Improving the language of migratory bird science in North America
Bibliographic record
Abstract
Abstract Several long-accepted terms are widely misused in ornithology and have led to a misperception of important concepts in the ecology of Nearctic–Neotropical migratory birds. The term “North America” (and its ancillary terms “North American species,” “North American habitats,” etc.) is widely used to refer to the United States and Canada, when in fact it should include all of the continent from the Arctic through Panama. In a similar vein, the terms “wintering” and “over-wintering” (whether used to describe the status of individual birds or species, or as a modifier for terms like habitats, ecology, or behavior), “spring migration” and “fall migration” are inappropriate for Nearctic–Neotropical migrants because they explicitly reference conditions in the temperate zone of the continent, even as most such species spend the majority of their annual cycle elsewhere, where these terms are inaccurate and unhelpful. We discuss the pitfalls of using these terms and suggest several alternatives and replacements. In particular, we urge more precision in the use of the term “North America”; for Nearctic–Neotropical migratory species (especially long-distance migrants), we suggest retiring the terms “wintering” and “over-wintering” in favor of “nonbreeding”; and for the same group of species we suggest retiring the terms “spring migration” and “fall migration” in favor of “pre-breeding,” “post-breeding,” or “post-natal” migration.
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 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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".