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Record W4385658069 · doi:10.1007/s10460-023-10493-9

Contested agri-food futures: Introduction to the Special Issue

2023· article· en· W4385658069 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAgriculture and Human Values · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Ottawa
FundersUniversity of Auckland
KeywordsScholarshipFood systemsSociologyFutures studiesFutures contractVisionEnvironmental ethicsTechnoscienceSocial sciencePolitical scienceFood securityAgricultureEngineering ethicsEconomicsEconomic growthEngineering

Abstract

fetched live from OpenAlex

Abstract Over recent decades, influential agri-food tech actors, institutions, policymakers and others have fostered dominant techno-optimistic, future visions of food and agriculture that are having profound material impacts in present agri-food worlds. Analyzing such realities has become paramount for scholars working across the fields of science and technology studies (STS) and critical agri-food studies, many of whom contribute to STSFAN—the Science and Technology Studies Food and Agriculture Network. This article introduces a Special Issue featuring the scholarship of STSFAN members, which cover a range of case studies and interdisciplinary and transdisciplinary engagements involving such contested agri-food futures. Their contributions are unique in that they emerged from the network’s specific modus operandi: a workshopping practice that supports the constructive, interdisciplinary dialogue necessary for critical research and rigorous analyses of science and technology in agri-food settings. This introduction offers an overview of STS and critical agri-food studies scholarship, including their historical entanglements in respective studies of food scandals, scientific regimes and technological determinism. We illustrate how interdisciplinary engagement across these fields has contributed to the emergent field of what we term agri-food technoscience scholarship, which the contributions of this Special Issue speak to. After a brief discussion of STS concepts, theories and methods shaping agri-food policy, technology design and manufacturing, we present the eleven Special Issue contributions in three thematic clusters: influential actors and their agri-food imaginaries; obfuscated (material) realities in agri-food technologies; and conflictual and constructive engagements in academia and agri-food. The introduction ends with a short reflection on future research trajectories in agri-food technoscience scholarship.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.016
GPT teacher head0.219
Teacher spread0.204 · 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