Bibliographic record
Abstract
Introduction It has been more than three decades since China started to transform its economy institutionally and structurally. The economic transformation has stimulated rapid economic growth in both GDP and personal incomes. From 1978 to 2007 the annual growth of GDP averaged close to 10 percent and that of household per capita income more than 7 percent. The rate of economic growth was even more impressive in later years, including the period under study in this chapter. From 2002 to 2007, annual growth of GDP was 11.6 percent and of rural and urban household per capita income 6.8 and 9.6 percent, respectively. Although the reforms were successful in promoting GDP growth, by the early 2000s, concerns about rising disparities and sustainability prompted the government to announce a new development strategy emphasizing sustainable, harmonious growth. A new policy program, referred to as the “scientific outlook on development” ( kexue fazhanguan ), or the “Hu-Wen New Policies” ( Hu-Wen xin zheng ), aimed to promote development in urban and rural areas, reduce regional disparities, narrow income inequalities, and establish a social protection network with broad coverage over most of the population. As discussed in Chapters 1 and 5, the new policy program contained a series of pro-rural measures. These included the elimination of agricultural taxes, which had been in place for almost sixty years, and the adoption of new farm subsidies, for example, for grain production, purchase of agricultural inputs, and farm insurance (Lin and Wong 2012). By the end of 2007, Chinese rural households were no longer paying agricultural taxes, and total agricultural production subsidies from the central government exceeded 50 billion yuan (Lin and Wong 2012; Ministry of Agriculture 2007).
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.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.291 | 0.157 |
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".