Correction to “Rural mechanization for equitable development: Disarray, disjuncture, and disruption”

Komang Ariyanto

Development Policy Review2026https://doi.org/10.1111/dpr.70068article
ABDC B
Weight
0.50

Abstract

Correction to “Rural mechanization for equitable development: Disarray, disjuncture, and disruption” Lewis, D., Biggs, S., & Justice, S. E. (2022). Rural mechanization for equitable development: Disarray, disjuncture, and disruption. Development Policy Review, 40(5), e12612. https://doi.org/10.1111/dpr.12612 “Zhang et al. (2017) show that, as has often been suspected, smaller farmers can compete if they are able to hire in services.” However, the corresponding bibliographic entry for Zhang et al. (2017) was inadvertently omitted from the reference list. This omission occurred during the final preparation of the manuscript and was not detected prior to publication. The correct reference that should appear in the reference list is as follows: Zhang, X., Yang, J., & Reardon, T. (2017). Mechanization outsourcing clusters and division of labor in Chinese agriculture. China Economic Review, 43, 184–195. https://doi.org/10.1016/j.chieco.2017.01.012 We apologize for this error. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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https://doi.org/https://doi.org/10.1111/dpr.70068

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@article{komang2026,
  title        = {{Correction to “Rural mechanization for equitable development: Disarray, disjuncture, and disruption”}},
  author       = {Komang Ariyanto},
  journal      = {Development Policy Review},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/dpr.70068},
}

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Correction to “Rural mechanization for equitable development: Disarray, disjuncture, and disruption”

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.