Neotropical ornithology: Reckoning with historical assumptions, removing systemic barriers, and reimagining the future
Bibliographic record
Abstract
Abstract A major barrier to advancing ornithology is the systemic exclusion of professionals from the Global South. A recent special feature, Advances in Neotropical Ornithology, and a shortfalls analysis therein, unintentionally followed a long-standing pattern of highlighting individuals, knowledge, and views from the Global North, while largely omitting the perspectives of people based within the Neotropics. Here, we review current strengths and opportunities in the practice of Neotropical ornithology. Further, we discuss problems with assessing the state of Neotropical ornithology through a northern lens, including discovery narratives, incomplete (and biased) understanding of history and advances, and the promotion of agendas that, while currently popular in the north, may not fit the needs and realities of Neotropical research. We argue that future advances in Neotropical ornithology will critically depend on identifying and addressing the systemic barriers that hold back ornithologists who live and work in the Neotropics: unreliable and limited funding, exclusion from international research leadership, restricted dissemination of knowledge (e.g., through language hegemony and citation bias), and logistical barriers. Moving forward, we must examine and acknowledge the colonial roots of our discipline, and explicitly promote anti-colonial agendas for research, training, and conservation. We invite our colleagues within and beyond the Neotropics to join us in creating new models of governance that establish research priorities with vigorous participation of ornithologists and communities within the Neotropical region. To include a diversity of perspectives, we must systemically address discrimination and bias rooted in the socioeconomic class system, anti-Blackness, anti-Brownness, anti-Indigeneity, misogyny, homophobia, tokenism, and ableism. Instead of seeking individual excellence and rewarding top-down leadership, institutions in the North and South can promote collective leadership. In adopting these approaches, we, ornithologists, will join a community of researchers across academia building new paradigms that can reconcile our relationships and transform science. Spanish and Portuguese translations are available in the Supplementary Material.
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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 | 0.034 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.059 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".