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Record W2898581439 · doi:10.1080/19186444.2018.1507872

Enabling Chinese FDI in Canadian oil sands: process and structure

2018· article· en· W2898581439 on OpenAlexaffvenueabout
Kalinga Jagoda, Xiaohua Lin, Patrick Wojcik

Bibliographic record

VenueTransnational Corporation Review · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsToronto Metropolitan UniversityUniversity of Guelph
Fundersnot available
KeywordsOil sandsForeign direct investmentProcess (computing)BusinessChinaEconomicsInternational tradeIndustrial organizationPolitical scienceAsphaltGeographyArchaeologyComputer scienceMacroeconomicsLaw

Abstract

fetched live from OpenAlex

The rise of Chinese investments in the Canadian resources sector has added to the already heated debate over growing outward FDI from developing countries since such investments often involve state controlled funds and entities. Prior research has rarely considered FDI formation as a result of interaction between developing country firms and Canadian firms. Using a case study approach, this paper examined the deal structure and the process by which the deal is negotiated and implemented in the CNOOC takeover of Nexen. The findings revealed that the company culture, risk migration, and host country government policies play important roles in successful implementation.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.273

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.009
Science and technology studies0.0030.001
Scholarly communication0.0050.002
Open science0.0010.001
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 head0.015
GPT teacher head0.261
Teacher spread0.246 · 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 designQualitative
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

Citations1
Published2018
Admission routes3
Has abstractno

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