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Record W3121106607 · doi:10.1002/bse.2686

Traders as sustainability governance actors in global food supply chains: A research agenda

2021· article· en· W3121106607 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBusiness Strategy and the Environment · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCorporate governanceSustainabilityBusinessStakeholderSupply chainPoliticsStakeholder engagementWork (physics)Industrial organizationEconomic systemEconomicsMarketingPublic relationsPolitical scienceManagementFinance

Abstract

fetched live from OpenAlex

Abstract Corporate actors are rapidly gaining ground as nontraditional forms of authority that shape sustainability governance efforts in global food supply chains. This paper highlights the critical, but underresearched role of traders—companies whose core business lies in the movement and exchange of agricultural commodities between producers and manufacturers—in linking corporate sustainability ambitions to on‐the‐ground impacts. Drawing on a systematic analysis of the major transnational corporations trading cocoa, coffee, and palm oil, we present advantages and potential pitfalls of relying on traders as implementers of sustainability governance and outline a future research agenda that focuses on producer‐level impacts, changes in supply chain organization and power dynamics, and traders' interactions with state and other nonstate actors. At the intersection of supply chain management, political economy, geography, and global governance, research on traders as key sustainability governance actors also provides novel opportunities for interdisciplinary work and stakeholder engagement.

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.

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)0.001
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 score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.035
GPT teacher head0.284
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