Small hydropower on and off screen: Mediating rural energy regimes in the People’s Republic of China (1958–2023)
Bibliographic record
Abstract
This paper focuses on the production and circulation of two films, The Young People in Our Village (1959) and its sequel (1963), to explore the mutual production of media and energy in socialist and post-socialist China. It first examines how The Young People was shot in rural Shanxi during the Great Leap Forward and how it presented humans’ ambition of taming water. It then details how the sequel was made in the post-famine years. The third section analyzes how the representations of small hydropower were changed and shaped by socialist politics. The last section discusses the circulation and interpretations of the two films that enabled the transition of energy aesthetics from revolutionary to sustainable. By showing the production and circulation of two films, I argue that small hydropower energized socialist cinematic production and circulation, and film, in turn, was involved in China’s energy transitions, powering the state to project its electricscape under socialism and embrace the global sustainability discourses in the twenty-first century. This paper shows how media and energy were fabricated and re-fabricated by China’s political economy and global sustainability concerns, and contributes to the current discussions on energy humanities, shifting the focus from oil to electricity and from capitalism to socialism.
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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 | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".