The Role of Experience in the Production of Fear of Crime: A Test of a Causal Model

1988 ◽  
Vol 30 (1) ◽  
pp. 67-76 ◽  
Author(s):  
Ian M. Gomme
Keyword(s):  
Fear Of Crime ◽  
Causal Model

The Role of Knowledge Sharing on Organisational Innovation

2016 ◽  
pp. 406-429 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Knowledge Management ◽  
Knowledge Sharing ◽  
Causal Model ◽  
Organisational Learning ◽  
Organisational Innovation ◽  
Business Goals ◽  
Management Knowledge ◽  
Innovation Knowledge ◽  
Positive Effect

This chapter introduces the framework and causal model of organisational learning, knowledge management, knowledge-sharing behaviour, and organisational innovation. It argues that dimensions of organisational learning, knowledge management, and knowledge-sharing behaviour have mediated positive effect on organisational innovation. Knowledge-sharing behaviour positively mediates the relationships between organisational learning and organisational innovation and between knowledge management and organisational innovation. Organisational learning is positively related to knowledge management. Understanding the theoretical learning is positively beneficial for organisations aiming to increase organisational innovation and achieve business goals.

scholarly journals Invariant Causal Prediction for Nonlinear Models

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Christina Heinze-Deml ◽  
Jonas Peters ◽  
Nicolai Meinshausen
Keyword(s):  
Linear Models ◽  
Causal Model ◽  
Nonlinear Models ◽  
Causal Structure ◽  
Nonparametric Tests ◽  
Population Projections ◽  
World Population ◽  
Residual Distribution ◽  
Using Data

AbstractAn important problem in many domains is to predict how a system will respond to interventions. This task is inherently linked to estimating the system’s underlying causal structure. To this end, Invariant Causal Prediction (ICP) [1] has been proposed which learns a causal model exploiting the invariance of causal relations using data from different environments. When considering linear models, the implementation of ICP is relatively straightforward. However, the nonlinear case is more challenging due to the difficulty of performing nonparametric tests for conditional independence.In this work, we present and evaluate an array of methods for nonlinear and nonparametric versions of ICP for learning the causal parents of given target variables. We find that an approach which first fits a nonlinear model with data pooled over all environments and then tests for differences between the residual distributions across environments is quite robust across a large variety of simulation settings. We call this procedure “invariant residual distribution test”. In general, we observe that the performance of all approaches is critically dependent on the true (unknown) causal structure and it becomes challenging to achieve high power if the parental set includes more than two variables.As a real-world example, we consider fertility rate modeling which is central to world population projections. We explore predicting the effect of hypothetical interventions using the accepted models from nonlinear ICP. The results reaffirm the previously observed central causal role of child mortality rates.

Adolescent fear of crime: Testing Ferraro’s risk interpretation model

2018 ◽  
Vol 16 (6) ◽  
pp. 746-766 ◽  
Author(s):  
Eva Krulichová ◽  
Zuzana Podaná
Keyword(s):  
Risk Perception ◽  
Fear Of Crime ◽  
Avoidance Behaviour ◽  
Substantial Part ◽  
Parental Supervision ◽  
Neighbourhood Environment ◽  
Adolescent Risk ◽  
Using Data ◽  
Interpretation Model

The aim of this study is to broaden the scope of knowledge on fear of crime by examining if Ferraro’s risk interpretation model of fear of crime also holds true for the adolescent population. Using data on approximately 1500 Czech students in middle and grammar school, we test three different models. First, the classic model of fear of crime, applied originally to adults, is estimated. Second, the role of perceived school disorganization is examined, taking into account that adolescents spend a substantial part of the day at school. Finally, we propose an extension of Ferraro’s model by considering parental supervision as a factor influencing adolescent fear of crime through risk perception and avoidance behaviour. The results indicate that Ferraro’s original model of fear of crime can be appropriately applied to both adults and adolescents. Nevertheless, adolescent risk perception, which remains the most influential determinant of individual fear, seems to be influenced by stimuli stemming from the school rather than the neighbourhood environment. Furthermore, the relationship between parental supervision and fear of crime is mediated by avoidance behaviour, while no direct effect of parental supervision on risk perception and fear of crime was found in the data.

The role of individual and personality factors in controlling risky behaviours related to AIDS: Proposing a causal model

2016 ◽  
Vol 11 (1) ◽  
pp. 51-63 ◽  
Author(s):  
Mansour Rezaei ◽  
Ali Zakiei ◽  
Soheyla Reshadat ◽  
Seyed Ramin Ghasemi
Keyword(s):  
Causal Model ◽  
Personality Factors ◽  
Risky Behaviours

A Causal Model of Mathematics Performance in Early Adolescence: The Role of Sex

1989 ◽  
Vol 64 (1) ◽  
pp. 167-176 ◽  
Author(s):  
Robert M. Midkiff ◽  
Joy Patricia Burke ◽  
Gerald C. Helmstadter
Keyword(s):  
Causal Model ◽  
Mathematics Performance ◽  
Self Concept ◽  
Scholastic Aptitude ◽  
Eighth Grade Students ◽  
Mathematics Examination ◽  
Achievement In Mathematics ◽  
And Performance ◽  
School Records

Using path analysis, the present investigation was done to clarify possible causal linkages among general scholastic aptitude, academic achievement in mathematics, self-concept of ability, and performance on a mathematics examination. Subjects were 122 eighth-grade students who completed a mathematics examination as well as a measure of self-concept of ability. Aptitude and achievement measures were obtained from school records. Analysis showed sex differences in prediction of performance on the mathematics examination. For boys, this performance could be predicted from scholastic aptitude and previous achievement in mathematics. For girls, performance only could be predicted from previous achievement in mathematics. These results indicate that the direction, strength, and magnitude of relations among these variables differed for boys and girls, while mean levels of performance did not.

Sign in / Sign up

Export Citation Format

Share Document