Resolving Conflicts with Double-Crested Cormorants (<i>Phalocrocorax auritus</i>): The Importance of Knowledge-Based and Non-Traditional Approaches, an Introduction
Bibliographic record
Abstract
This paper introduces the special section prepared for Waterbirds from selected papers originally presented at a symposium titled “Recent Advances in Biology and Management of Double-crested Cormorants (Phalocrocorax auritus)”, held in Bar Harbor, Maine, USA, at the 39th Annual Meeting of the Waterbird Society, 11–15 August 2015. The principal objective of this symposium was to explore and communicate about ways to address conflicts with this species that would result in fewer birds being killed under legal management programs. Fifteen papers were presented in three subject categories: population status and new research; knowledge-based challenges for Double-crested Cormorant management; and ethical, bird conservation and other perspectives on cormorant management. Three papers from the second two categories provided unique and important perspectives on ways to manage conflicts in which fewer birds would be destroyed and are presented here. The well-developed approaches in these papers are important steps toward a knowledge-based path to resolving conflicts and, most importantly, living with Double-crested Cormorants.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".