0.287
Teacher spread0.248 · 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 designOther design
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

Citations2
Published2017
Admission routes1
Has abstractyes

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