MétaCan
Menu
Back to cohort
Record W4414748881 · doi:10.1111/joac.70048

The Ambiguous Ecologies of Agri‐Alternatives: Exploring the Calculus of Social Reproduction in Rural India

2025· article· en· W4414748881 on OpenAlexfundno aff
Arianna Tozzi, Enid Still

Bibliographic record

VenueJournal of Agrarian Change · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsnot available
FundersUniversity of ManchesterRoyal Geographical SocietyEuropean CommissionMultiple Sclerosis Scientific Research Foundation
KeywordsScholarshipConstruct (python library)Agency (philosophy)ReproductionEthnographyNarrativeAgrarian societySocial reproduction

Abstract

fetched live from OpenAlex

ABSTRACT This paper advances scholarship on agri‐alternatives by probing the gap between romanticised narratives of how alternative farming transitions ought to be and the actual practices farmers enact in their fields. Focusing on moments when such alternatives encounter on‐the‐ground realities, we propose ambiguous ecologies as a lens to explore the various elements shaping farmers' decisions and their complex dynamics. Centering social reproduction, we argue that transitions to agri‐alternatives are contested processes whereby farmers renegotiate productive and reproductive agrarian relations amidst uneven risks. Drawing on ethnographic insights from India, we contribute to feminist theorisation on the calculus guiding farmers' practices in two ways. First, by positing that ecologies and their materialities are key to how farmers navigate their engagement with agri‐alternatives, and second, by showing how ambiguous ecologies work as sites of agency where farmers make intimate calculations to construct liveable socio‐ecological relations against the grain of industrialised farming regimes.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0060.064
Scholarly communication0.0110.004
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.049
GPT teacher head0.251
Teacher spread0.202 · 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 designQualitative
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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Agrarian ChangeSame topicAgriculture, Land Use, Rural DevelopmentFrench-language works237,207