Toilet revolution in China
Bibliographic record
Abstract
The wide-spread prevalence of unimproved sanitation technologies has been a major cause of concern for the environment and public health, and China is no exception to this. Towards the sanitation issue, toilet revolution has become a buzzword in China recently. This paper elaborates the backgrounds, connotations, and actions of the toilet revolution in China. The toilet revolution aims to create sanitation infrastructure and public services that work for everyone and that turn waste into value. Opportunities for implementing the toilet revolution include: fulfilling Millennium Development Goals and new Sustainable Development Goals; government support at all levels for popularizing sanitary toilet; environmental protection to alleviate wastewater pollution; resource recovery from human waste and disease prevention for health and wellbeing improvement. Meanwhile, the challenges faced are: insufficient funding and policy support, regional imbalance and lagging approval processes, weak sanitary awareness and low acceptance of new toilets, lack of R&D and service system. The toilet revolution requires a concerted effort from many governmental departments. It needs to address not only technology implementation, but also social acceptance, economic affordability, maintenance issues and, increasingly, gender considerations. Aligned with the ecological sanitation principles, it calls for understanding issues across the entire sanitation service chain. Public-private partnership is also recommended to absorb private capital to make up the lack of funds, as well as arouse the enthusiasm of the public.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".