China in and Beyond the Headlines.
Bibliographic record
Abstract
Introduction: China, the United States, and Convulsive Cooperation Lionel M. Jensen and Timothy B. Weston Part I: In the Headlines Chapter 1: Jousting with Monsters: Journalists in a Rapidly Changing China David Bandurski Chapter 2: Youth Culture in China: Idols, Sex, and the Internet Jonathan S. Noble Chapter 3: Dismantling the Socialist Welfare State: The Rise of Civil Society in China Jessica C. Teets Chapter 4: Mutually Assured Destruction or Dependence? U.S. and Chinese Perspectives on China's Military Development Andrew S. Erickson Chapter 5: China's Environmental Tipping Point Alex L. Wang Chapter 6: China's Historic Urbanization: Explosive and Challenging Timothy B. Weston Chapter 7: The Worlds of China's Intellectuals Timothy Cheek Chapter 8: Why Does China Fear the Internet? Susan D. Blum Part II: Beyond the Headlines Chapter 9: Producing Exemplary Consumers: Tourism and Leisure Culture in China's Nation-Building Project Travis Klingberg and Tim Oakes Chapter 10: Professionals and Populists: The Paradoxes of China's Legal Reforms Benjamin L. Liebman Chapter 11: The Decriminalization and Depathologization of Homosexuality in China Wenqing Kang Chapter 12: The Evolution of Chinese Authoritarianism: Lessons from the Arab Spring Orion A. Lewis Chapter 13: Culture Industry, Power, and the Spectacle of China's Confucius Institutes Lionel M. Jensen Chapter 14: Tensions and Violence in China's Minority Regions Katherine Palmer Kaup Chapter 15: An Unharmonious Society: Foreign Reporting in China Gady Epstein Afterword: What Future for Human Rights Dialogues? John Kamm
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.045 | 0.004 |
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".