Bibliographic record
Abstract
In the late 1970s China embarked upon a period of wide-ranging reforms, amongst which the Economic Reforms and the Open Door Policy can be counted. This article is to investigate ensuing patterns and trends in the interCity per-capita income distribution in China in the 1990s, after the reforms had been in place for a decade. The following methodologies are used: inequality and polarization indices, to illustrate basic trends, stochastic dominance techniques, to provide unambiguous economic welfare and poverty comparisons across regions and over time, and transition probability techniques and polarization/ convergence tests, to study the long-run evolution of income distributions for Cities. The results suggest a significant welfare improvement and concomitant reduction in the poor status of Cities for all regions, with strict welfare dominance of the Eastern Coastal Area over the interior. They also indicate a significant convergence trend in the center (especially in the Eastern Coastal Area) together with a divergence trend in both lower and upper tails of interCity income distributions. Economic reform and globalization effects in the coastal area have driven convergence in the central mass; divergence in both tails of the distribution stems from the growing coastal-inland gap due to the unbalanced pace of the economic reform and globalization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".