Theorizing socio-environmental reproduction in China’s countryside and beyond
Bibliographic record
Abstract
Over the past four decades, pollution and other forms of environmental degradation have radically transformed China’s landscape. So have the ambitious greening policies implemented to tackle these problems. During the same period, an enormous gap in wealth and amenities has arisen between the modernizing cities and rural areas, the latter playing an important, and often ignored, role in China’s environmental project. This paper identifies two paradoxical processes transforming rural environments: the mobilization of rural efforts to green the nation and the ruralization of pollution. While seemingly contradictory, both processes illustrate how the rural is expendable and malleable to state interests. This article proposes the concept of socio-environmental reproduction to theorize the environmental paradox in which many rural communities find themselves in contemporary China, as their environmental work and sacrifices sustain economic and political systems. This concept builds on the work on social reproduction by feminist scholars, particularly those who have sought to integrate the environment into their analyses. This paper proposes to expand the concept to include all the environmental work and sacrifices that certain people are asked to make to fuel the economic system, preserve political stability, and protect privileged spaces from pollution. As a whole, this article shows how China’s rural–urban divide is constitutive of the country’s environmental project and how national greening initiatives enable uneven development. Furthermore, this case foreshadows what will likely occur elsewhere as countries seek to green themselves. As the ecological era unfolds in China and elsewhere, it exposes how deep social divides are mobilized to fulfill environmental objectives. This paper theorizes the environmental work and sacrifices that risk falling on the shoulders of the most vulnerable.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.023 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".