Adorno and Marcuse’s critical analysis of media culture and its implications for media education in China
Bibliographic record
Abstract
This thesis explores the educational insights in Adorno and Marcuse’s critical theory and discusses its implication for media education in mainland China. There are three main areas where their critical philosophy can strengthen critical pedagogy and media education in contemporary China: their analysis of the nature and effects of media culture, their critique of the educational system, and their aesthetic educational method with the aim of cultivating critical thinking. Given mass media’s significant role in shaping people’s understanding towards different social affairs, my thesis challenges the current technical mode of media education in mainland China, which stresses too much the teaching of technical knowledge while ignoring the cultivation of the ability to think critically. I also discuss the educational methods that teachers may use to cultivate critical thinking based on Adorno and Marcuse’s philosophy of education. As a philosophical inquiry, my thesis concentrates on theoretical analysis. By applying Adorno and Marcuse’s critical philosophy to contemporary China, I not only analyze the insights of their philosophy for understanding the current society, but also suggest that some opinions in their theory should be changed within the contemporary social and cultural context.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".