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Record W2030387233 · doi:10.15353/cfs-rcea.v1i2.57

Farmageddon: The True Cost of Cheap Meat

2014· article· en· W2030387233 on OpenAlex
Rita Hansen Sterne

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsnot available
Fundersnot available
KeywordsPurchasingAgricultureFood systemsArable landPerspective (graphical)Consumption (sociology)MarketingBusinessAnimal welfareSet (abstract data type)Food securityComputer scienceSociologyEcologySocial scienceBiology

Abstract

fetched live from OpenAlex

Food systems include many issues interconnected through complex relationships. Some writers examine one part of the food system in depth but—from my perspective as a management student—a strength of Farmageddon: The True Cost of Cheap Meat is that it examines food systems by systematically connecting a broad set of issues in its analysis of the widespread adoption of the industrial farming model. This model, the authors argue, requires vast tracts of arable land, makes broad and lifelong use of antibiotics in farm animals to minimize disease and encourage rapid growth, and promotes an increasing use of grain for animal feed rather than for human consumption. Throughout the book, the authors share evidence in an effort to encourage consumers to reflect on the implications of the system we support when purchasing our meat cheaply. The authors have written this book from their experiences as animal welfare activists for a broad audience, but focus their attention on costs that have been unaccounted for in the industrial food system.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.796
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.023
GPT teacher head0.222
Teacher spread0.199 · 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