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Record W2518777409 · doi:10.31542/j.ecj.56

A Discounted Threat: Environmental Impacts of the Livestock Industry

2012· article· en· W2518777409 on OpenAlexafffundvenue
Leanne Bourgeois

Bibliographic record

VenueEarth Common Journal · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsMacEwan University
FundersMacEwan University
KeywordsLivestockGreenhouse gasNatural resource economicsAgricultureBusinessBiodiversityEnvironmental protectionEnvironmental impact assessmentEnvironmental scienceOverconsumptionEnvironmental pollutionEnvironmental planningProduction (economics)EcologyEconomicsBiology

Abstract

fetched live from OpenAlex

This article provides an overview of the environmental effects of the livestock industry. Current industry practice, specifically the proliferation of concentrated animal feeding operations as the primary means of production, has left far-reaching ecological consequences in its wake. Animal agriculture is implicated in numerous environmental threats including rising greenhouse gas emissions (particularly through release of nitrous oxide and methane, in addition to carbon dioxide), overconsumption of water for both live animals and feed crops, and decreased water quality. Furthermore, localized pollution owing to copious animal waste has tainted many regions and compromised human health. Alterations of land use and the resulting loss of biodiversity are also of major concern. The problem has expanded as developing countries’ appetite for these products grows – however, the issue has tended not to be a focal point of environmental debate. The article details the environmental destruction wrought by current practices, while outlining recommendations for reducing the environmental toll, at both the individual and systemic level

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0060.006
Open science0.0010.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.006
GPT teacher head0.217
Teacher spread0.211 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2012
Admission routes3
Has abstractyes

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