On the frontier of party-state capitalism: mapping the geopolitical economies of China’s Greater Bay Area
Bibliographic record
Abstract
• Explores the multifaceted development of China’s Greater Bay Area. • Positions the Greater Bay Area as a globalized frontier of party-state capitalism. • Problematizes the geopolitical within a geographical political economy approach. • Operationalizes a geographical variant of conjunctural analysis. • Offers a heuristic framework for analyzing geopolitical and geoeconomic dynamics. Developing and operationalizing a heuristic framework for analyzing China’s Greater Bay Area (GBA) as a conjunctural formation, the paper documents the mutual constitution and complex interweaving of geopolitical and geoeconomic relations in this cross-border regional space. Straddling an unstable fault line in the world system, the GBA is a fast-evolving and potentially volatile frontier zone of party-state capitalism. An ambitious region-building project with few, if any, precedents or templates, the GBA is a novel experiment in the production of new and recombinant spatial forms, discourses, and logics, the long-run outcomes of which are diverse and unpredictable, even as they are sure to be consequential. Thinking about the GBA requires simultaneous attention to the geoeconomic and the geopolitical, not least at the nexus of party-statecraft, multi-actor and multi-scalar governance, “security,” and new conceptions of national development. Moreover, thinking with the GBA can be taken as a (constructive, if challenging) prompt to explore new styles of methodological practice in geographical political economy, where the geopolitical has an endogenous but disruptive presence.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".