Exploring the Relationship Between Fishing Actors and Network Prominence in information-sharing Networks in Jamaican small-scale Fisheries
Bibliographic record
Abstract
Abstract Information-sharing social networks support the adaptive capacity of small-scale fishers in the face of social and environmental change by allowing them to increase access to unique knowledge critical to their fishing success. The facilitation of information exchange may be supported and influenced by persons in key positions. Within these networks, centralized actors often control the flow and access to information. We take a descriptive approach to explore the relationship between fishing role and actor prominence within information-sharing networks in Jamaica. We hypothesized that fishing captains – given their perceived legitimacy and formal and informal authority – would be more prominent in information-sharing networks, and the information they shared would be perceived as more trustworthy and influential than that of non-captains. We collected personal social networks of fishers (n = 353) on 20 fishing beaches across four parishes in Jamaica using structured questionnaires. We found low centralization and density scores across the parishes, suggesting an even distribution of actor centrality. Our results show that non-captains play a more prominent role in information sharing than fishing captains in one parish suggesting that captains and non-captains play similar roles in facilitating information, and that differences lie in whether fishers perceive the shared information as trustworthy and influential in their fishing decisions and not the prominence of the actor. These findings contribute to understanding the various adaptive strategies fishers develop to meet growing social-ecological changes in small-scale fisheries. Identifying key informants in prominent positions can also support the development of more effective strategies to communicate and share information across communities.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".