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Record W1886116518 · doi:10.7202/601279ar

La multinationalisation des pétrolières canadiennes

2009· article· en· W1886116518 on OpenAlexvenueaboutno aff
Jorge Niosi

Bibliographic record

VenueL Actualité économique · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicNatural Resources and Economic Development
Canadian institutionsnot available
Fundersnot available
KeywordsPaceMultinational corporationForeign direct investmentPetroleum industryInternational tradeBusinessInvestment (military)EconomySection (typography)Economic geographyInternational economicsEconomicsGeographyPolitical scienceFinanceEngineeringMacroeconomics

Abstract

fetched live from OpenAlex

Canadian foreign direct investment in the oil and gaz industry has been growing at a very rapid pace during the seventies and early eighties. Traditionnally oriented towards the United States, it is now flowring towards the United Kingdom and other North Sea Countries, the Mediterranean, Indonesia and Australia. Increasing oil prices and profits, mainly in international operations, explain the growth of many Canadian independent. These international firms are not already truly multinationals: they produce oil and/or gaz in two to four countries, but the extent of their exploration and development activities is leading them towards a more global activity. The article is organized into three sections. In the first section the patterns of ownership and control in the Canadian industry is shown, including the emergence of local companies and the "Canadianization" process of the seventies; in the second one, the multinational expansion of Canadian firms is analyzed using agregate data; in the final section the main results are summarized and some forecasts are made on the future evolution of Canada emerging oil multinationals.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.045
GPT teacher head0.216
Teacher spread0.171 · 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 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

Citations0
Published2009
Admission routes2
Has abstractyes

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