scholarly journals Perceived injustice, perceived group threat and self-reported right-wing violence: An integrated approach

Author(s):  
Harley Williamson ◽  
Ann De Buck ◽  
Lieven JR Pauwels

Abstract The present study seeks to explain individual differences in self-reported politically motivated violence and vandalism, and participation within an extreme right-wing group. While violent extremism is highly debated, few criminological studies explicitly test factors that can trigger violent extremism. The present study addresses this gap by integrating two different frameworks: a perceived injustice and group threat-initiated model and an impulsivity-initiated model. We also investigate several intervening mechanisms. We draw on a sample of 705 adolescents and young adults living in Flanders, Belgium to test the strength of direct and intermediary effects of perceived injustice, perceptions of out-group threat from Jewish populations, ethnocentrism, feelings of superiority, moral support for right-wing extremism, and exposure to racist peers on politically motivated violence and vandalism. Results of structural equation models (SEM) indicate various direct and intermediary effects between both perceived injustice and violent extremism, and between impulsivity and violent extremism. Our model reveals the complex and intricate antecedents of violent extremism. Importantly, we find that feelings of injustice and unfair treatment are a major source of extremist violence, as they easily trigger often debated causes such as high in-group identification and ethnocentrism. Implications of these findings for preventing violent extremism are discussed, given the centrality of perceptions of injustice and threat.

Author(s):  
David Matthew Doyle ◽  
Christopher T. Begeny ◽  
Manuela Barreto ◽  
Thomas A. Morton

AbstractRelatively little is known about identity-related resilience factors associated with well-being among transgender and gender non-conforming (TGNC) people. Drawing upon theory on stigma-related stress and resilience and work examining group identification as a buffer against discrimination, the aim of the current study was to model perceived discrimination, transgender identification, and gender identity affirmation as predictors of well-being for TGNC people. We also tested whether the positive association between gender identity affirmation and well-being might be explained by the benefits affirmation has for individual self-concept clarity. Participants were 105 TGNC individuals (42% transgender male, 39% transgender female, 19% other gender non-conforming [e.g., non-binary]) recruited through online forums and support groups in the UK and North America who completed an online survey including self-report measures of key constructs. Results from structural equation models demonstrated that: (1) experiences of discrimination were associated with lower well-being overall, but having a stronger transgender identity moderated this association; (2) after adjustment for discrimination and transgender identification, experiences of gender identity affirmation were independently associated with greater well-being for TGNC people. Secondary analyses demonstrated that gender identity affirmation was linked to well-being through reinforcing a strong, internalized sense of clarity about individual self-concept. Results are discussed in terms of the implications for TGNC health and well-being, particularly with regard to the need for supportive, identity-affirming social environments.


2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.


2009 ◽  
Vol 14 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Laura Borgogni ◽  
Silvia Dello Russo ◽  
Laura Petitta ◽  
Gary P. Latham

Employees (N = 170) of a City Hall in Italy were administered a questionnaire measuring collective efficacy (CE), perceptions of context (PoC), and organizational commitment (OC). Two facets of collective efficacy were identified, namely group and organizational. Structural equation models revealed that perceptions of top management display a stronger relationship with organizational collective efficacy, whereas employees’ perceptions of their colleagues and their direct superior are related to collective efficacy at the group level. Group collective efficacy had a stronger relationship with affective organizational commitment than did organizational collective efficacy. The theoretical significance of this study is in showing that CE is two-dimensional rather than unidimensional. The practical significance of this finding is that the PoC model provides a framework that public sector managers can use to increase the efficacy of the organization as a whole as well as the individual groups that compose it.


Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.


Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.


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