Evidence map›Paper›PMID 39642141›Full record

ArticlePloS one2024

Can agricultural technological progress promote China's interprovincial rural revitalization? an analytical perspective based on agricultural-scale operations.

Fei Wang, Dong Xue, Zheyi Yang

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Fei WangSchool of Economics, Henan University, Kaifeng, China.
Dong XueSchool of Economics, Henan University, Kaifeng, China.ORCID 0000-0002-2660-8589
Zheyi YangCentral China Securities, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To clarify the role of agricultural technological progress in the process of rural revitalization, this paper uses the agricultural panel data of 31 provinces in China from 2007 to 2020 to measure the Total Factor Productivity of agriculture, analyzes the impact direction and spatial spillover effect of agricultural technological progress on China's rural revitalization through the spatial Durbin model, and analyzes the threshold mechanism of agricultural technological progress on China's rural revitalization by using the panel threshold model. The results are as follows: (1) The spatial and geographical agglomeration of interprovincial rural revitalization in China has gradually weakened, and the regional imbalance has improved; (2) The progress in agricultural technology plays a positive role in promoting China's interprovincial rural revitalization, and the overall nonlinear characteristics of "first inhibiting and then promoting" are presented, and the conclusion is still robust after fully considering the factors of time, region and economic distance; (3) Further analysis shows that the impact of agricultural technological progress on China's interprovincial rural revitalization is based on the threshold constraints of land-scale operation and agricultural-industry agglomeration, and shows significant spatial heterogeneity. The inherent reason is that whether the land-scale operation entity adopts long-term investment decisions such as new agricultural technology depends on the expectation of land management risk stability, while agricultural-industry agglomeration hinders the diffusion and spillover of agricultural technology due to the exclusive characteristics of agricultural production geographical locations. Therefore, in the future of China's rural revitalization, the government should guide the large-scale operation of land and agricultural production according to local conditions to give full play to the positive spillover effect and spatial radiation capacity of agricultural technology.

Indexed as

AgricultureRural PopulationChinaHumans

Identifiers

PMID39642141
PMCPMC11623457

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.