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Record W2778814162 · doi:10.1111/anti.12380

The Value of Rents: Global Commodity Chains and Small Cocoa Producers in Ecuador

2018· article· en· W2778814162 on OpenAlexaff
Thomas Purcell, Estefania Martinez, Nora Fernández

Bibliographic record

VenueAntipode · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEconomic rentCommodityValue (mathematics)Commodity chainCONTESTEconomicsDownstream (manufacturing)Production (economics)Agrarian societyMarket economyMicroeconomicsPolitical scienceLawAgricultureGeography

Abstract

fetched live from OpenAlex

Abstract Drawing on the Marxian theory of ground rent, this paper develops an analysis of “global commodity chains” ( GCC s) with agrarian roots. There is an acknowledgement that the concentrated downstream governance of primary commodity‐based GCC s has created a set of “asymmetrical” power relations which blocks the transmission of value upstream towards small producers. This paper argues that this research under‐specifies what is meant by value and rent, and in doing so marginalises the analysis of value production before its journey through inter‐firm relations. We demonstrate the importance of theorising the value constitution of commodities produced on the land and the forces that contest the payment of ground rent and thereby shape the geography of GCC s. Based on empirical research conducted around Ecuador's “post‐neoliberal” cocoa re‐activation plan, we identify the class politics and production mechanisms through which value and rent escapes the hands of a stratified network of small owner producers.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.271
Teacher spread0.248 · 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 designObservational
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

Citations22
Published2018
Admission routes1
Has abstractyes

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