Bibliographic record
Abstract
Readers in the China field will eagerly turn to Susan Greenhalgh's latest work for an indepth treatment of the formation of China's one-child policy, but they will find much more here.This volume exemplifies some of the strongest work in the anthropology of China in the present day, pulling ethnographic research in China into the mainstream of central debates in contemporary anthropology. 2Greenhalgh makes two broad types of knowledge claim in this volume, both based on diverse ethnographic techniques.First, she claims to explain, in considerable ethnographic and analytic depth, the specific policy-making process through which China arrived at the one-child-percouple formulation during critical months in 1979-80.This is a significant addition to the comprehensive work she co-authored with Edwin Winckler, Governing China's Population: From Leninist to Neoliberal Biopolitics (Berkeley, University of California Press, 2005).In the present work she examines three competing scientific groups and their positions, as well as the political and scientific means through which the contention unfolded.These comprised the population studies group at People's University, led by Liu Zheng and others; the cybernetic missile control scientists led by Song Jian; and the critical voice of Liang Zhongtang of the Shanxi Party School.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".