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Is China’s outward investment in oil a global security concern?

2012· article· en· W1931685620 on OpenAlexvenueno aff
Ilan Alon, Aleh Cherp

Bibliographic record

VenueTransnational Corporation Review · 2012
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy Security and Policy
Canadian institutionsnot available
FundersHarvard Kennedy SchoolCentral European UniversityRollins College
KeywordsChinaForeign direct investmentEnergy securityNational securityHarmInternational tradeBusinessSubsidyGovernment (linguistics)Investment (military)Market economyState (computer science)EconomicsPolitical scienceLawPoliticsRenewable energy

Abstract

fetched live from OpenAlex

The motivations prompting China's dramatic increase in outward foreign direct investment (OFDI) are not always clear, especially regarding OFDI by state-owned enterprises (SOEs) in energy and natural resources. First, both commercial and governmental interests are intertwined, although not necessarily in lock-step. Chinese SOEs listed in the West may worry about the reputational risks to their global corporate citizenship, while government stakeholders may instead focus on diplomatic international relations. Second, subsidies for oil investments may be viewed as serving Chinese national interests and threatening the national security of the host countries. Whether China's OFDI will benefit or harm global energy security, economic development and diplomatic relations is still hotly contested. This article discusses China's outward investment in oil with a global security concern.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.319
Teacher spread0.270 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2012
Admission routes1
Has abstractno

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