Use of Graph Model for the Resolution of Conflicts between Fishers of the Amazonian Floodplain Lakes
Bibliographic record
Abstract
We evaluated the GMCR II (Model of the Graphs for Conflict Resolution) as a tool for the identification of fishing management strategies that could be possible solutions for fishing conflicts in the floodplain lakes of the Central Amazon. The procedures of this software are based on the Graph Theory, a mathematical approach derived from the Game Theory. In our modeling, the players were IBAMA (environmental agency in Brazil), commercial fishers and subsistence fishers. The GMCR II demonstrated that when IBAMA adopts the strategy of restriction of some fishing gear in floodplain lakes, the resolution of the conflict between fishers is more likely to happen. We also conclude that the use of a mathematical approach, by the employment of the GMCR II, would be an important tool for approaching conflict situations but that its use needs to be followed by other methodologies, mainly participative programs.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".