Feather-damaging Behaviour in Companion Parrots: An Initial Analysis of Potential Demographic Risk Factors
Bibliographic record
Abstract
Captive parrots (Psittaciformes) commonly engage in “feather-damaging behaviour” (FDB) that suggests compromised welfare. Susceptibilities to FDB have been suggested, but not empirically demonstrated, to vary across the > 200 species kept in captivity. Other demographic risk factors have been proposed for particular species – but neither confirmed nor generalised across Psittaciformes. In this preliminary study, we analysed data from a previously-conducted survey of pet owners: among 538 companion parrots representing 10 non-domesticated, non-hybrid species ( n ≥ 17/species), FDB prevalence was 15.8% overall. We tested whether individual FDB status was predicted by four previously-suggested demographic risk factors: species, sex, age, or hatch origin. Available (limited) data on husbandry were assessed as potential confounding variables and controlled for as appropriate. Species identity was a predictor of FDB status ( P = 0.047), even after controlling for all other variables tested; however, in light of multiple statistical testing, this effect cannot be considered robust until it is replicated. The strongest predictors of FDB status were age ( P = 0.001; with odds of positive FDB status lower in juveniles versus adolescents or adults [ P ≤ 0.036]), and sex ( P = 0.006; with odds of FDB lower in individuals of unknown, versus known, sex [ P ≤ 0.037]). These findings need to be replicated with data that allow better statistical controls for systematic differences in housing. However, they do provide preliminary empirical evidence for within-species risk factors (suggesting new, testable hypotheses about the etiology of parrot FDB); and for intrinsic, cross-species differences in FDB susceptibility (providing a rationale for future study of the biological factors that might underpin any such taxonomic differences).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".