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Enregistrement W751404944

Correlates of Volunteerism and Charitable Giving in the 50 United States

2014· article· en· W751404944 sur OpenAlexaboutno aff
George I. Whitehead

Notice bibliographique

RevueNorth American journal of psychology · 2014
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueNonprofit Sector and Volunteering
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPsychologySocial psychologyPopulationQuarter (Canadian coin)PropositionRural areaSociologyDemographyGeographyPolitical scienceLaw
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Cities have been described as environments where there is sensory overload (Milgram, 1970). One way urbanites adapt is to spend less time on each input. Consequently, people who live in cities have reduced moral and social involvement with others. One implication of this proposition is that people will be less helpful in urban than in rural areas. Steblay's (1987) meta-analytic study of the research literature on this proposition supports it. Specifically, Steblay's analysis of the 52 tests of the urban-rural differences in terms of where the helping occurred found that people were less helpful in an urban than a rural environment. One reason why urbanites have high sensory overload is high population density. In an examination of the relationship between population density and helping, Levine, Martinez, Brase, and Sorenson (1994) examined six types of helping across thirty-six cities in the United States. In general, they found that people living in denser cities were less helpful. However, this effect occurred on only three of their six measures of helping. Specifically density was negatively correlated with picking up a dropped pen, helping someone with a hurt leg, and making change for a quarter. Density was not correlated with helping a blind person cross the street, mailing a lost letter, and giving to United Way. Levine et al. concluded that urban-rural differences are more likely to occur for spontaneous than planned helping, though this delineation is not clear-cut, as they acknowledged. The present study also examines the correlation between population density and helping but examines these variables in the 50 United States. To the author's knowledge no previous research has examined the relationships at the state level. Furthermore, helping behavior is operationalized in terms of volunteerism and charitable giving. As previously stated, Levine et al. found a negative but not statistically significant correlation between population density in a city and charitable giving. They did not include volunteerism. Although both exemplify helping behavior, volunteerism is giving of one's time, whereas charitable giving is giving of one's monetary resources. Both volunteerism and charitable giving exemplify planned, long-term giving. Research on this topic often focuses on whom and why people volunteer and/or give to charity (Schroeder, Penner, Dovidio, & Piliavin, 1995). For example, Schroeder et al. indicated that people who have more financial resources are more likely to donate their time and money. Levine et al. also demonstrated that economic indicators were correlated with charitable giving. The foregoing might suggest that people who volunteer also give. This may not always be the case. For example, a national survey indicated that although 42% of the adults surveyed gave and volunteered, 46% only gave, 2% only volunteered, and 10% did neither (Independent Sector, 2001). As DeVoe and Pfeffer (2010) demonstrated, people sometimes prefer to give their money rather than their time (i.e., volunteer). Indeed volunteerism and charitable giving may not be significantly positively correlated at the level of the 50 United States (Whitehead & Kitzrow, 2012). If volunteerism is more time dependent than charitable giving, then population density may impact volunteerism more than charitable giving. As Milgram proposed, people in denser, overloaded situations spend less time on each input. On this basis the study is designed to test the following hypotheses. First, population density and volunteerism will be negatively correlated. Second, because charitable giving is the giving of one's monetary resources, it is more likely to correlate with variables related to income. Therefore, charitable giving will be correlated with individual income tax rates and median household income. METHOD To examine the relationship between population density, volunteerism, and charitable giving, individual income tax rates, and median household income of residents in the 50 United States, archival data were used. …

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,023
Score d'incertitude au seuil0,338

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,015
Tête enseignante GPT0,314
Écart entre enseignants0,299 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2014
Routes d'admission1
Résumé présentoui

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