Desarrollo costero integrado (DCI): una alternativa de organización y desarrollo para el subsector pesquero artesanal
Bibliographic record
Abstract
Artisanal fisheries has been since long the subject of interest for social scientistsand national planningagencies because it representsoneof the last exampleofactivities forsustenance basedon the hun tingo! the wild resources. Recently, this interest has increased because the importance of the artisanal fishery for fresh food supplies for human consumption and becauses of the overexploitation of Coastal resources which has resulted in a stagnation and even a decrease of the fish consumption in poor developed communities. The possibility of utilizing the fishermen manpower, the experience in dealing with the marine environment and the use of marine technologies availables for the artisanal fishermen, requires of a conceptual frame and a coherent plan that we cali “Integrated Coastal Development” (ICD). This plan will allow to coordínate the effort of the different disciplines and elemenls involved in the development process of the artisanal fisheries sector. The disciplines are mainly from the social area of biological (bioecology) and social Sciences (e.g. sociology.anthropology, economic) and the elements are the Fisheries Resources, the Technologies utilized in the production process, and the Fishing community where this process takes place. These three elements are interrelated and interact creating new fields where concrete actions are required. A conceptual model in proposed and the elements and the interactions are described. The model proposed is being utilized as a frame for the activities that the Fisheries Program of the IDRC-Canada is implementing in collaboration with research institutions in Latin America.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| 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".