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Formalization through contracts: Implications for power in smallholder cocoa supply chains

2025· article· en· W4410909014 on OpenAlexafffund
Sophia Carodenuto, Claire Cutler, Sokhna Dieng, Marshall Alhassan Adams, William J. Thompson

Bibliographic record

VenueGeoforum · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of CanadaUniversity of Victoria
KeywordsPower (physics)Supply chainAgricultural economicsBusinessEconomicsIndustrial organizationAgricultural scienceNatural resource economicsCommerceMarketingEnvironmental science

Abstract

fetched live from OpenAlex

Côte d’Ivoire and Ghana, accounting for the majority of global cocoa production, exemplify the challenges of addressing environmental sustainability and social equity in informal agricultural supply chains. In this paper, we explore the implications of contractual relationships at the ’first mile,’ where smallholder cocoa farmers first market their product. Our analysis is motivated by the European Union’s Deforestation-free Regulation (EUDR), which aims to eliminate deforestation from global supply chains and is likely to accelerate contract formalization within the cocoa sector. Using in-depth case studies of Côte d’Ivoire and Ghana, we examined both formal and informal contracts, supported by 107 in-person interviews, to understand how these relationships shape smallholder agency and power dynamics. Formal contracts, as manifested through certification, offer certain structured benefits and are often viewed as a pathway to sustainable cocoa production. However, our findings reveal that they may constrain farmer agency by limiting flexibility in buyer selection and amplifying existing inequalities. Conversely, informal contracts, though opaque, appear to provide smallholders with greater negotiating power and autonomy at the first mile. These findings raise critical questions about the trade-offs inherent in formalization and highlight the need for nuanced policy approaches to achieve equitable and sustainable outcomes in global supply chains.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.580

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.020
GPT teacher head0.289
Teacher spread0.269 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2025
Admission routes2
Has abstractyes

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