The Basic Rules of Marxist Philosophy Say “No” to the Long-standing English Teaching: Taking China’s Large-Scale English Teaching for Example
Bibliographic record
Abstract
Abstract: This paper, by using the basic rules of Marxist philosophy, has discussed the universal natural rules violated by China’s large-scale English teaching and researching, with the purpose of calling experts' and scholars' attention to the question below: is it true that, for a long time, there have been some large faults in China’s large-scale English teaching at all levels of our education, and that the teaching orbit and the researching orbit have been mistaken and misleading? On the basis of more than 30 years’ probing, researching and experimenting, the author has put forward a suggestion that we should adopt a new teaching and researching method of imitating thinking orbit, by taking advantage of the natural rules existing inside and outside the brain. The author expects that, in China’s English teaching and researching circle, there appears a discussion of “Practice-is-the-sole-criterion-of-truth”. Key words: The Basic Rules of Philosophy; Negation; Thinking Imitating; Practical Values
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.023 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".