Editorial: Social networks analyses in primates, a multilevel perspective

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Modeling Marginalization: Emergence, Social Physics, and Social Ethics of Bullying

In this paper, we outline the construction and initial simulation experiment results of the Marginalization model (MARG). We experiment under different group parameters because the theoretical paradigm we follow views bullying as a result of social processes. Our primary research question explores the possibility of bullying emergence as agents select interaction partners in a university setting. Based on the simulated process, our results take indications of the stress of marginalization in a student group as a proxy for emer-gent marginalization. MARG simulates two types of interactions between pairs of students: forced and hang-out interactions. In the latter, students decide whether to interact based on individual preferences formed by social norms and individual tolerance related to those norms. The emergence of intensified mar-ginalization from MARG processes leads to some ethical considerations and provides ground for discus-sions concerning suitable interventions.submittedVersio

Dimensionality and Factorial Invariance of Religiosity Among Christians and the Religiously Unaffiliated: A Cross-Cultural Analysis Based on the International Social Survey Programme

We present a study of the dimensionality and factorial invariance of religiosity for 26 countries with a Christian heritage, based on the 1998 and 2008 rounds of the International Social Survey Programme (ISSP) Religion survey, using both exploratory and multi-group confirmatory factor analyses. The results of the exploratory factor analysis showed that three factors, common to Christian and religiously unaffiliated respondents, could be extracted from our initially selected items and suggested the testing of four different three-factor models using multi-group confirmatory factor analysis. For the model with the best fit and measurement invariance properties, we labeled the three resulting factors as “Beliefs in afterlife and miracles”, “Belief and importance of God” and “Religious involvement.” The first factor is measured by four items related to the Supernatural Beliefs Scale (SBS-6); the second by three items related to belief in God and God’s perceived roles as a supernatural agent; and the third one by three items with the same structure found in previous cross-cultural analyses of religiosity using the European Values Survey (ESS) and also by belief in God. Unexpectedly, we found that one item, belief in God, cross-loaded on to the second and third factors. We discussed possible interpretations for this finding, together with the potential limitations of the ISSP Religion questionnaire for revealing the structure of religiosity. Our tests of measurement invariance across gender, age, educational degree and religious (un)affiliation led to acceptance of the hypotheses of metric- and scalar-invariance for these groupings (units of analysis). However, in the measurement invariance tests across the countries, the criteria for metric invariance were met for twenty-three countries only, and partial scalar invariance was accepted for fourteen countries only. The present work shows that the exploration of large multinational and cross-cultural datasets for studying the dimensionality and invariance of social constructs (in our case, religiosity) yields useful results for cross-cultural comparisons, but is also limited by the structure of these datasets and the way specific items are coded

Religious Exiting and Social Networks: Computer Simulations of Religious/Secular Pluralism

Statistical models attempting to predict who will disaffiliate from religions have typically accounted for less than 15% of the variation in religious affiliations, suggesting that we have only a partial understanding of this vital social process. Using agent-based simulations in three “artificial societies” (one predominantly religious; one predominantly secular; and one in between), we demonstrate that worldview pluralism within one’s neighborhood and family social networks can be a significant predictor of religious (dis)affiliation but in pluralistic societies worldview diversity is less important and, instead, people move toward worldview neutrality. Our results suggest that there may be two phases in religious disaffiliation: (1) the early adopters initially disaffiliate regardless of social support, and subsequently (2) disaffiliation spreads as support for it within local social networks widens and it appears more acceptable. An important next step is for sociologists to confirm or correct the theoretical findings of this model using real-world socialnetwork data, which will require overcoming the measurement difficulties involved in estimating each individual’s degree of local network pluralism.publishedVersio

A multilevel statistical toolkit to study animal social networks : the Animal network toolkit Software (Ants) R package

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Adapting Cohort-Component Methods to a Microsimulation: A case study

Social scientists generally take United Nations (UN) population projections as the baseline when considering the potential impact of any changes that could affect fertility, mortality or migration, and the UN typically does projections using the cohort-component method (CCM). The CCM technique is computationally simple and familiar to demographers. However, in order to avoid the exponential expansion of complexity as new dimensions of individual difference are added to projections, and to understand the sensitivity of projections to specific conditions, agent-based microsimulations are a better option. CCMs can mask hidden assumptions that are surfaced by the construction of microsimulations, and varying such assumptions can lead to quite different projections. CCM models are naturally the strongest form of validation for population projection microsimulations but there are many complexities and difficulties associated with matching microsimulation projections and CCM projections. Here, we describe our efforts to tackle these challenges as we validated a microsimulation for Norway by replicating a UN CCM projection. This provides guidance for other simulationists who seek to use CCMs to validate microsimulations. More importantly, it demonstrates the value of microsimulations for surfacing assumptions that frequently lie hidden, and thus unevaluated, within CCM projections.publishedVersio

Adapting Cohort-Component Methods to a Microsimulation: A case study

Social scientists generally take United Nations (UN) population projections as the baseline when considering the potential impact of any changes that could affect fertility, mortality or migration, and the UN typically does projections using the cohort-component method (CCM). The CCM technique is computationally simple and familiar to demographers. However, in order to avoid the exponential expansion of complexity as new dimensions of individual difference are added to projections, and to understand the sensitivity of projections to specific conditions, agent-based microsimulations are a better option. CCMs can mask hidden assumptions that are surfaced by the construction of microsimulations, and varying such assumptions can lead to quite different projections. CCM models are naturally the strongest form of validation for population projection microsimulations but there are many complexities and difficulties associated with matching microsimulation projections and CCM projections. Here, we describe our efforts to tackle these challenges as we validated a microsimulation for Norway by replicating a UN CCM projection. This provides guidance for other simulationists who seek to use CCMs to validate microsimulations. More importantly, it demonstrates the value of microsimulations for surfacing assumptions that frequently lie hidden, and thus unevaluated, within CCM projections.publishedVersio