Primates and disability: Behavioral flexibility and implications for resilience to environmental change
Bibliographic record
Abstract
Congenital malformations, conditions, injuries, and illness can lead to long-term physical impairment and disability in nonhuman primates. How individual primates change their behaviors flexibly to compensate for their disabilities can inform our understanding of their resilience and ability to adjust to environmental change. Here, we synthesize the literature on nonhuman primates and disability, addressing the questions: how does disability influence behavior in primates? What insights can we take from the literature to better understand and predict the capacity of primates to modify their behaviors in the face of human-induced environmental change? We conducted a systematic review of the literature on spontaneous physical impairment and disability in captive, free-ranging, and wild primates. We surveyed 2807 articles on Web of Science and Scopus and identified 114 studies that fit our predetermined inclusion criteria. Behavioral plasticity, maternal and conspecific care, and the potential for innovation of novel behaviors allow many primates with disabilities to compensate when faced with challenges that are outside the scope of usual circumstances. We also found that 60% of the publications connected primate physical impairment and disability to human activities, suggesting an entangled relationship among humans, the environment, and primate disability. Disability and physical impairments provide an opportunity to examine how primates modify their behavior when presented with challenging conditions, and their potential resilience to a changing environment.
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 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".