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Record W2063205517 · doi:10.1163/156913303100418753

The Canadian Corporate Network in Comparative Perspective

2003· article· en· W2063205517 on OpenAlexaboutno aff
Michael Ornstein

Bibliographic record

VenueComparative Sociology · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCooperative Studies and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsSubordination (linguistics)Cohesion (chemistry)Perspective (graphical)BusinessAccountingComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract This paper compares the network of Canadian corporate directorships to the networks of ten rich nations described by Stokman, Ziegler, and Scott. The analysis tests claims about the exceptional weakness and disorganization of the Canadian capitalist class, due to high foreign ownership and dependence on resource extraction. The Canadian network is neither unusually sparse nor fragmented; there is no pronounced cleavage between, or subordination of, non-financial corporations to financial corporations; nor do the foreign-controlled corporations constitute an alternative centre or fragment of the network. It resembles the networks of countries such as Germany and France. The findings are consistent with the managerial and class cohesion models of the network, which emphasize its unity.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.091
Threshold uncertainty score0.659

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0100.016
Science and technology studies0.0090.006
Scholarly communication0.0090.004
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.000

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 head0.118
GPT teacher head0.292
Teacher spread0.174 · 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 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

Citations3
Published2003
Admission routes1
Has abstractyes

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