Carlo Natale Lauro
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Carlo Natale Lauro has a total of 10 co-authors. Here are the top co-authors by number of shared publications:
- Caterina Arcidiacono
Department of Humanities University of Naples Federico II Napoli Italy
1 shared publication - Chiara Castiello
Institute for Socio-Psychological Training, Research and Sexual Education, 80127 Naples, Italy
1 shared publication - Filomena Grassia
Istituto Nazionale di Statistica, Rome, Italy
1 shared publication - Fortuna Procentese
Department of Humanities, University of Naples Federico II, Napoli, Italy
1 shared publication - Ida Galli
University of Salerno, Italy
1 shared publication - Maria Gabriella Grassia
University of Naples Federico II
1 shared publication
Latest Publications
- Open Access
- 10 July 2020
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 17 (14) , 4991
The Use of Partial Least Squares–Path Modelling to Understand the Impact of Ambivalent Sexism on Violence-Justification among Adolescents
Gender violence is generally conceived as a phenomenon concerning only adults. Nonetheless, it is also perpetrated within teenagers’ relationships, as many empirical studies have shown. We therefore have focused our attention on a non-probabilistic sample consisting of 400 adolescents living in Naples (Italy), to study the association between sexism and the justification of violent attitudes. Generally, sexism is recognised as a discriminatory attitude towards people, based on their biological sex. However, it is conventional to talk about sexism as a prejudice against women. The Ambivalent Sexism Inventory (ASI) for adolescents was used to evaluate the two dimensions of ambivalent sexism, i.e., hostile sexism (HS) and benevolent sexism (BS). Moreover, the questionnaire regarding attitudes towards diversity and violence (CADV) was administered to assess participants’ attitudes towards violence. A Partial Least Square–Second Order Path Model reveals that girls’ ambivalent sexism is affected more by benevolent sexism than hostile sexism. On the contrary, among boys, hostile sexism has a higher impact. Finally, benevolent sexist girls justify domestic violence more than boys do.
- 10 July 2020
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 17 (14) , 4991
Open AccessThe Use of Partial Least Squares–Path Modelling to Understand the Impact of Ambivalent Sexism on Violence-Justification among Adolescents
Gender violence is generally conceived as a phenomenon concerning only adults. Nonetheless, it is also perpetrated within teenagers’ relationships, as many empirical studies have shown. We therefore have focused our attention on a non-probabilistic sample consisting of 400 adolescents living in Naples (Italy), to study the association between sexism and the justification of violent attitudes. Generally, sexism is recognised as a discriminatory attitude towards people, based on their biological sex. However, it is conventional to talk about sexism as a prejudice against women. The Ambivalent Sexism Inventory (ASI) for adolescents was used to evaluate the two dimensions of ambivalent sexism, i.e., hostile sexism (HS) and benevolent sexism (BS). Moreover, the questionnaire regarding attitudes towards diversity and violence (CADV) was administered to assess participants’ attitudes towards violence. A Partial Least Square–Second Order Path Model reveals that girls’ ambivalent sexism is affected more by benevolent sexism than hostile sexism. On the contrary, among boys, hostile sexism has a higher impact. Finally, benevolent sexist girls justify domestic violence more than boys do.
- 5 October 2014
- Published by Springer Nature in Quality & Quantity
- Vol. 49 (3) , 891-902
Comparing maximum likelihood and PLS estimates for structural equation modeling with formative blocks
- 5 October 2014
- Published by Springer Nature in Quality & Quantity
- Vol. 49 (3) , 891-902
Comparing maximum likelihood and PLS estimates for structural equation modeling with formative blocks