Descriptive Texts in Dog Profiles Associated with Length of Stay Via an Online Rescue Network
Notice bibliographique
Résumé
To increase the public’s awareness of animals needing homes, PetRescue, Australia’s largest online directory of animals in need of adoption, lists animals available from rescue and welfare shelters nationwide. The current study examined the descriptions accompanying online PetRescue profiles. The demographic data and personality descriptors of 70,733 dogs were analysed for associations with LOS in shelters—with long stays being a potential proxy for low appeal. Univariable and multivariable general linear models of log-transformed LOS with personality adjectives and demographic variables were fitted and the predicted means back-transformed for presentation. Further analyses were conducted of a subset of the dataset for the four most common breeds (n = 20,198 dogs) to investigate if the influence of personality adjectives on the LOS differed by breed. The average LOS of dogs was 35.4 days (median 18 days) and was influenced by several adjectives. Across all breeds, the LOS was significantly shorter if the adjectives ‘make you proud’, ‘independent’, ‘lively’, ‘eager’ and ‘clever’ were included in the description. However, the LOS was longer if the terms ‘only dog’, ‘dominant’, ‘sensitive’ and ‘happy-go-lucky’ were included in the description. Some of the association of descriptors with relatively long LOS are difficult to explain. For example, it is unclear why the terms “obedient” and trainable” appear unappealing. The confidence adopters have in these terms and their ability to make the most of such dogs merits further exploration. As expected, the LOS differed in different breeds with the Labrador retrievers having the fastest adoption rate among the most common four breeds with an average LOS of 14.5 days. Breed had interactions with four personality adjectives (gentle, active, quiet and energetic) indicating that the adoption rate of dogs with these descriptors in their online PetRescue profiles differed by breed. This highlights an important knowledge gap, suggesting that potential adopters have differing expectations according to the breed being considered. Increased awareness of the breed-specific influence of personality adjectives on appeal to potential adopters, may enhance adoption success by allowing dogs with risk factors for low appeal to be promoted more intensively than high-appeal dogs.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».