An examination of challenges and issues facing sustainable forest management and forest certification in China
Bibliographic record
Abstract
This study investigated the challenges facing the adoption of sustainable forest management (SFM) and forest certification in China. To achieve this goal, the perceptions of four influential direct and indirect stakeholders were examined to reveal the awareness, understanding, interest, motivation, and barriers to adopting SFM and forest certification. The four stakeholders consisted of Chinese small-scale forest farmers who have received small forest land from the collectives through the new forest tenure reforms, Chinese market officials working for forestry property markets, Chinese wood products manufacturers, and Canadian wood products retailers. In addition, the new forest tenure reforms and their supporting mechanisms, including forestry property markets, were assessed in terms of their impacts on the promotion of SFM and certification in China. The study revealed general low levels of awareness and understanding about SFM and forest certification amongst various stakeholders in China, with forest farmers having particularly low awareness. Several challenges to the adoption of SFM and forest certification in the period before the new forest tenure reforms were identified by the small-scale forest farmers, including insecure and unclear forest tenure, inconsistent forest policies, inadequate finances, under-developed infrastructure and transport system, and lack of efficient knowledge and technical transfer. Market officials were found to have limited knowledge of SFM and forest certification but their role in educating forest farmers and promoting SFM and certification is particularly important, as government support is considered to be critical to the early and rapid uptake of SFM and certification in China. Chinese manufacturers expressed immense interest in forest certification despite the identified barriers. From their perspectives, the biggest barrier was the lack of market demand for certified wood products. Canadian retailers were chosen as a substitute of Chinese retailers to gain insights into how a more advanced market for certified wood products might evolve, and how the demand might evolve in China. The new forest tenure reforms and forestry property markets are likely to overcome many of the challenges and enable forest farmers to adopt SFM and certification. That said, the widespread adoption of SFM and certification amongst various stakeholders has a long way to go.
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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 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".