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Record W4377000097 · doi:10.1525/elementa.2022.00144

Just agricultural science: The green revolution, biotechnologies, and marginalized farmers in Africa

2023· article· en· W4377000097 on OpenAlexfundno aff
Brian Dowd‐Uribe

Bibliographic record

VenueElementa Science of the Anthropocene · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsnot available
FundersDalhousie University
KeywordsAgricultureGreen RevolutionVariety (cybernetics)Work (physics)Agricultural revolutionNeutralityScale (ratio)Inclusion (mineral)Economic growthBusinessPolitical scienceSociologyEconomicsSocial scienceEngineeringGeography

Abstract

fetched live from OpenAlex

Contemporary agricultural development has changed in significant ways since the green revolution (GR). Its goals have expanded beyond national development to the achievement of environmental and social goals, and, notably, targeted gains for marginalized farmers. Moreover, advances in molecular breeding have expanded the tools used to achieve such goals. This research examines a prominent agricultural biotechnology program, pest resistant (Bt) cowpea in Burkina Faso, and asks whether and how this program can best achieve its goal of delivering benefits for marginalized farmers. I argue that 2 substantially criticized assumptions of GR-era agricultural development—the scale-neutrality of seeds and the sufficiency of expert technical knowledge—continue to guide the Bt cowpea project and limit its ability to deliver benefits for marginalized farmers. The presence of these guiding assumptions can be located in key programmatic decisions that work at a cross purpose to the project’s social goals, notably (a) the choice of parent variety favoring commercial producers, (b) an absence of institutions to extend adoption and benefits, and (c) a lack of meaningful farmer inclusion. This case adds to a body of research that shows that biological innovations alone—what I call “just agricultural science”—are not sufficient to drive socially just outcomes for marginalized farmers without accompanying social innovations.

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 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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.008
Science and technology studies0.0010.008
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.287
Teacher spread0.239 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations11
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueElementa Science of the AnthropoceneSame topicGenetically Modified Organisms ResearchFrench-language works237,207