Bibliographic record
Abstract
It has been said that Mao Zedong always disagreed with his intellectual comrades. In his career, he clashed with many leading revolutionaries in terms of ideology formation and/or policymaking. He caused irreparable damage to educated revolutionaries through his anti-intellectual stance. By looking into his ideological development, culminating in what is conventionally dubbed “Mao Zedong Thought,” I argue that despite his conflicts with many communist intellectuals, Mao shared with them similar concerns and ideas. In so doing, I shall analyze his theorization about the role of communist intellectuals in the Revolution. This dimension is chosen for two reasons. First, it is most germane to Mao and his colleagues because they always assumed that they were members of this coterie. And second, Mao and other communist thinkers drew on their experiences to contemplate what they as the educated revolutionary elite should do in order to accomplish their mission of revolutionizing China. As a result, Mao's discussion on revolutionary intellectuals reflects the themes defining Mao Zedong Thought. This chapter is divided into three sections. First, to show that communist intellectuals laid the foundation for Mao Zedong Thought, I shall examine the ideological milieu of the communist Revolution: I focus on how revolutionary intellectuals contemplated their own role in the Revolution generally and in the rural Revolution especially in view of Mao's largely rural career.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".