The role of a multi-jurisdictional organization in developing ecosystem-based management for fisheries in the Great Lakes basin
Bibliographic record
Abstract
One of the mandated charges to the Great Lakes Fishery Commission is to facilitate the coordination of Great Lakes fishery management across jurisdictions. To do this, the Great Lakes Fishery Commission organized annual lake committee meetings among Great Lake fishery professionals since 1964. Our objective was to describe the role of the Great Lakes Fishery Commission in facilitating communication among fishery jurisdictions that fueled the development of ecosystem-based management principles in the basin. Meeting minutes from lake committee meetings and publications from the Great Lakes Fishery Commission-facilitated Salmonid Community of Oligotrophic Lakes workshop were coded based on 12 a priori ecosystem-based management principles. Meeting and workshop attendance data were analyzed through a bipartite network analysis (organizations connected to meetings) to determine if attendance at meetings were grouped, or clustered, within the fishery governance network. No significant clusters were detected, demonstrating that during 1970-75 fishery professionals in Great Lakes were cooperative in nature – in contrast to the prior half century where little cross-jurisdictional management was reported. Our analyses based on meeting attendance and coded discussions at the meetings demonstrated that three ecosystem-based management perspectives were discussed prior to 1972 (ecological integrity, hierarchical context, and humans embedded in nature) whereas discussions at lake committee meetings from 1972-74 and the Salmonid Community of Oligotrophic Lakes workshop influenced discussions about data collection, ecosystem boundaries, and hierarchical context at lake committee meetings in 1975. The Great Lakes Fishery Commission played a bridging role in facilitating communication among Great Lakes jurisdictions. These annual meetings were becoming a forum for professionals to collaboratively discuss fishery management issues, thereby advancing ecosystem-based management principles throughout the basin. Ultimately discussions at lake committee meetings helped contribute to the Great Lakes Fishery Commission and allied fishery management organizations agreeing to manage Great Lakes fisheries under ecosystem-based management through the ratification of A Joint Strategic Plan for Management of Great Lakes Fisheries in 1981.
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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".