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Enregistrement W4224030325 · doi:10.15353/cfs-rcea.v9i1.511

de-meatification imperative

2022· article· en· W4224030325 sur OpenAlexaffvenue
Tony Weis, Rebecca Ellis

Notice bibliographique

RevueCanadian Food Studies / La Revue canadienne des études sur l alimentation · 2022
Typearticle
Langueen
DomaineEnvironmental Science
ThématiqueAgriculture Sustainability and Environmental Impact
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésPopulationConsumption (sociology)Environmental ethicsChinaPolitical sciencePopulation growthDevelopment economicsEconomic growthGeographyEnvironmental healthSociologyLawMedicineSocial scienceEconomics

Résumé

récupéré en direct d'OpenAlex

Meatification describes a momentous dietary transformation: the average person on earth today consumes nearly twice as much animal flesh every year as did the average person just two generations ago, amidst a period of rapid human population growth and with marked disparities between rich and poor. Further, meatification is projected to continue in the coming three decades, at the same time as the world adds another 2 billion people, with growth concentrated in fast-industrializing countries. There is overwhelming evidence that meatification bears heavily on a range of problems including climate change, biodiversity loss, food consumption disparities, mounting risks of antibiotic resistance, increasing rates of non-communicable disease, and growing realms of animal suffering. The basic implication is inescapable: the de-meatification of diets is an urgent environmental and social priority, and must be part of any project of providing critical food guidance. There are many signs this recognition is growing in environmental and public health advocacy (including pressure to reform dietary guidelines, most notably in China), calls for a ‘meat tax’, and in rising levels of vegetarianism and veganism in some of the countries that have long been at the forefront of meatification. After briefly summarizing the course of meatification and the de-meatification imperative, this chapter focuses on its 3 primary possibilities: conscientious omnivory (which has various hues, as in calls for ‘green’ or ‘ethical’ meat); vegetarianism; and veganism. The first possibility, conscientious omnivory, recognizes the need to reduce 'meatification' from levels of consumption in industrialized countries, but resolutely upholds the need for some livestock products in human diets and for small livestock populations in mixed farming systems, due to their role recycling some wastes, returning condensed nutrients to land, and providing some labour. From this perspective, necessity makes some meat consumption (but less than in industrialized countries today) a 'benign indulgence' in Simon Fairlee’s terms, with the challenge to source meat, eggs, and milk from sustainable mixed farms where the animals have lived decent lives. The second possibility, vegetarianism, accepts the functional necessity of small livestock populations in mixed farming systems, which includes their ability to generate useable nutrition along with providing beneficial on-farm services (augmented, for some, by pure palate pleasure, as in the love of ice cream, cheesy pizza, or scrambled eggs), but seeks a non-violent resolution. But unlike conscientious omnivory, the need for animals on mixed farms does not justify killing them for food, much less make it ‘benign’, and it is seen to be desirable and possible for animals to have good lives with only reproductive outputs (i.e. milk and unfertilized eggs) and wool taken, rather than flesh. The third possibility, veganism, rejects all use of animals in production and consumption, arguing that the place of livestock in mixed farming systems for most of agrarian history does not justify its continuance in the present age. This position holds that livestock production is an inherently inefficient way of meeting human nutritional needs for two basic reasons: first, there is compelling evidence that it is not only possible to be healthy with plant-based diets but that they often lead to improved health and lower risks of non-communicable diseases; and second, it is clear that plant-based diets tend to command much less land and resources, on average, than do either omnivorous or vegetarian diets. Along with improving population health, meeting human nutritional needs more efficiently is seen to have the potential to enhance distributional equity. Finally, the case for veganism insists that vegetarianism cannot escape some level of systematic killing of animals, as most males are not productive in this conception and because females become unproductive short of their natural lifespan. In spite of key mutual objections to the current scale of animal consumption and industrial production, there are often heated debates between conscientious omnivores, vegetarians, and vegans. Observing this, some might assume that these groups should just aim to get along, submerge their differences, and focus collective energies on confronting the big, urgent need to build momentum for de-meatification and undermine industrial livestock production. In such a few, debates about the end point of de-meatification appear as unnecessary distractions, to the extent that these groups discredit one another, and are best left (or at least strategically moderated) for that future day when industrial livestock production is eradicated. This paper suggests that thinking critically about different end-points is necessary to recognize the challenges of alliance-building and constructively communicating the de-meatification imperative.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,998
Score d'incertitude au seuil0,051

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0030,014
Communication savante0,0050,007
Science ouverte0,0020,007
Intégrité de la recherche0,0050,006
Charge utile insuffisante (le modèle a refusé de juger)0,0150,005

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,225
Écart entre enseignants0,203 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2022
Routes d'admission2
Résumé présentoui

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