MétaCan
Menu
Back to cohort
Record W2771522729 · doi:10.3390/ani7120099

Is a “Good Death” at the Time of Animal Slaughter an Essentially Contested Concept?

2017· article· en· W2771522729 on OpenAlexaff
Qurat ul-Ain, Terry L Whiting

Bibliographic record

VenueAnimals · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsAgriculture Food and Rural Development
Fundersnot available
KeywordsMoralityVisionPoliticsEpistemologyNormativeDemocracySociologyOriginal positionVariety (cybernetics)PhrasePolitical philosophyLawPolitical sciencePhilosophyEconomic JusticeLinguistics

Abstract

fetched live from OpenAlex

The phrase "essentially contested concept" (ECC) entered the academic literature in 1956 in an attempt to better characterize certain contentious concepts of political theory. Commonly identified examples of contested concepts are morality, religion, democracy, science, nature, philosophy, and certain types of creative products such as the novel and art. The structure proposed to identify an ECC has proven useful in a wide variety of deliberative discourse in the social, political, and religious arenas where seemingly intractable but productive debates are found. Where a strongly held moral position is contradicted by law, a portion of the citizenry see the law as illegitimate and do not feel compelled to respect it. This paper will attempt to apply the analytic structure of ECC to the concept of animal wellbeing at the time of slaughter specifically a "good death." The results of this analysis supports an understanding that the current slaughter debate is a disagreement in moral belief and normative moral theory. The parties to the dispute have differing visions of the "good." The method of slaughter is not an essentially contested concept where further discourse is likely to result in a negotiated resolution. The position statements of veterinary organizations are used as an example of current discourse.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.099
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.035
GPT teacher head0.372
Teacher spread0.337 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations6
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAnimalsSame topicHuman-Animal Interaction StudiesFrench-language works237,207