The impact of China's millennium labour restructuring program on firm performance and employee earnings<sup>1</sup>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Around the turn of the century, China experienced perhaps the largest labour restructuring program in the world. This paper uses a new dataset of Chinese industrial enterprises to examine what leads to downsizing, and tries to understand the effects of labour downsizing on firms’ technical efficiency, financial performance and employee wages. We find that downsizing is more prevalent in state‐owned enterprises (SOEs), and is more likely when enterprises are older, larger and have higher excess capacity. For both SOEs and private firms, downsizing is more likely when the prices of their products drop, but private firms respond more dramatically. Moreover, downsizing has serious short‐term costs in terms of total factor productivity (TFP). For mild downsizing, private firms suffer more deterioration in productivity. The distribution of surplus after downsizing is more favourable to labour in SOEs. For severe downsizing, both SOEs and private firms exhibit lower TFP growth with similar magnitudes. Our findings imply that private firms emphasize profit goals, while SOEs place a greater weight on labour protection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it