How do environmental regulations and financial support for agriculture affect agricultural green development? The mediating role of agricultural infrastructure
Bibliographic record
Abstract
Environmental regulations and financial support for agriculture have been respectively proved as important means to break through the dilemma of agricultural green development in China. While their interactive influences on agricultural green development are rarely focused, as well as the mediation mechanism. This paper provides an interactive perspective by exploring the direct and indirect mechanisms affecting the relationship between environmental regulations, financial support for agriculture, and agricultural green development, among which the mediating effects of agricultural infrastructure, are further discussed. Based on the provincial panel data for China from the year 2000 to 2021, this paper constructs a fixed effect model, mediating effects model, and threshold panel model to empirically test the direct and indirect effects of environmental regulations and financial support for agriculture on agricultural green development. The results show that: (1) The full sample of agricultural green development in China shows an M-shaped trend, environmental regulations and financial support for agriculture show spatial and temporal heterogeneity among regions. (2) Environmental regulations, financial support for agriculture, and their interaction all have positive effects on agricultural green development, while their interactive effect is greater. (3) Agricultural power facilities not only significantly mediate the relationship between financial support for agriculture and agricultural green development, but also play a mediating role in the positive effect of the interaction between environmental regulations and financial support on agricultural green development. While rural transportation facilities only significantly mediate the positive effect of the interaction between environmental regulations and financial support for agriculture on agricultural green development. (4) Heterogeneity analysis results show that the effect of the interaction between environmental regulations and financial support for agriculture on agricultural green development is greatest in agricultural optimized developing areas; however moderate developing areas are insignificant. This research contributes to understanding how environmental regulations and financial support for agriculture affect agricultural green development and extends the mediating role of agricultural infrastructure in their relationships.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".