Opportunities, Dilemmas and Innovative Paths for Youth Sports Training in Chengdu under the "Double Reduction" and "Double Increase" Policies
Bibliographic record
Abstract
This article uses research methods such as literature, expert interviews and field visits to study the development of youth sports training in Chengdu. This paper conducts research on how the two policies of "double reduction" and "double increase" change the operating environment of the youth sports training market in Chengdu, and how these changes affect the development prospects of the market. The study found that this policy has brought new development opportunities to the youth sports training market in Chengdu, but it also faces some challenges. To address these challenges, we have proposed a series of innovative paths, including measures such as improving government supervision mechanisms, optimizing market management, unifying coaching qualification certification standards and standardizing coaching promotion channels, and strengthening school-enterprise cooperation. We hope that through this research, we can provide valuable reference for relevant policymakers and training institutions, and provide predictions for future market development trends.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".