Strategic coupling, state capitalism, and the shifting dynamics of global production networks
Bibliographic record
Abstract
Abstract This paper critically evaluates the relationship between state capitalism and “strategic coupling” within global production networks (GPN). It underscores specifically the lack of cases on “coupling” involving state‐owned enterprises (SOEs) from developing countries and city‐regions within developed countries. Most existing studies focus on the connection between regions in developing economies with lead firms originating from developed economies. This leaves open a conceptual and empirical gap as SOEs from developing countries (like those of China and India) are (1) increasingly becoming lead firms in their own right and (2) investing in developed economies. Against this backdrop, this paper highlights conceptually significant points from the acquisition of Nexen, a Canada‐based oil and gas TNC, by CNOOC, a large Chinese SOE, and argues for a fresh research agenda that examines the strategic coupling of lead firms that are also SOEs from developing economies.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.009 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".