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Enregistrement W4405744996 · doi:10.2458/jpe.7243

Review of Ellingson, Stephen. 2024. Planting with purpose: How farmers create a resilient food landscape.

2024· article· en· W4405744996 sur OpenAlexaff

Notice bibliographique

RevueJournal of Political Ecology · 2024
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueIntellectual Property Law
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésBusinessChemistryEnvironmental science

Résumé

récupéré en direct d'OpenAlex

In Planting with purpose: How farmers create a resilient food landscape, Stephen Ellingson explores how a relatively robust local food system emerged in Central New York state over roughly the past decade.As a sociologist, Ellingson is specifically interested in understanding what motivates people to take on the punishing and precarious work of local food production, and what motivates them to remain committed to the work despite the manifold challenges.The short answer-perhaps intuitive at first blush, though conceptually more complicated-is that local farmers, chefs, and artisanal producers are motived and sustained by a complex moral order.Ellingson here makes an interesting-and ultimately generative-conceptual move by training our focus away from the more conventional analytic approach of investigating the intertwining of ethical commitments and consumption, toward questions of morals within the context of production-side dynamics.Accordingly, Ellingson seeks to contribute to a theory of local food production that centers morality as a key driver in compelling actors to engage, and remain, with the challenging work of realizing alternative local food systems.Drawing on a resurgent body of sociological scholarship the centers values and morality as an explanatory element of action, Ellingson sets up a distinction between conventional agriculture and alternative agriculture.The former incorporates capitalist logics and transposes upon them a moral rationality: the pursuit of efficiency, profit maximization, and market share all become proxy indicators for 'good' farming.Alternative agriculture, on the other hand, prioritizes and assigns moral status to commitments beyond simple capitalist logics, including support for biodiversity and minimizing (or indeed reversing) the ecological impacts of farming.As Ellingson observes, the farmers, chefs, and artisanal producers he engages in the study "organize their work so that these values are placed above profit" (p.30).This is a methodologically rich project, started in 2018, and based on extensive engagement in the field.Ellingson conducted 51 interviews, representing 45 organizations working across 8 counties that comprise Central New York state in the USA.Ellingson engaged with people and organizations from across the local, alternative food production and distribution sector, including seven farmers running community supported agriculture (CSA) businesses, seven meat producers, four cheese makers, seven small farmers, four local food retailers, six self-identified locavore restaurateurs, seven actors who work on local food issues for local governments or farming non-profits, two farm-based breweries, and one owner of a small local food distribution co-op.In total Ellingson notes that his interviewees represent nearly 40% of all those included in the local food system in Central New York (p.37).In Chapter 2, Ellingson elaborates on his findings by describing the moral commitments of farmers and chefs who support the alternative local food system within Central New York.This chapter will be of particular interest to readers of this journal as Ellingson demonstrates the complex entanglements between 'nature', 'humans' and the development of moral commitments.Ellingson develops a three-part typology to categorize farmers in the study area: new farmers, returning farmers, and legacy farmers.He notes that there is no unifying moral order among these groups, though he also states that "all farmers identified a broad set of environmental and communal values that motivated them to adopt an ethic of care" (p.49).To the extent there is a difference in motivation between these three groups, it is a matter of emphasis.New farmers were more likely to articulate commitments to sustainability and the reformation of food systems, while returning and legacy farmers were more often compelled by ethical animal husbandry, land stewardship, and commitment to family.Local farmto-table restauranteurs share some of these values and articulate them through food aesthetics, land stewardship and sustainability, and relationships with other local food system actors.In Chapter 3, Ellingson describes how his interviewees prioritize 'non-economic' values and relationships to navigate the challenges of local alternative production.He builds on this in Chapter 4 to make the more general argument that we need to take emotion and values seriously in our analysis of what motivates people.As it relates to local alternative food system actors, Ellingson writes, "focusing on the interplay of emotions, production, and morality helps us understand the kinds of behaviors that may not seem rational or financially rewarding" (p.40).There is much for political ecologists to pick up on in this monograph.At times Ellingson's analysis might be read as a reification of the so-called natural and social worlds as discrete entities, a logic that political

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)0,004
score de la tête « metaresearch » (Gemma)0,016
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: Sans objet
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,062

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,016
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0080,009
Études des sciences et des technologies0,0020,002
Communication savante0,0030,005
Science ouverte0,0030,002
Intégrité de la recherche0,0070,006
Charge utile insuffisante (le modèle a refusé de juger)0,0110,011

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 Opus0,026
Tête enseignante GPT0,301
Écart entre enseignants0,275 · 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
GenreSynthèse

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

En bref

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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