Opportunity for marine fisheries reform in China
Bibliographic record
Abstract
China's 13th Five-Year Plan, launched in March 2016, provides a sound policy platform for the protection of marine ecosystems and the restoration of capture fisheries within China's exclusive economic zone. What distinguishes China among many other countries striving for marine fisheries reform is its size-accounting for almost one-fifth of global catch volume-and the unique cultural context of its economic and resource management. In this paper, we trace the history of Chinese government priorities, policies, and outcomes related to marine fisheries since the 1978 Economic Reform, and examine how the current leadership's agenda for "ecological civilization" could successfully transform marine resource management in the coming years. We show how China, like many other countries, has experienced a decline in the average trophic level of its capture fisheries during the past few decades, and how its policy design, implementation, and enforcement have influenced the status of its wild fish stocks. To reverse the trend in declining fish stocks, the government is introducing a series of new programs for sustainable fisheries and aquaculture, with greater traceability and accountability in marine resource management and area controls on coastal development. As impressive as these new plans are on paper, we conclude that serious institutional reforms will be needed to achieve a true paradigm shift in marine fisheries management in China. In particular, we recommend new institutions for science-based fisheries management, secure fishing access, policy consistency across provinces, educational programs for fisheries managers, and increasing public access to scientific data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".