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Record W4387530403 · doi:10.1080/09640568.2023.2263637

How do environmental regulations and financial support for agriculture affect agricultural green development? The mediating role of agricultural infrastructure

2023· article· en· W4387530403 on OpenAlex
Lingyan Xu, Jing Jiang, Jianguo Du

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Environmental Planning and Management · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEnergy, Environment, Economic Growth
Canadian institutionsInstitute on Governance
FundersSocial Science Foundation of Jiangsu ProvinceNational Social Science Fund of ChinaNational Natural Science Foundation of China
KeywordsAgricultureBusinessPanel dataGreen developmentChinaMediationStructural equation modelingEconomicsGeographyPolitical science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.172
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it