Educational Policy Development in China in the 21st Century: A Multi-Flows Approach
Bibliographic record
Abstract
Recently China has miraculously transformed itself from a learner in the 20th century to a re-rising leader of educational excellence. The enduring policy endeavors over the past few decades have largely enabled China as the largest educational system in the world move to a recently emerging status as a global leader of educational improvement, recognized and appreciated with admiration by many traditionally advanced countries. The two authors intend to offer a snapshot of the China miracle of educational development in terms of public policies since the turn of the 21st century. With a Multi-Flows Approach constructed from Csikszentmihalyi’s idea of “flow”, this paper investigates the complexity and dynamism of three policy streams, i.e., basic education, teacher education and higher education. It is concluded from the literature review that central to China’s key policy actions in recent decades are four core themes, i.e., equality in terms of a democratic mission of education for every citizen, quality in terms of individual and social productivity, efficiency as a national priority based on practicality, and rejuvenation of the state for nation-building and global status. Educational policy development in China since the new century is thus examined with economic, political, cultural and international flows, each presenting a colorful jigsaw puzzle that is not easily tessellated by other flows. The authors argue that the different focus of flows and beyond can benefit policy communities in the world with varied directions for educational change resulting in significant improvement while none of them should be seen as a single force in solely shaping educational policy development without the convergence of other forces. This implies that for any public policy in education policymakers, implementers and other stakeholders must ensure a comprehensive consideration of the interdependent, converging effects of these forces to prioritize and maximize their outcomes, which may be easily missed by any single force of them. The implications from this paper sheds new light on policy studies in education in China and globally, and the learner-provider dynamism of educational development in a post-colonial 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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".