The Relationship between Social Capital and Weapon Possession on Campus.
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The present research focused on the problem of how college officials might be able to predict weapon possession on college campuses. We hypothesized that measures of social capital (i.e., trust and participation in society) may be useful in identifying individuals who are likely to possess weapons on campuses. Prior research has shown that those who report both relatively low levels of trust in society and high levels of participation in society engage in higher levels of risk-taking than others. The study utilized an online survey method involving 531 college students. The results support the conclusion that colleges may be able to use measures of social capital to predict weapon possession on college campuses. ********** Violence on school campuses has become an increasing concern among educators, parents, and students (Furlong & Morrison, 2000). Data from 1996-1997 indicated that there were 11,000 incidents of violence involving weapons in public schools (Heaviside et al., 1998). Without a doubt, the Columbine and Virginia Tech shootings are still painful memories. Other incidents of campus violence have not grabbed the national spotlight. From 2000 to 2008, institutions of higher education experienced 83 incidents of lethal violence that involved weapons (Drysdale, Modzeleski, & Simons, 2010). Prior research has shown that perpetrators of school violence have common characteristics, including social alienation and accessibility to guns (Bender, Shubert, & McLaughlin, 2001). In the present paper, we investigated the hypothesis that there is a link between the extent to which individuals trust and participate in society and the degree to which students engage in risky behaviors, including possessing weapons. The term social capital has been described as the extent to which one cooperates with other within a group (Fukuyama, 1999; Putnam, 1993). Numerous studies have shown that there is a link between the social capital of large populations and a variety of health-related measures (Kawachi, Kennedy, Lochner, & Prothrow-Stith, 1997; De Silva, McKenzie, Harpham, & Huttly, 2005; Crosby et al., 2003). For example, Kawachi, Kennedy, Lochner, and Prothrow-Stith (1997) analyzed data from 39 U.S. states, obtained from the nationally representative General Social Survey (GSS: Davis & Smith, 1993). Trust was assessed using three questions: one regarding lack of fairness (i.e., someone will try to exploit you rather than treat you fairly), one regarding social mistrust (i.e., that people are not able to be trusted rather than being trustworthy), and perceived helpfulness (i.e., people will generally help others rather than being exclusively concerned with themselves). Participation in society was defined by the number of social, community, or group organizations to which participants belonged. Results indicated that lower social capital resulting from a decrease in social cohesion was strongly correlated with discrepancy in income, and was also associated with mortality, including death from coronary heart disease. Other studies have found a link between social capital and mental illness (see De Silva, McKenzie, Harpham, & Huttly, 2005). Lindstrom and colleagues found that individuals in Sweden who report low levels of trust in society and high levels of participation report the lowest levels of self-rated health (Lindstrom, 2004b; Lindstrom & Mohseni, 2009) and also the highest levels of risky behaviors, including smoking tobacco (Lindstrom, 2003; Lindstrom, 2009; Lindstrom & Ostergren, 2001), marijuana usage (Lindstrom, 2004a), anxiolytic--hypnotic drug use (Johnell, Lindstrom, Melander, Sundquist, Eriksson, & Merlo 2006), and high alcohol consumption (Lindstrom, 2005). Boyce, Davies, Gallupe, & Shelley (2008) analyzed data from Canadian adolescents and found that low social capital was related to high levels of risky behaviors such as smoking and alcohol use. …
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.
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 | 0,002 | 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 | 0,007 | 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 découle