Bibliographic record
Abstract
Between 1919–1920, while giving a series of speeches in China, John Dewey raised a doubt about Chinese education: Can Chinese education cultivate children with independent consciousness? Based on the sevenyear “Reciprocal Learning in Teacher Education and School Education between Canada and China” project, we have the answer to Dewey’s doubt. In the 1990s, Chinese education could not respond affirmatively to Dewey’s question, but after forty years of reform and development, Chinese education has taken a big step forward in cultivating children with independent consciousness. However, Canada’s school education is, at present, better at cultivating self-determined and independent children in daily life, organically integrating teaching knowledge and cultivating students, and encouraging the structured teaching characterized in the reciprocal learning project as “the forest and the trees.” The teaching framework of different disciplines in Chinese school education has more obvious constraints on education and teaching. Although the current Chinese education, from the grassroots to the government, has begun to try to break the shackles of the “discipline framework” and explore new possibilities, at the present time, it solely uses western concepts and ideological framework to conduct its own practice, especially with respect to Dewey’s experience theory. China needs to contribute its own distinctive educational concept and ideological framework, so it can truly “find a place in the world.”
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".