Opportunities for the Progression of Farm Animal Welfare in China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As the world's largest livestock producer, China has made some progress to improve farm animal welfare in recent years. Recognizing the importance of locally led initiatives, this study aimed to engage the knowledge and perspectives of Chinese leaders in order to identify opportunities to further improve farm animal welfare in China. A team of Chinese field researchers engaged 100 senior stakeholders in the agriculture sector (livestock business leaders, agriculture strategists and intellectuals, government representatives, licensed veterinarians, agriculture lawyers, and national animal welfare advocates). Participants completed a Chinese questionnaire hosted on a national platform. The raw data responses were then translated and subjected to qualitative and quantitative analyses from which themes were built and resulting recommendations were made. The findings of this study urge emphasis on the ties between improved animal welfare with food safety, product quality, and profit, and demonstrate the existence of animal welfare opportunities outside of the immediate introduction of specific animal protection legislation. The resulting applications are anticipated to be of strategic use to stakeholders interested in improving farm animal welfare in China.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it