Impact of Dairy Imports on Raw Milk Production Technology Progress in China
Bibliographic record
Abstract
China's dairy product import volume and output continue to grow rapidly, and to a certain extent, it will form a substitute for the Chinese dairy market. Therefore, it is necessary to study the impact of the import of dairy products on the technological progress of raw milk production in China. Using the data from 2005 to 2017, this paper uses the DEA model and the input-output model to analyze the impact of China's dairy product imports on the technological progress of raw milk production. The model results show that: (1) there are differences in the technological content of dairy products from different importing countries; (2) The total technological content of imported dairy products hinders the improvement of the technological progress index of small, medium and large-scale production of raw milk in China, and has the most prominent negative impact on the technological progress of large-scale raw milk production in China; (3) The technological content of dairy products imports from New Zealand, Australia, Germany, the Netherlands and other countries can help improve the technological progress index of China's moderate-scale production of raw milk, while importing countries from the United States, Canada and other countries hinder it.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".