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Record W2104679059 · doi:10.1177/0020715209105146

Rethinking Global Commodity Chains

2009· article· en· W2104679059 on OpenAlexvenueno aff
Paul S. Ciccantell, David A. Smith

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
FundersUniversity of California, Irvine
KeywordsCommodityCommodity chainConsumption (sociology)Industrial organizationEconomicsEconomic geographyAgricultureProduction (economics)BusinessEconomic systemEconomyMarket economyEcologyMicroeconomicsSociology

Abstract

fetched live from OpenAlex

The global commodity chains (GCCs) approach is an insightful way to understand issues of `development' and production and consumption differentials across space. It potentially offers insight into the issue of `ecologically unequal exchange'. However, we propose three revisions to conventional GCC analysis. First, many of the GCC studies tend to focus on only part of the commodity chain — and we need, in effect, to `lengthen' the chains. Stephen Bunker (1984) emphasized that `commodities can emerge only from locally based extractive and productive systems' (p. 1017). Beginning GCC analysis with these primary products forces the examination of various modes, techniques and technologies of extractive regimes, as well as the key roles of transportation and communications systems. Second, focusing on this `longer chain' requires analysis of spatially based disarticulations and contestations. Mineral deposits and agricultural economies tend to be tied to specific `natural' geographies — thus, `enclave economies' frequently develop that are globally integrated but locally disarticulated. Transportation systems (especially of bulk products) are extremely vulnerable to disruption and change dramatically over time. Third, we explicitly focus on tightly integrated social and natural processes across a range of industries. The goal is to focus on the relationship between long-term changes in the world economy and the natural environment, as well as on research in environmental studies that examines `ecologically unequal exchange' and points to prospects for sustainable development.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score0.499

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 communication0.0000.001
Open science0.0010.000
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 head0.067
GPT teacher head0.365
Teacher spread0.299 · 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

Citations61
Published2009
Admission routes1
Has abstractyes

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