Comparison of Orchid Conservation Between China and Other Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Global attention is highly focused on biodiversity conservation. Various countries are actively implementing relevant conservation measures. To advance these efforts in China, it is essential to understand global conservation actions. The orchid family, one of the most diverse groups of flowering plants, has become a “flagship” group for plant conservation. In this study, we summarized 3418 policies and regulations related to orchid conservation in 45 countries. We found that orchid conservation actions in various countries have focused on in situ conservation, with 1469 policies and regulations issued for nature reserves, while ex situ conservation has been seriously neglected, with only seven relevant regulations. Most developing countries have experienced an increase in orchid conservation actions, while developed countries have plateaued. We amassed 370 non-governmental organizations (NGOs) for orchid conservation. At present, the total number of policies and regulations for orchid protection in China is approximately 84, with 67 issued since 2000. Two non-governmental organizations have been established for orchid conservation. Although the benefit of orchid conservation in China is significant, it still requires continuous improvement compared to many other countries. We recommend that the Chinese government draws on the experiences of the United States, Canada, and Australia in areas such as policy and regulation formulation, optimization of non-governmental organizations, and implementation of related conservation projects. Through learning and collaboration, challenges can be transformed into opportunities for development.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it