Global to Local: International Conferences and Environmental Education in The People’s Republic of China
Bibliographic record
Abstract
This paper describes research exploring the relationship between international recommendations for environmental education (EE) developed at United Nations (UN) Conferences and non-formal EE initiatives undertaken by Chinese civil organisations. Specifically, the research assesses how international recommendations may have influenced the development and the delivery of Chinese non-formal EE programmes. Data were collected and analysed through an interpretivist perspective and involved: (1) historical and content analysis of recommendations from UN-sponsored conferences related to EE; (2) interviews with academics, Chinese officials and Chinese civil organisations representatives; and (3) document analysis of academic literature as well as governmental and non-governmental publications related to EE. Findings were interpreted in terms of patterns of influence and consistency. Results show that international recommendations for EE did not directly influence non-formal EE efforts in China; nevertheless, some of these efforts seem consistent with international recommendations. Based on these results, questions are raised about the nature of communication between participants in international deliberations and practitioners at the local level. Suggestions are made for improving this communication.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".