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Record W4221032248 · doi:10.1080/08941920.2022.2049410

The Green Transition in Context—Cobalt Responsible Sourcing for Battery Manufacturing

2022· article· en· W4221032248 on OpenAlex
Raphael Deberdt, Philippe Le Billon

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

VenueSociety & Natural Resources · 2022
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCorporate social responsibilityContext (archaeology)BusinessSustainabilitySupply chainDemocracyLanguage changeTransparency (behavior)Natural resource economicsEconomicsMarketingPolitical sciencePublic relationsPoliticsEcology

Abstract

fetched live from OpenAlex

Responsible cobalt in the context of the green transition is a major issue on the global sustainability agenda. Spurred by concerns around child labor in artisanal mine sites in the Democratic Republic of the Congo (DRC), corporate actors adopted a myriad of strategies to tackle reputational risks and establish responsible sourcing programs. Now encompassing forced labor, corruption, and environmental degradation mining-specific, as well as community development projects constitute the core of Corporate Social Responsibility (CSR) practices in the DRC. Informed by a review of academic and industry studies, this article raises concerns regarding the limitations of responsible cobalt sourcing. We present the initiatives developed to date, based on voluntary strategies, and then introduce new technology tools developed to trace mineral in supply chains, ensuring transparency of the information on the conditions of extraction and trade. Finally, we identify five limitations to responsible cobalt sourcing strategies constituting avenues for future research.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.726
Threshold uncertainty score0.638

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.203
Teacher spread0.195 · 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