The end of secularization in Europe? A socio-demographic perspective

Much of the current debate over secularization in Europe focuses only on the direction of religious change, and pays exclusive attention to social causes. Scholars have been less attentive to shifts in the rate of religious decline, and to the role of demography – notably fertility and immigration. This article addresses both phenomena. It uses data from the European Values Surveys and European Social Survey for the period 1981-2008 to establish basic trends in religious attendance and belief across the ten countries that have been consistently surveyed. These show that religious decline is mainly occurring in Catholic European countries and has effectively ceased among post-1945 birth cohorts in six northwestern European societies where secularization began early. It also provides a cohort component projection of religious affiliation for two European countries using fertility, migration, switching and age and sex-structure parameters derived from census and immigration data. These suggest that western Europe may be more religious at the end of our century than at its beginning

Secularization in Europe: religious change between and within birth cohorts

There is ample evidence of religious decline in Western Europe but no general consensus on the situation in the East. Analysis of three waves of the European Values Study (from 1990, 1999 and 2008) adds to the evidence base on secularization across the continent. As expected, older people in most countries, even in Central and Eastern Europe (though not in parts of the former Yugoslavia), seem to be more religious than the rest of the population. More surprisingly, the data suggest that religiosity increased in Northern and Southern as well as Eastern Europe during the 1990s. It is far from clear that these apparent rises are genuine. It still seems fair to say that society is changing religiously not because individuals are changing, but rather because old people are gradually replaced by younger people with different characteristics. Much remains to be understood, though, about why recent generations are different. Parents may be partly responsible, by giving children more control over their own lives. The composition of society has changed, but so has the context in which people are raised. Young people acquire different values and face new conditions. Which factors are most important remains to be determined

Acceptance Criteria for Critical Software Based on Testability Estimates and Test Results

Testability is defined as the probability that a program will fail a test, conditional on the program containing some fault. In this paper, we show that statements about the testability of a program can be more simply described in terms of assumptions on the probability distribution of the failure intensity of the program. We can thus state general acceptance conditions in clear mathematical terms using Bayesian inference. We develop two scenarios, one for software for which the reliability requirements are that the software must be completely fault-free, and another for requirements stated as an upper bound on the acceptable failure probability

The Rise and Fall of Fuzzy Fidelity in Europe

Two issues have been especially contentious in debates over religious change in Europe: the unity or diversity of the trends observed across the continent, and the significance of the large subpopulation that is neither religious nor completely unreligious. This article addresses these problems. An analysis of the first wave of the European Social Survey (ESS) shows that each generation in every country surveyed is less religious than the last. Although there are some minor differences in the speed of the decline (the most religious countries are changing more quickly than the least religious), the magnitude of the fall in religiosity during the last century has been remarkably constant across the continent. Despite these shifts in the prevalence of conventional Christian belief, practice and self-identification, residual involvement is considerable. Many people are neither regular churchgoers nor self-consciously non-religious. The term ‘fuzzy fidelity’ describes this casual loyalty to tradition. Religion usually plays only a minor role in the lives of such people. Religious change in European countries follows a common trajectory whereby fuzzy fidelity rises and then falls over a very extended period. The starting points are different across the continent, but the forces at work may be much the same

Afterword: some reflections on numbers in the study of religion

Religious adherence can and should be quantified, but there are serious problems of validity and reliability in measuring religion. Sometimes the problems themselves are informative about the nature of identity and its significance or insignificance. Understanding the difficulties with numbers helps us to understand religion itself

Religious involvement over the life course: problems of measurement and classification

Longitudinal studies have the potential to enhance our understanding of stability and change in religious identity, practice and belief. Good individual-level data would help in developing and testing theories concerning the causes and consequences of religious involvement. Past research has shown, however, that even subtle differences in wording or context can substantially affect responses to questions on religion. The 1970 British Cohort Study offers an important opportunity to test the consistency of self-reported religion and religiosity. In addition, the 2012 sweep asked questions on belief in God and life after death as well as religious affiliation and practice, allowing us to explore the complexity of religious adherence. A close examination of the multiple waves of the BCS70 reveals a large amount of uncertainty in measurement, making it hard to detect whatever genuine change might have occurred. There are indications of considerable unreliability in reported past and present affiliation. It is also difficult to be confident about changes in religious commitment, though a substantial proportion of teenagers who reported that religion was an important part of their lives became relatively unreligious adults. The data on religious belief make it apparent that while some people seem wholly non-religious and a smaller number are actively (and consistently) religious, the majority fall into intermediate categories defined by nominal allegiance, unorthodox belief, or belief in the absence of affiliation or practice. It is clear that multiple survey items covering identity, practice and belief are needed to obtain a reliable picture of religious commitment

Is the secularization research programme progressing? Debate on Jörg Stolz’s article on Secularization theories in the 21st century: ideas, evidence, and problems

The methodology of scientific research programmes, developed by Imre Lakatos, can help us to identify which theories are strong or weak. Applying this approach suggests that the secularization research programme is progressing, as Stolz argues. Some of the recent advances have been more successful than others, however. In particular, we have done better at understanding how secularization happens than why it happens

Intentionality, Numerical Growth and the Rural Church

A recent report on church growth argued that there are no strong connections between numerical growth and worship style or theological tradition. Instead, what seems crucial is that congregations engage in reflection: choices should be made intentionally, rather than by default. This article summarises the evidence for that claim and considers the implications for rural churches. To the extent that congregations are inward-looking, follow inherited practice and are resistant to change, it may be difficult to avoid stagnation and decline. The revitalisation of tradition is a challenge for rural clergy and congregations

A dynamic failure model for performing propagation and infection analysis on computer programs

This thesis introduces a methodology for determining program locations where faults can easily hide. It is a program structure-based model that analyzes program flow both statically and dynamically; each program location is analyzed relative to its preceding locations and succeeding locations. A statistical model termed propagation analysis studies the relation between incorrect internal data states and their affect on the output. Infection analysis is a statistically model which studies the relation between classes of faults and internal data states. Together these two models combine to form one model of analyzing programs termed Propagation and Infection Analysis (PIA).;PIA employs aspects of both software testing methods and verification techniques. The results of PIA distinguish it from traditional verification efforts however. Verification compares a program with its specification. The ultimate goal of verification is to show the program with its specification. The ultimate goal of verification is to show the program is correct with respect to its specification. PIA characterizes a program in terms of how its failure behavior will be impacted by the presence of faults at various locations. A location which minimally impacts the failure behavior is called fault insensitive. The goal of PIA is to identify fault insensitive location. Since program correctness, safety, and reliability are all intricately connected to the presence (or absence) of faults in the code, PIA therefore provides information useful in quantifying the effectiveness of other verification activities.;The implementation of the propagation and infection analysis model is performed through dynamic executions of the program. Propagation analysis quantifies the impacts on a program after its internal data states have been altered; infection analysis quantifies the impacts on internal data states that common faults have once injected at program locations. The statistics gathered from both altered data states and altered locations are then used to make predictions about expected program behavior if a fault were there.;Models are also provided for applying the results from propagation and infection analysis to a variety of applications dealing with software quality assurance. These include software complexity, debugging, software testing, software reliability, software security, and probable correctness