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Record W1971391815 · doi:10.1155/2013/672060

China and the Global Uranium Market: Prospects for Peaceful Coexistence

2013· article· en· W1971391815 on OpenAlexafffund
Pascale Massot, Zhanming Chen

Bibliographic record

VenueThe Scientific World JOURNAL · 2013
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsProcurementChinaCommodityArgument (complex analysis)International tradeUraniumBusinessNuclear powerEconomicsEconomyMarket economyPolitical scienceLawMarketing

Abstract

fetched live from OpenAlex

China's recent reemergence has resulted in a significant increase in the global demand of commodities and is already having major impacts on the dynamics of global commodity markets. In the case of the global uranium market, we stand at the very beginning of a period of change. However, interesting trends are already emerging. Whereas China has had many policy reversals, and some difficulties in taking control of its procurement strategy in other commodity markets, it is seemingly more successful in managing its uranium procurement strategy. Why? The argument presented here is that a mixture of domestic and international level variables has allowed China more room for maneuver in fulfilling its uranium procurement strategy. On the domestic level, a centralized industry, and, on the international level, a geographically dispersed and uncoordinated market have allowed China to forge ahead with an ambitious civilian nuclear power plan and triple its total uranium imports, all within the span of a few years. Many challenges remain, not the least that of negative public opinion, which has surged since the Fukushima disaster in 2011. Nevertheless, should uranium demand continue to grow, this paper will consider the potential for continued peaceful coexistence among uranium market participants worldwide.

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)0.002
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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 designNot applicable
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

Citations16
Published2013
Admission routes2
Has abstractyes

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