The demographics of knowledge, attitudes and emotions toward coyotes
Notice bibliographique
Résumé
Abstract Context A coyote-caused human fatality in Cape Breton Highlands National Park of Canada (CBHNPC) occurred in 2009. Because CBHNPC is federally protected, rangers have a limited number of management options for dealing with human–coyote conflict. The park initiated the present study to understand the publics’ acceptance of coyotes. Aims This article examined relationships between each of four independent variables (respondent type (resident vs visitor), sex, age, education) and each of four dependent variables (knowledge, attitude, two emotions) related to coyotes in CBHNPC. Researchers have repeatedly suggested that demographics are related to cognitions and emotions toward wildlife. Managers can use demographic findings to target education campaigns to specific stakeholders. Methods Survey data were obtained from (a) residents living around CBHNPC (n = 556, response rate = 70%), and (b) visitors hiking two popular trails in CBHNPC (n = 443, response rate = 60%). Key results All four independent variables were related to knowledge. Visitors were more knowledgeable about coyotes than were residents. Females were more knowledgeable than were males. Younger respondents were more knowledgeable than were older individuals. All education categories differed from each other. Findings for the attitude construct were similar. Residents held negative attitudes toward coyotes, whereas visitors were slightly positive. Males and females both held negative attitudes. The youngest age category held a positive attitude, whereas the oldest group was the most negative. Respondents with a high-school degree had a negative attitude; those with a college degree held a positive attitude. For the first emotion concept, residents were more emotional than were visitors. Males were more emotional than were females, and high-school graduates were more emotional than were college graduates. For the second emotion, there were statistical differences between residents and visitors, as well as between males and females. However, age and education were not related to this scenario. Conclusions Although there were statistical differences for 13 of 16 tests, over 80% of the effect sizes were minimal and there were interaction effects among the four demographic variables. Implications Findings highlighted complexities managers should consider when designing communication strategies aimed at influencing stakeholders’ knowledge of and attitudes and emotions toward wildlife.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 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) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».