Bibliographic record
Abstract
China's leadership has spoken for much of the past decade about the need to ‘rebalance’ the economy and put it onto a different growth path, with domestic consumption as a leading driver of growth. This paper analyses two questions in this regard. The first is how to best to characterise China's existing growth path. China is typically considered to be an export-led economy par excellence. However, the results of the growth accounting approach are reviewed which question this characterization. Second, if China wishes to shift growth paths then, on the basis of insights generated by post-Keynesian growth models, I conclude that a shift to a consumption-driven (wage-led) growth path may be much more problematic than is generally assumed. Résumé Durant la dernière décennie, les autorités chinoises n'ont cessé de communiquer sur la nécessité de rééquilibrer l'économie chinoise et de la mettre sur une différente trajectoire de développement, en faisant de la consommation domestique une des sources majeures de la croissance. Cet article en explore deux problématiques. D'abord, on s'interroge sur la meilleure façon de caractériser l'économie chinoise. En effet, alors que la Chine est communément perçue comme un pays exportateur, des études récentes démontrent le contraire. Ensuite, on explore les autres trajectoires de développement susceptibles d'être empruntées par la Chine. Il semble, sur la base des conclusions des modèles de croissance post-keynésiens, qu'un changement de trajectoire de croissance en Chine serait plus problématique que ce qui est généralement admis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".