Over the last decades, the rise of Social Capital as a central field of research in Social Science has contributed to an increasingly controversial and in-depth debate about trust. In particular, the identification of valid predictors for trust has been widely discussed, entailing various theories and outcomes. In the context of this course, this paper focuses on one specific predictor for trust, which has been generally accepted, namely the degree of diversity. Many scholars have applied this relationship of diversity and trust, yet by using very diverse definitions of what they understand by diversity.
This paper seeks at filling this gap of lacking conceptual clarification in terms of measuring diversity. We aim at answering the question whether or not the diversity measure has a significant impact on trust as the dependent measurement variable, and if so, which diversity variable matters most. For this research, we combine three papers related to the research question. Alesina et al. (2003) have presented a more comprehensive overview of diversity by introducing three different measures (ethnic, linguistic, and religious). Secondly, Fearon (2003) contributed to the topic through the refinement of the ethnic diversity measures, and the development of two indicators, ethnic and cultural fractionalization. Furthermore, he divided his large sample of countries into six world regions, a typology which we will also use in our study in order to identify possible peculiarities according to a certain region.
We will combine the three measures by Alesina et al. (2003) and the two by Fearon (2003) and correlate those five independent variables with the dependent variable “trust” on a country level, whose scores are taken from Bjørnskov (2008). The stronger the correlation, the more relevant we interpret the respective independent variable for trust. Moreover, we introduce viable controlling variables in order to eliminate external influences. After the already described screening for regional specialties, we finally execute a linear regression which would further explore the relationships between our variables of interest. We will argue on the basis of our findings that the diversity measure matters, in particular that ethnic fractionalization has the strongest impact on generalized social trust.
Table of Contents
I. Introduction
II. Methodology, Data Sources and Variables
III. Results
Bivariate Correlations: Aggregate Level
Bivariate Correlations: Regional level
Control variables
Partial correlation
Multiple regression analysis
IV. Conclusion
V. Bibliography
VI. Appendix
Research Objectives & Core Topics
This study investigates the relationship between various measures of ethnic, linguistic, and religious diversity and generalized social trust on a national level, aiming to clarify whether diversity measurements significantly predict trust levels or if other socio-economic factors are more influential.
- Comparison of diversity metrics by Alesina et al. and Fearon
- Statistical correlation between societal diversity and trust levels
- Influence of socio-economic control variables (GDP, GINI coefficient, Rule of Law)
- Regional analysis of trust and diversity patterns
- Evaluation of existing theoretical models on social capital
Excerpt from the Book
II. Methodology, Data Sources and Variables
In this paper we analyze the data from the papers by Alesina et al. (2003) and Fearon (2003) with the objective to re-examine the effects of diversity on trust, as measured by Bjørnskov (2008). We start by combining the different measures of diversity and the trust measure into one common dataset. We extract our first three variables - ethnic fractionalization, linguistic fractionalization, and religious fractionalization from the comprehensive overview of diversity by Alesina et al. (2003). They are measured through the probability that two randomly picked individuals of the population belong to a different group. A maximum value of 1 is reached when each person belongs to a different group as it can be seen from the following formula:
The variable linguistic heterogeneity identifies linguistic groups on the basis of languages spoken as “mother tongues” within a country and the religious heterogeneity variable identifies religious groups within a country. The data for both is taken from Encyclopedia Britannica. For the variable ethnic heterogeneity, which identifies ethnic groups within a county incorporating also racial and language characteristics, the authors compare and combine data from Encyclopedia Britannica, CIA Factbook and Minority Rights Group International in order to achieve higher reliability (Alesina et al., 2003, p. 158-160)
The next two measures of diversity are taken from Fearon (2003). The ethnic groups are classified according to Fearon’s prototypical ethnic group using the following criteria:
Summary of Chapters
I. Introduction: Outlines the rise of social capital research, identifies the gap in conceptualizing diversity, and sets the research goal of testing diversity's impact on trust.
II. Methodology, Data Sources and Variables: Describes the integration of diverse datasets (Alesina et al., Fearon, Bjørnskov) and defines the statistical variables and formulae used for the analysis.
III. Results: Details the empirical findings from bivariate correlations, regional comparisons, partial correlations, and multiple regression models while testing the influence of control variables.
IV. Conclusion: Summarizes that diversity measures alone are insufficient predictors for trust and highlights the greater relevance of GDP, GINI coefficient, and Rule of Law.
V. Bibliography: Lists the academic sources and datasets used to support the research paper.
VI. Appendix: Provides comprehensive statistical data tables and graphs supporting the bivariate and multiple regression analyses.
Key Terms
Social Capital, Social Trust, Ethnic Fractionalization, Linguistic Fractionalization, Religious Fractionalization, Diversity Measure, GDP per capita, GINI coefficient, Rule of Law, Regression Analysis, Correlation, World Values Survey, Globalization, Migration, Socio-economic Factors
Frequently Asked Questions
What is the core subject of this paper?
The paper examines whether different measures of social diversity, such as ethnic or linguistic fragmentation, have a significant impact on generalized social trust across different countries.
What are the central thematic fields?
The main themes include social capital theory, the influence of diversity on societal cohesion, and the impact of economic and political governance indicators on interpersonal trust.
What is the primary research question?
The study aims to determine if the diversity measure used matters for explaining trust, and if so, which specific diversity variable has the most significant impact.
Which scientific methods are applied?
The authors employ Pearson Product Moment Correlation, partial correlation tests to control for external factors, and multiple linear regression analysis.
What topics are covered in the main section?
The main section covers the methodological framework, bivariate correlations at both aggregate and regional levels, the impact of control variables like wealth and income inequality, and formal regression testing.
Which keywords characterize the work?
Key terms include social capital, fractionalization, trust, regression analysis, GINI coefficient, GDP, and diversity measurement models.
Why did the authors choose to include the Rule of Law as a control variable?
The authors included Rule of Law because it acts as a proxy for good governance, which historical social capital theory (such as Putnam's work) suggests is deeply connected to levels of trust.
What conclusion did the authors reach regarding diversity and trust?
The authors concluded that diversity, in general, is not strongly connected to trust; instead, factors like GDP, the GINI coefficient, and the Rule of Law appear to be much more reliable predictors.
- Quote paper
- Anonym (Author), 2008, Diversity and Social Trust – Does the Diversity Measure Make the Difference? , Munich, GRIN Verlag, https://www.grin.com/document/175316
