Bibliographic record
Abstract
The Guidelines provide a special focus on information and knowledge sharing and its current and potential role in supporting implementation of the Code of Conduct for Responsible Fisheries. They expand on relevant principles and standards set forth in the Code and make practical suggestions about ways to ensure that this role can be enhanced. The issues involved in the flow of information between different stakeholder groups include topics as diverse as information policy frameworks and information and communication technology infrastructure, hence coverage is introductory. Some of the constraints involved in the cycle from the creation, production, dissemination and availability of information and knowledge to its effective use and sharing by the present generation as well as its preservation for the future are presented. The special circumstances and requirements of stakeholders in developing countries are recognized in accordance with Article 5 of the Code. A separate chapter on small-scale fisheries and aquaculture looks in more detail at the special situation and information needs of the sub-sector. The Guidelines aim to foster a better understanding of the issues involved to ensure that stakeholders obtain the essential information that they need and that they make available their own information and knowledge for the public good. (PDF contains 115 pages)
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.018 | 0.020 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.055 | 0.025 |
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".