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Record W4402517709 · doi:10.5751/es-15485-290324

Ecological agriculture and rural revitalization: toward a post-productivist countryside in Nanjing, China

2024· article· en· W4402517709 on OpenAlexvenueno aff
Danshu Qi

Bibliographic record

VenueEcology and Society · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRural development and sustainability
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsChinaAgricultureRural areaGeographyEcologyRural developmentEnvironmental protectionEnvironmental resource managementPolitical scienceEnvironmental planningEconomicsBiology

Abstract

fetched live from OpenAlex

The Chinese central government has launched the Rural Revitalization plan as a basic state policy. This has led to the growth of ecological agriculture (EA) in rural China as an approach to achieve rural development. However, whether transitions to EA can facilitate rural reinvigoration is controversial both in China and in other countries. These rural transformations are of interest to scholars, policy makers, and the public. Drawing on the theoretical framings of post-productivism, this study focuses on two villages in Nanjing and their transitions to EA, one that embarks on green agritourism and one that cooperates in organic rice production. The finding is that EA has shifted full-scale transitions away from dominant productivism to different post-productivist ends, i.e., a consumption version of the post-productivist countryside and an agriculture-revitalized version of the post-productivist countryside. This study stresses the significance of using post-productivism to characterize heterogeneous rural changes but warns of the indiscriminate match of post-productivism to resolutions for rural dilemmas. Empirical findings suggest that spatial accommodations to the farming culture and peasant lifestyle are important for retaining a vigorous rural community. A major insight is that a socio-spatial lens is necessary to refine the conceptualization of post-productivism and to understand the depth of rural sustainability transitions. This study argues that greater rural revitalization can be achieved only if more nuanced socio-cultural adaptations to spatial restructuring are considered.

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.

How this classification was reachedexpand

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 score0.082
Threshold uncertainty score0.184

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 head0.006
GPT teacher head0.207
Teacher spread0.201 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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