Bibliographic record
Abstract
This book discusses the political economy of the SARS epidemic and its impact on human resources in East Asia, as it occurred in 2003. The epidemic spread from the People’s Republic of China, to Hong Kong, Singapore and Taiwan, amongst other countries in East Asia and as far away as North America, particularly Canada, the EU and elsewhere. The book looks first at earlier precedents, such as the Black Death and the way in which the potential threats of the recent epidemic were diffused across the world in ‘instant news’ reports; examining why it was dubbed the first ‘global epidemic’ due to its media coverage and how far the threat started a psychological ‘tsunami’ of fear and panic. Next, it examines the anticipated economic consequences arising from this phenomenon and how it affected the business of everyday life, market behaviour and human resources in the Chinese and Overseas Chinese economies. It focuses in particular detail on the cases of the PRC, Hong Kong, Singapore and Taiwan. It concludes with a discussion of the issues involved and lessons to be learnt, and draws conclusions both for theory and practice vis-à-vis future pandemics that may threaten the global economy in the coming decade and the public policy issues involved
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".