A framework for sharing power in research teams and promoting justice in scientific publication
Bibliographic record
Abstract
Abstract Many ornithologists seek tools to work more equitably with people from historically marginalized and exploited groups. We developed a process to promote the collective construction of ornithological knowledge in the Special Feature series “Ecology and conservation of cavity nesters in the Neotropics’‘ for the journals Ornithology and Ornithological Applications. Colonialism produces systems that consecrate Eurocentric ideas from dominant nations (including Canada, the USA, and countries of Western Europe) and reinforce hierarchies of power between and within regions. Recognizing these systems, we proposed a Special Feature to support, highlight, and connect teams from Latin America, a region historically exploited by imperial powers. We adopted sociocracy, a governance model that promotes the sharing of power, to create the proposal and organize the call for papers and to write a Review article and this Perspective article. We adopted and developed transparent, consent-based decision-making processes, including a process for determining authorship order. We crafted open invitations, used collective proposals (structured brainstorming), encouraged citation of work from regional journals, tested a system for manuscript submission and review in Spanish, and introduced mechanisms for multi-way feedback. This framework helped reduce some barriers commonly faced by historically marginalized authors, distribute power more equitably, and recognize a broader diversity of contributions to ornithology. Despite these efforts, several challenges remained. For example, the publishing interests of Ornithology, Ornithological Applications, and most high-impact ornithological journals are often poorly aligned with current research priorities in many parts of Latin America (e.g., reproductive biology of endangered species). We encourage scientists at all career stages, technicians, and non-academics to reflect on their citation politics (which sources they cite, and how their citation practice may unintentionally reproduce inequities), and to implement collective workflows that promote equitable sharing of power within research teams. Translated versions of this article are available in Supplementary Material 1 (Spanish) and Supplementary Material 2 (Portuguese).
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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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 teacher head, 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".