The Logic of Survival Culture of Rural Collective Action in China: A Preliminary Study Framework
Bibliographic record
Abstract
This paper focuses on the formation of the Water Association in River Village after the People’s Commune through a framework of “Understanding Knowledge”. It starts from the perspective of rural people's daily life, using a narrative explanation way of the Experience Ethnography. In the life history between written history and oral history, the paper shows a picture of “collective in the rural society” to everyone. And then, the paper discusses the logic of collective on its generation process in the view of culture from the perspective of people’s daily life. Key words: Chinese Rural; Daily Life; Collective Actions; Survival Culture Resume: Cet article se concentre sur la formation de l'Association de l'eau dans le Village de riviere apres la Commune populaire a travers un cadre de connaissance de comprehension. Il commence par la perspective de la vie quotidienne des populations rurales, en utilisant un moyen d'explication narrative de l'experience ethnographique. Dans l'histoire de la vie entre l'histoire ecrite et l'histoire orale, l'etude montre une image des actions collectives dans la societe rurale a tout le monde. Et puis, le document examine la logique des collectives dans son processus de generation d'un point de vue culturel a partir de la perspective de la vie quotidienne des gens. Mots-cles: Chine Rurale; Vie Quotidienne; Actions Collectives; Culture De Survie
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".