The Rise of China's Global Middle Class in an International Context
Bibliographic record
Abstract
Abstract We estimate the size of the global middle class in China and 33 other countries and analyze China's expanding middle class in an international context. The “global middle class” is defined in terms of being neither poor nor rich in the developed world. China's global middle class has grown rapidly and has been catching up with the middle class in developed countries. By 2018 China's global middle class constituted 25 percent of China's population; in absolute size it was nearly double the size of the global middle class in the US and was similar in size to that of Europe. Cross‐country analysis of the relationship between the middle‐class share of the total population and GDP per capita reveals an inverted‐U pattern. China is not an outlier from the cross‐country pattern but the speed with which its middle‐class has expanded is unusual. The only other countries with similarly large, rapid expansions of the middle class are transition economies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 teacher head, 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".