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Record W1961330828 · doi:10.26522/br.v12i1.326

How Happy is Your Meat? Confronting (Dis)connectedness in the ‘Alternative’ Meat Industry

2011· article· en· W1961330828 on OpenAlex

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

VenueThe Brock Review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsnot available
Fundersnot available
KeywordsDisconnectionDenialPopularityMeat packing industrySocial connectednessBusinessMarketingPsychologyBiologyPolitical scienceFood science

Abstract

fetched live from OpenAlex

The rise of ‘happy meat’ and support for small farmers has gained popularity in the alternative food movement in response to concerns about the industrialized meat industry. Looking at slaughter in the alternative meat movement, this article identifies three types of disconnectedness: socio-spatial, aesthetic, and connected. Socio-spatial disconnection is explored here through an analysis of the Mobile Slaughter Unit as a practice of slaughter alternative to industrial scale slaughter. This article uses alternative farms’ web marketing materials to explain aesthetic disconnection occurring in the alternative meat movement. Connected disconnection is understood through a brief analysis of a new phenomenon of ‘do-it-yourself’ slaughter. This article discusses how these three sites of disconnection represent a denial of the actual connections humans share with animals.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.637
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.157
GPT teacher head0.365
Teacher spread0.209 · 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