Majestic tigers: personality structure in the great Amur cat
Bibliographic record
Abstract
We explore individual differences in tiger personality. We first asked-is there evidence of personality dimensions (analogous to the Big Five in human personality research) in the Amur tiger? We then asked, are any discoverable personality dimensions associated with measured outcomes, including group status, health and mating frequency? 152 of our participating tigers live in the world's largest semi-wild tiger sanctuary in North Eastern China. Our second sample of 96 tigers also lives in a sanctuary. Having two samples allowed us to assess the replicability of the personality dimensions or factors reported in our first sample. We found that two factors (explaining 21% and 17% of the variance among items) which we call, for descriptive ease, Majesty and Steadiness, provide the best fit to the data. Tigers that score higher on Majesty are healthier, eat more live prey, have higher group status (among other tigers as assessed by human raters) and mate more often. We provide some ethological context to put flesh on the quantitative bones of our findings concerning these magnificent and charismatic animals.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".