Conserving Transborder Migratory Bats, Preserving Nature's Benefits to Humans: The Lesson from North America's Bird Conservation Treaties
Bibliographic record
Abstract
In 2015, Canada, the United States, and Mexico signed a letter of intent to protect the continent's migratory bats. In charting a path for protecting bats, we look to the century of efforts to protect birds. Despite a barrage of obstacles, millions of migratory birds still cross North America each year. One key reason for their survival has been international cooperation. The past year marks the 100th anniversary of the Migratory Bird Treaty between Canada and the United States, as well as the 80th anniversary of a similar agreement between the United States and Mexico. These treaties were based on the practical benefits from migratory birds—values today known as ecosystem services. Migratory bats also provide significant natural benefits to people; a fully fledged international convention on migratory bats would not only protect these benefits but would also celebrate a century of transborder cooperation to conserve migratory species in North America.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".