Voluntary Participation in Regional Fisheries Management Council Meetings
Bibliographic record
Abstract
Insufficient and unrepresentative participation in voluntary public hearings and policy discussions has been problematic since Aristotle's time.In fisheries, research has shown that involvement is dominated by financially resourceful and extreme-opinion stakeholders and tends to advantage groups that have a lower cost of attendance.Stakeholders may exhibit only one or all of these traits but can be still similarly advantaged.The opposites of these traits tend to characterize the disadvantaged, such as the middle-ground opinions, the less wealthy or organized, and the more remote stakeholders.Remoteness or distance is the most straightforward and objective of these characteristics to measure.We analyzed the New England Fishery Management Council's sign-in sheets for 2003-2006, estimating participants' travel distance and associations with the groundfish, scallop, and herring industries.We also evaluated the representativeness of participation by comparing attendance to landings and permit distributions.The distance analysis showed a significant correlation between attendance levels and costs via travel distance.These results suggest a potential bias toward those stakeholders residing closer to meeting locations, possibly disadvantaging parties who are further and must incur higher costs.However, few significant differences were found between the actual fishing industry and attendee distributions, suggesting that the geographical distribution of the meeting attendees is statistically similar to that of the larger fishery.The interpretation of these results must take into consideration the limited time span of the analysis, as policy changes may have altered the industry make-up and location prior to our study.Furthermore, the limited geographical input of stakeholders may lend bias to the Council's perception of ecological and social conditions throughout the spatial range of the fishery.These factors should be further considered in the policy-formation process in order to incorporate a broader range of stakeholder input.
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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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".