2024 AOS Florence Merriam Bailey Award to Devin de Zwaan
Bibliographic record
Abstract
Devin de Zwaan The Florence Merriam Bailey Award—named for the first woman associate of the American Ornithologist’s Union (AOU) in 1885, who was also the first woman elected as a Fellow of the AOU in 1929—recognizes an outstanding article published in Ornithology or in Ornithological Applications by an early-career AOS member. The 2024 recipient of the Florence Merriam Bailey Award is Devin de Zwaan for his 2022 paper, “Mass gain and stopover dynamics among migrating songbirds are linked to seasonal, environmental, and life-history effects” (de Zwaan et al. 2022), which was published in the American Ornithological Society (AOS) journal Ornithology. Devin de Zwaan is an avian ecologist, working at multiple scales from individuals to communities. His training in behavioral ecology has helped inform more recent interests in movement ecology, landscape ecology, and community ecology, all within a conservation framework. He received a BSc Honors from Simon Fraser University with Bernard Roitberg, PhD, and David Green, PhD, where he studied the foraging ecology of a tropical understory insectivore in Panama. In 2020, de Zwaan completed a PhD at the University of British Columbia with former AOS President Kathy Martin, PhD. His dissertation research focused on alpine ecology and conservation, specifically the full annual cycle effects of weather on offspring development and reproductive success. Since his PhD, de Zwaan shifted focus to assessing abundance and occupancy trends using citizen science datasets. He recently completed postdoctoral research at Mount Allison University and Acadia University with Diana Hamilton, PhD, and Phil Taylor, PhD. These projects involved shorebird movement ecology and tracking nocturnal migrating birds near wind farms using marine radar and thermal imaging. de Zwaan has recently started a position with Environment and Climate Change Canada, where he will be working with seabird data to inform response action plans for environmental disasters. He was previously awarded the Taverner Award from the Society of Canadian Ornithologists–Société des Ornithologistes du Canada and an AOS Student Research Grant and AOS Travel Grant. He contributed two chapters to a book on mountain bird ecology, bringing together mountain ecology experts from every continent other than Antarctica.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.479 | 0.252 |
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".