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Record W2091603524 · doi:10.7202/021351ar

The spatial concentration of domestic and foreign multinational corporate headquarters in Canada

2005· article· en· W2091603524 on OpenAlexvenueaboutno aff
R. Keith Semple

Bibliographic record

VenueCahiers de géographie du Québec · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsMultinational corporationLeverage (statistics)PoliticsMainstreamCorporationPower (physics)BusinessEconomicsMarket economyEconomyEconomic geographyEconomic systemInternational tradePolitical scienceFinanceLaw

Abstract

fetched live from OpenAlex

This paper examines the spatial concentration of corporate power in Canada and measures the regional imbalances that are presently so noticeable. Furthermore, since corporate power in many instances is becoming ever more synonomous with foreign control the research notes not only the spatial concentration of this control but the sectors of the economy that are effectively under foreign domination. The paper intimates that those areas that house the headquarters of the giant multinational corporation are the net beneficiaries of the monetary strength, political leverage and technical expertise that these establishments have available to bring to bear in a wide variety of economic and political situations. It follows that if an area benefits from the presence of large corporations, and these same corporations are concentrated into particular regions then the possibility arises that certain "have-not" regions will have cause to feel left out of the mainstream of decision making that characterizes the economic and political well being of the entire nation. It appears that this joint problem of spatial concentration and sectoral domination by domestic as well as foreign corporations may be one of the many catalysts fostering both present-day Canadian nationalism and overt provincial sectionalism.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.163
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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 designObservational
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

Citations14
Published2005
Admission routes2
Has abstractyes

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Same venueCahiers de géographie du QuébecSame topicCultural Industries and Urban DevelopmentFrench-language works237,207