Human–animal relationships in zoo‐housed orangutans (<i>P. abelii</i>) and gorillas (<i>G. g. gorilla</i>): The effects of familiarity
Bibliographic record
Abstract
I examined human-animal relationships (HARs) in zoo-housed orangutans (Pongo abelii) and gorillas (Gorilla gorilla gorilla) to see if they followed patterns similar to conspecific relationships in great apes and humans. Familiarity and social relationships guide humans' and great apes' behaviors with conspecifics. Inter-individual relationships, based on shared social history, and "generalized" relationships, based on a history of interactions with relevant classes of individuals, guide behavior with familiar and unfamiliar conspecifics, respectively. I examined whether both familiarity and social relationships similarly guides great apes' cross-species interactions with humans. I used repeated measures MANOVA to compare hourly rates and average durations of ape-initiated human-directed behaviors (HDBs) between familiar and unfamiliar humans and between great ape species. HDB patterns were consistent with familiarity-based HAR predictions, indicating more negative relationships with unfamiliar humans and more positive relationships with familiar humans. Findings for unfamiliar humans are consistent with negative effects of humans on apes' behavior reported in traditional visitor effect studies (VES). However, findings for familiar humans may be overlooked in VES due to pooling across levels of human familiarity or failure to consider humans other than primarily unfamiliar visitors. Additionally, species differences in apes' HDBs suggest that data pooling across species, common in many zoo studies, may mask important differences. These findings have important methodological implications for studies of human-animal interaction as well as for captive animal wellbeing.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".