Demographic Variables Are Associated with Differing Perceptions of a Broad Range of Public Library Benefits
Notice bibliographique
Résumé
Objective – To determine the frequency and nature of perceived beneficial outcomes of public libraries on individuals, and to identify demographic differences in these perceived outcomes.
 
 Design – Self-administered, online questionnaire asking respondents to rate the frequency of benefits they received from public libraries in 22 areas of life including education, work, and business; everyday activities; and leisure activities.
 
 Setting – United States of America.
 
 Subjects – 1010 respondents from 49 states: 50% female, 76% white, 55% urban or suburban. 
 Methods – Correspondence analysis was used to visualize relationships between demographic variables and perceived outcomes. Exploratory factor analysis was used to identify structures among the outcomes and summarize data into three core dimensions: everyday activities and interests; reading and self-education; and work and formal education. Multiway ANOVAs were used to test the significance of demographic differences on perceived outcomes.
 
 Main Results – The most highly ranked areas of perceived benefits were reading fiction and non-fiction, self-education during leisure time, interest in history or society, and health. Outdoor activities, exercise, and sport ranked the lowest. Respondents in younger age groups reported benefits in “education and work,” as did ethnic minorities and people with lower household incomes. “Everyday life” benefits were reported by male, suburban, White, middle-income respondents. “Reading and self-education” benefits were reported by high-income, older age groups, White, and female respondents. Two demographic groups did not correspond to any benefit categories: those who did not graduate high school and those over age 65.
 
 Conclusion – There are significant differences among demographic groups in how the benefits of public libraries are perceived, and these demographic differences have implications for program planning, marketing, and outreach in public libraries. Specifically, libraries should work to increase and improve service to less-advantaged groups, including low-income earners and ethnic minorities, and make available more services and resources relevant to older people.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,323 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».