Drawing Lessons from Experience in Marine Ecosystem-Based Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In December 2011, managers from three states and two Canadian provinces celebrated twenty years of working hand in hand to advance marine conservation in the Gulf of Maine. Together, they have leveraged millions of dollars to enable restoration projects, advance scientific understanding, and coordinate monitoring and management on both sides of the border. When they began meeting twenty years earlier, federal officials suggested they were "incredibly naive" to think they could make a difference in what had become a highly contentious environment. The U.S. State Department discouraged their efforts. Recalling this skepticism, one of the group's cofounders laughs and says, "For some of us who are still around, we kind of smile and say, 'Here we are twenty years later!'" From its humble beginnings with the simple objective "to learn and network and share information so that we can all do our respective jobs better," the Gulf of Maine Council on the Marine Environment has become a model for transboundary marine conservation worldwide.KeywordsMarine ReserveMarine ConservationOcean PolicyMarine Resource ManagementGalapagos Marine ReserveThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it