Included are discussions of historical, theoretical, and feminist scholarship; case-study and ethnographic research; text and conversation analysis; and cognitive, experimental, and descriptive research. Issues that cross methodological boundaries, such as the nature of collaborative research and writing, methodological pluralism, the classification and coding of research data, and the politics of composition research, are also examined. Contributors reflect on their own research practices, and so reflect the current state of composition research itself. Patricia A. Sullivan is assistant professor of English and associate director of composition at the University of New Hampshire.
Methods and Methodology in Composition Research.
Capturing Individual Uptake: Toward a Disruptive Research Methodology
Friend Reviews. To see what your friends thought of this book, please sign up. To ask other readers questions about Methods and Methodology in Composition Research , please sign up. Be the first to ask a question about Methods and Methodology in Composition Research. Lists with This Book. This book is not yet featured on Listopia. Community Reviews. Showing Rating details. Sort order. This book provides detailed introductions into writing studies intersections with empiricism, but I do not find the essays here to be completely mind-altering.
Nonetheless, there is plenty of useful information here for resources and inspiration for writing studies research. Excellent overview of where comp. This is the case, for example, when census data with overall religious composition results are available but a detailed breakdown by age and sex is not released by the census bureau, in which case another source must be used to generate the age structure. Sources are also different when multiple waves of a survey series have to be combined in order to have a sample size large enough to construct reliable age structures.
Age structures were further adjusted in countries where the age structure data source is much older than the source used for the religious composition of the country. In order to harmonize the data on overall religious affiliation with the age structure data, the latter is aged in five-year projections while holding the religious composition data constant. In a small number of countries, age structures were estimated based in part on ethnicity or citizenship data.
For example, all six Gulf Cooperation Council GCC countries release information on the age distribution of citizens and non-citizens, but only Bahrain further breaks down this information by Muslims and non-Muslims. In many countries, there are substantial differences in the number of children born to women in different religious groups.
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Furthermore, religious groups often vary in the share of women in their population who are of childbearing age, and women in some groups may, on average, begin having children at younger or older ages than do women in other groups. Fertility data were gathered from censuses and surveys, and fertility rates were estimated via direct and indirect measures.
Some censuses and surveys directly measure recent births or the number of children a woman has ever born by the time of the survey. These various sources of fertility data were used to estimate age-specific and Total Fertility Rates for religious groups in each country. In many countries, data on differential fertility are available for the largest religious groups but sufficient detail is not available for all minority religious groups. For other groups in Nigeria, however, researchers had to base estimates on more limited data.
In some countries, differential fertility data by religion were not available. In these cases, researchers applied prevailing national fertility rates to all religious groups equally. Little research has been conducted on cross-national differences in mortality and life expectancy across religious groups. In the absence of better data, the same mortality patterns within each country are assumed for all groups; for example, Christians and Muslims born in the same year in Nigeria are assumed to have the same life expectancy at birth.
At the global level, mortality rates for each group reflect differences between the countries in which the various groups are concentrated. To model the impact of migration on future religious change, the population projections in this report required an estimate of the religious composition of recent migrant flows between countries — that is, how many migrants moving from Country X to Country Y are Christian? How many are Muslim?
How many are Hindu? Data on the size and religious breakdown of migrant flows were pieced together in two steps. The first step was to estimate how many people move to and from every country in the world. Second, the religious composition of migrants moving between countries was estimated. The limited flow data that are available may not capture all modes of travel or all kinds of international migrants, and it can be difficult to distinguish short-term travel from long-term migration.
Both data sources represent a compilation of census and survey data from around the world, estimating the size of the foreign-born population in each destination country, broken down by country of origin. Flows were estimated by first approximating stocks using interpolated trends based on differences between the and migrant stock information. Second, using an innovative technique developed by researchers at the Vienna Institute of Demography, differences in foreign-born populations between and were used to estimate migration flows for countries.
Resulting estimates of migration flows were reviewed by Pew Research Center staff to be sure all estimates represented recent migration patterns, and some adjustments were made. Several countries with a total population of less than a million people did not have recent data on migration; thus, migration flows for these smaller countries are not included in the population projections. Migration patterns to some countries changed between and Most notably, the economic crisis in the latter part of the decade slowed migration in many parts of the world.
In Israel, for example, the origins of migrants in were much different than those arriving in In this case, data containing the most recent migration flows into Israel were used. Adjustments made to migrant flows are listed by country in the appendix on data sources see Appendix B on page The second step was to identify the religious breakdown of migrants. It is important to realize that the religious composition of migrants is not always the same as the religious composition of the general population in their country of origin.
In many cases, members of some religious groups are more likely than others to leave a country, and they are also more likely to choose certain destination countries. Religious minorities, in particular, may be disproportionately likely to migrate to a country in which their religion is in the majority. For example, surveys of recent immigrants indicate that Christians from the Middle East and North Africa are more likely than Muslims from the region to move to the United States.
The information in the database is of varying quality. Using all of this information, researchers calculated migration rates to and from most countries by age, sex and religion.
As countries increase or decrease in size and their religious composition changes, the migration rates will produce corresponding changes in the size and religious composition of migrant flows. Studies of religious switching indicate that this phenomenon is often concentrated in young adult years, roughly between ages 15 and Change in religious affiliation may occur as young adults move away from their parents and partner with someone of a different affiliation status. While some religious switching may take place at other ages, switching is modeled as a life course phenomenon in which some young adults change their religious affiliation status.
There may be some time periods during which people of all ages are prone to religious switching, such as when political circumstances in a country encourage or discourage religious identity or lack of religious identity. The typical procedure for measuring religious switching is to compare the religion in which a person grew up with their current religion when the person is an adult.
The best sources of data on religious switching are nationally representative surveys that ask adults about their current religion as well as the religion in which they were raised. In 70 countries, data are available on both the religious upbringing of survey respondents and on current adult religious identity.
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Data sources include cross-national surveys carried out as part of the International Social Survey Program and by the Pew Research Center, as well as some surveys carried out only in one country. Censuses in Northern Ireland and Scotland are exceptions. Since men and women often follow different switching patterns, researchers calculated rates of switching separately for men and women based on the experiences of adults ages at the time of the survey.
Researchers assume that the experience of young respondents is the best source of information about likely switching patterns for emerging generations, so the experiences of older respondents those ages 55 and above are excluded from the analysis. The analysis was initially restricted to the switching experience of to year-olds; while this restriction allowed the focus to be on respondents who have recently completed their young adult years, it left less-than-optimal sample sizes. Including the full range of adults ages in the sample increased sample sizes and did not appear to compromise the reliability of the switching rates.
The most populous countries in which switching was not modeled are China and India. Prior to this study, the most extensive analysis of religious switching covered 40 countries. It is difficult to formally project religious switching in China without information on recent or likely patterns of switching. For example, it is not clear at what rate people in China may be converting to Christianity from other groups, and retention patterns among Christian converts are not known.