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Record 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 on OpenAlexaff

Bibliographic record

VenueJournal of Political Ecology · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntellectual Property Law
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBusinessChemistryEnvironmental science

Abstract

fetched live from 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

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)0.004
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0080.009
Science and technology studies0.0020.002
Scholarly communication0.0030.005
Open science0.0030.002
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0110.011

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 head0.026
GPT teacher head0.301
Teacher spread0.275 · 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
GenreReview

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

Citations0
Published2024
Admission routes1
Has abstractyes

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