Victimization

2022 ◽  
pp. 130-148
Author(s):  
Ramona S. McNeal ◽  
Susan M. Kunkle ◽  
Mary Schmeida
Keyword(s):  
Sexual Orientation ◽  
Survey Data ◽  
Statistical Methods ◽  
Sexual Minority ◽  
Research Center ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Cyber Aggression ◽  
Intermediate Variable

Not all groups are equally likely to be subject to acts of aggression; specific subgroups are more likely to be victimized. For example, youth who identify as a sexual minority are more likely to be victims of traditional forms of bullying than their heterosexual friends. There has been less research, however, on population subgroups and the likelihood of becoming a victim of cyber aggression. In exploring this topic, this chapter examines several questions including, “How important is the amount of time spent online as an intermediate variable in predicting whether an individual will become a victim of cyber aggression?” and “Does sexual orientation impact the likelihood of being a victim of cyberaggression above and beyond the amount of time spent online?” Multivariate statistical methods and survey data from the Pew Research Center for the year 2014 was used in this analysis.

Victimization

2018 ◽  
pp. 25-51
Keyword(s):  
Sexual Orientation ◽  
Survey Data ◽  
Statistical Methods ◽  
Sexual Minority ◽  
Research Center ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Cyber Aggression ◽  
Intermediate Variable

Not all groups are equally likely to be subject to acts of aggression; specific subgroups are more likely to be victimized. For example, youth who identify as a sexual minority are more likely to be victims of traditional forms of bullying than their heterosexual friends. There has been less research, however, on population subgroups and the likelihood of becoming a victim of cyber aggression. In exploring this topic, this chapter examines several questions including, “How important is the amount of time spent online as an intermediate variable in predicting whether an individual will become a victim of cyber aggression?” and “Does sexual orientation impact the likelihood of being a victim of cyberaggression above and beyond the amount of time spent online?” Multivariate statistical methods and survey data from the Pew Research Center for the year 2014 was used in this analysis.

Policing Online Aggression

2018 ◽  
pp. 122-147
Keyword(s):  
Survey Data ◽  
Statistical Methods ◽  
Health Professionals ◽  
School Community ◽  
Research Center ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Online Aggression

Research argues that to address bullying/cyberbullying it will take the larger school community including teachers, families, health professionals, etc. The same can be said for other forms of aggression. This chapter provides an overview of the literature on what each member of the larger community can do to curtail the spread of online aggression. The chapter concludes by examining the effectiveness of recommendations for individuals for protecting themselves from becoming victims of online aggression as well as strategies for parents to protect their children from becoming victims of cyberbullying. Multivariate statistical methods and survey data from the PEW Research Center for the years 2013 and 2014 were used in this analysis.

Policing Online Aggression

2019 ◽  
pp. 80-98
Author(s):  
Ramona S. McNeal ◽  
Susan M. Kunkle ◽  
Mary Schmeida
Keyword(s):  
Survey Data ◽  
Statistical Methods ◽  
Health Professionals ◽  
School Community ◽  
Research Center ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Online Aggression

Research argues that to address bullying/cyberbullying it will take the larger school community including teachers, families, health professionals, etc. The same can be said for other forms of aggression. This chapter provides an overview of the literature on what each member of the larger community can do to curtail the spread of online aggression. The chapter concludes by examining the effectiveness of recommendations for individuals for protecting themselves from becoming victims of online aggression as well as strategies for parents to protect their children from becoming victims of cyberbullying. Multivariate statistical methods and survey data from the PEW Research Center for the years 2013 and 2014 were used in this analysis.

Nuisance or Remedy? The Utility of Stylistic Responding as an Indicator of Data Fabrication in Surveys

Methodology ◽  
2014 ◽  
Vol 10 (3) ◽  
pp. 92-99 ◽  
Author(s):  
Christoph J. Kemper ◽  
Natalja Menold
Keyword(s):  
Data Quality ◽  
Survey Data ◽  
Statistical Methods ◽  
Questionnaire Data ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Ex Post ◽  
Response Range ◽  
Data Fabrication

Stylistic responding is usually seen as a nuisance by researchers working with questionnaire data due to its contaminating effects on the measurement of substantiative constructs. We demonstrate that stylistic responding may be useful to improve the data quality in surveys by allowing for an identification of deviant interviewer behavior – data fabrication – in survey fieldwork. Stylistic responding in N = 710 genuine and corresponding falsified interviews was compared. Genuine survey data was collected in paper-assisted personal interviews. Corresponding falsified data were obtained by instructing falsifiers to fabricate data based on person descriptions of genuine survey respondents. Acquiescent and midpoint responding, response range, and self-enhancement emerged as useful predictors of falsification. These indicators might now be used to develop and refine multivariate statistical methods for the ex-post identification of cheating interviewers in survey fieldwork.

Null se constructions in Brazilian and European Portuguese: morphosyntactic deletion or emergence of new constructions?

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Augusto Soares da Silva ◽  
Susana Afonso ◽  
Dafne Palú ◽  
Karlien Franco
Keyword(s):  
Statistical Methods ◽  
External Factors ◽  
Important Predictor ◽  
Cognitive Grammar ◽  
Multivariate Statistical Methods ◽  
Multivariate Statistical ◽  
Passive Construction ◽  
European Portuguese ◽  
Change Of State ◽  
The Moment

Abstract Se constructions designate a set of polysemous constructions along a transitivity continuum marked by the clitic se that perform various functions: reflexive/reciprocal, middle, anticausative, passive, and impersonal. A counterpart of these constructions without the clitic – the null se construction – is also attested. Based on an extensive usage-feature and profile-based analysis, and using multivariate statistical methods, we analyze, considering Cognitive Grammar, the conceptual, structural, and lectal factors that determine the choice between overt and null se constructions. The results of the study show that the null constructions are far more frequent in Brazilian (BP) than in European Portuguese (EP). In BP, the focus on the moment of change is a crucial factor for the overt/null variation in reflexive/reciprocal, middle, anticausative, and impersonal constructions. If the moment of the change of state is profiled, the overt se construction is usually produced. If the moment of change is not profiled, the null se construction is preferred. External factors also play a role in the variation. Register is an important predictor for the observed variation of the anticausative construction, and the only predictor for the overt/null variation in the case of the passive construction. In EP, the null se variant is mainly limited to anticausative constructions. In all cases of null constructions, there is a shift to an absolute construal, which has an impact on the way that the transitivity continuum is conceptualized.

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