Transnational Class Formation? Globalization and the Canadian Corporate Network
Bibliographic record
Abstract
The issue of transnational class formation has figured centrally in recent debates on globalization. These debates revolve around the question of whether or not new patterns of cross-border trade and investment have established global circuits of capital out of which a transnational capitalist class has emerged. This paper takes up the notion of transnational class formation at the point of corporate directorship interlocks. Using Canada as a case study, it maps the changing network of directorship interlocks between leading firms in Canada and the world economy. In particular, the paper examines the role of transnational corporations (TNCs) in the Canadian corporate network; the resilience of a national corporate community; and new patterns of cross-border interlocking amongst transnational firms. Through this empirical mapping, the paper finds a definite link between investment and interlocking shaping the social space of the global corporate elite. Corporations with a transnational base of accumulation tend to participate in transnational interlocking. While national corporate communities have not been transcended, transnational firms increasingly predominate within them, articulating national with transnational elite segments. This new network of firms reconstitutes the corporate power bloc and forms a nascent transnational capitalist class.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".