Applied Cross-Cultural Data Analysis for Social Work

2021 ◽  
Author(s):  
Thanh V. Tran ◽  
Keith T. Chan
Keyword(s):  
Social Work ◽  
Data Analysis ◽  
Large Scale ◽  
Cultural Analysis ◽  
Cross Cultural ◽  
Bivariate Analysis ◽  
Practical Applications ◽  
Statistical Approaches ◽  
Cultural Data Analysis ◽  
Cultural Data

Applied Cross-Cultural Data Analysis for Social Work is a research guide which provides a hands-on approach for learning and understanding data analysis techniques for examining and interpreting data for the purpose of cultural group comparisons. This book aims to provide practical applications in statistical approaches of data analyses that are commonly used in cross-cultural research and evaluation. Readers are presented with step-by-step illustrations in the use of descriptive, bivariate, and multivariate statistics to compare cross-cultural populations using large-scale, population-based survey data. These techniques have important applications in health, mental health, and social science research relevant to social work and other helping professions, especially in providing a framework of evidence to examine health disparities using population-health data. For each statistical approach discussed in this book, we explain the underlying purpose, basic assumptions, types of variables, application of the Stata statistical package, the presentation of statistical findings, and the interpretation of results. Unlike previous guides on statistical approaches and data analysis in social work, this book explains and demonstrates the strategies of cross-cultural data analysis using descriptive and bivariate analysis, multiple regression, additive and multiplicative interaction, mediation, and SEM and HLM for subgroup analysis and cross-cultural comparisons. This book also includes sample syntax from Stata for social work researchers to conduct cross-cultural analysis with their own research.

Introduction to Applied Cross-Cultural Data Analysis

2021 ◽  
pp. 1-6
Author(s):  
Thanh V. Tran ◽  
Keith T. Chan
Keyword(s):  
Data Analysis ◽  
Cultural Analysis ◽  
Cross Cultural ◽  
Cultural Identification ◽  
Social Work Research ◽  
Race Ethnicity ◽  
Definition Of ◽  
Cultural Data Analysis ◽  
Cultural Data ◽  
Cross Cultural Analysis

This chapter introduces applied cross-cultural data analysis and addresses the concepts of culture and how culture can be integrated into social work research. We review the definition of culture and how it has been understood and examined in research across various disciplines. We present an overview of the theories and frameworks of cross-cultural analysis, and provide the lens through which culture is examined by means of the techniques and approaches that are used in this book. Cross-cultural analysis can be viewed as comparisons based on key demographic variables such as countries of origin, race, ethnicity, language, sex, religion, and related cultural identifications. The assumption is that people who share the same cultural identification also share similar values and behaviors.

scholarly journals Neural Network: An Improved FCM for Multimodal Cultural Data Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yan Wang ◽  
Di Liu ◽  
Lingling Tian ◽  
Aiping Tan
Keyword(s):  
Neural Network ◽  
Data Analysis ◽  
Bp Neural Network ◽  
Clustering Algorithm ◽  
Cultural Analysis ◽  
Fuzzy C Means ◽  
Correlation Degree ◽  
Feature Information ◽  
Cultural Data Analysis ◽  
Cultural Data

With the development of cloud computing, big data, and artificial intelligence (AI) technology, there is a growing interest in “cultural analysis.” Cultural analysis requires different types of data such as texts, pictures, and videos. The richness and differences of resources in the cultural field lead to diverse modalities of cultural data. Traditional text analysis methods can no longer meet the data analysis needs of current multimedia cultural resources. This article starts from cultural data’s feature information to solve the heterogeneity problem faced by massive multimodal cultural data analysis. It analyzes it from geography, time, art, and thematic character, classified and aggregated to form a multimodal cultural feature information matrix. The corresponding correlation measurement methods for different matrices from the above dimensions are proposed, solved in turn, and substituted into the optimized training back propagation (BP) neural network to obtain the final correlation degree. The improved fuzzy C-means (FCM) clustering algorithm is used to aggregate the high correlation cultural data based on the degree. The algorithm proposed in this study is compared with the existing algorithm. The experimental results show that the optimized BP neural network is at least 58% more accurate than the current method for calculating different matrices’ correlation degrees. In terms of accuracy, the improved fuzzy C-means algorithm effectively reduces the random interference in the selection of the initial clustering center, which is significantly higher than other clustering algorithms.

Comparing a Binary Dependent Variable Across Cultural Groups Using Applied Logistic Regression

2021 ◽  
pp. 131-232
Author(s):  
Thanh V. Tran ◽  
Keith T. Chan
Keyword(s):  
Logistic Regression ◽  
Data Analysis ◽  
Cross Cultural ◽  
Cultural Groups ◽  
Logistic Regression Models ◽  
Cross Cultural Comparison ◽  
Binary Dependent Variable ◽  
Basic Ideas ◽  
Cultural Data Analysis ◽  
Cultural Data

This chapter reviews the basic ideas of logistic regression involving a binary dependent regressed on independent variables, along with assumptions for analysis and interpretations of results. It provides strategies and practical guides for data analysis using Stata and explains the basic assumptions of logistic regression and its applications for cross-cultural data analysis. The chapter also provides examples of logistic regression models for cross-cultural comparison, and outlines the techniques for testing the equivalence of effects across groups. The text includes examples of charts and graphs that can be used to explain differences in effects across cultural groups.

scholarly journals Examination of Heterogeneous Societies

2016 ◽  
Vol 48 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Fumiko Kano Glückstad ◽  
Mikkel N. Schmidt ◽  
Morten Mørup
Keyword(s):  
Cultural Context ◽  
Latent Class ◽  
Cultural Analysis ◽  
Cross Cultural ◽  
Relational Model ◽  
Response Patterns ◽  
World Value Survey ◽  
Applied Model ◽  
Similarities And Differences ◽  
Cultural Data

The recent development of data analytic tools rooted around the Multi-Group Latent Class Analysis (MGLCA) has enabled the examination of heterogeneous datasets in a cross-cultural context. Although the MGLCA is considered as an established and popular cross-cultural data analysis approach, the infinite relational model (IRM) is a new and disruptive type of unsupervised clustering approach that has been developed recently by cognitive psychologists and computer scientists. In this article, an extended version of the IRM coined the multinominal IRM—or mIRM in short—is applied to a cross-cultural analysis of survey data available from the World Value Survey organization. Specifically, the present work analyzes response patterns of the Portrait Value Questionnaire (PVQ) representing Schwartz’s 10 basic values of Japanese and Swedes. The applied model exposes heterogeneous structures of the two societies consisting of fine-grained response patterns expressed by the respective subpopulations and extracts latent typological structures contrasting and highlighting similarities and differences between these two societies. In the final section, we discuss similarities and differences identified between the MGLCA and the mIRM approaches, which indicate potential applications and contributions of the mIRM and the general IRM framework for future cross-cultural data analyses.

Data Management and Cross-Cultural Descriptive Analysis

2021 ◽  
pp. 27-56
Author(s):  
Thanh V. Tran ◽  
Keith T. Chan
Keyword(s):  
Data Management ◽  
Research Evaluation ◽  
Descriptive Analysis ◽  
Cultural Analysis ◽  
Cross Cultural ◽  
Descriptive Statistics ◽  
Cultural Groups ◽  
Practical Applications ◽  
Cultural Research ◽  
Cross Cultural Research

Quantitative cross-cultural analysis requires the application of statistics to study the variability of a phenomenon (variable,) across cultural groups. This chapter aims to provide practical applications of descriptive statistics to describe the variables used in a cross-cultural research/evaluation project. We use statistical methods to describe the variables of interests and to test the hypotheses derived from theories for understanding cross-cultural comparisons. More specifically, we address the importance of examine the variables of interest across selected comparative groups. It is our position that in order to describe and to test hypotheses, we need first to know how the variables of interest are measured. We illustrate the use of STATA for data management and descriptive statistics throughout the chapter.

The cross-cultural analysis of the metaphorical conceptualization of happiness in English and Vietnamese

2016 ◽  
Vol 14 (2) ◽  
pp. 275-302
Author(s):  
Van Trao Nguyen
Keyword(s):  
Data Analysis ◽  
Conceptual Metaphor ◽  
Cultural Influences ◽  
Cultural Analysis ◽  
Cross Cultural ◽  
Abstract Concept ◽  
Target Domain ◽  
Behavioural Responses ◽  
Strong Link ◽  
Idiomatic Expressions

This paper, based on the idiomatic expressions, examines the metaphoric conceptualization of happiness in English and Vietnamese and brings insights into the relevant cross-linguistic and cross-cultural similarities and dissimilarities in the articulation of happiness. The discussion falls into two categories: conceptual metonymy and conceptual metaphor of happiness. The former involves physiological, expressive, and behavioural responses of happiness. These are regarded as metonymies in a sense that there is a ‘stand-for’ relationship between the responses and the emotion of happiness as the whole (i.e., the part stands for the whole) (Kövecses, 2000, 2008). The latter involves the metaphorical conceptualization of happiness, in which the abstract concept of happiness as target domain is structured in terms of a nonabstract domain as a souce domain. The data analysis suggests that metaphors and metonymies involved in the conceptualization of happiness have a strong link not only to physiological, but also to cultural, influences.

Current Issues in Bilingualism: an Update of Directions in Research

1984 ◽  
Vol 5 ◽  
pp. 10-34 ◽  
Author(s):  
Braj B. Kachru
Keyword(s):  
Data Analysis ◽  
Data Collection ◽  
Cross Cultural ◽  
Research Activity ◽  
Social Commitment ◽  
Linguistic Research ◽  
Basic Concepts ◽  
Tools And Techniques ◽  
Intense Research ◽  
Cultural Data

This survey is primarily an update of the review published inARAL I, (Kaplan 1981:2-24). The research on various aspects of bilingualism during the last five years shows three main characteristics. First, there is questioning of some basic concepts which are still considered, as it were, sacrosanct by researchers for the description and analysis of bilingualism--individual and societal--and for actual fieldwork (cf., section 2 below). In such questioning--however mute at present--several theoretical and methodological sacred cows are under attack. Second, one notices a shift in the areas of research towards experimentation, with more precise methodology and techniques, to answer questions concerning the bilingual's brain (cf., sections 5 and 6). Third, there are insightful breakthroughs in crosscultural and cross-linguistic research with serious applied orientation (cf., sections 10 and 11) and, equally important, there is concern for a social commitment in such research. True, in this intense research activity there are very few questions asked which may be considered as breaking new ground. However, the newness lies in the answers which are provided to old questions. In these answers, we notice many fresh insights gained through a wealth of cross-cultural data, through the results obtained from longitudinal studies (e.g., Hakuta and Diaz in press, Rosier and Holm 1980), through the experiments conducted with highly refined and sophisticated tools and techniques of data collection and data analysis, and through increasing understanding of the bilinguals' and monolinguals' neuropsychological processes.

Cross-Cultural Considerations for Social Work Practice:

1998 ◽  
Vol 4 (1) ◽  
pp. 75-85
Author(s):  
Paula T. Tanemura Morelli
Keyword(s):  
Mental Illness ◽  
Social Work ◽  
Severe Mental Illness ◽  
Large Scale ◽  
Work Practice ◽  
Well Being ◽  
The United States ◽  
Social Work Practice ◽  
Cross Cultural ◽  
Mental Illnesses

In the United States, our increasing populations of ethnic and racial minorities suffering with severe mental illnesses require culturally sensitive and culturally appropriate mental health services. The multiple facets of work involving culturally diverse individuals with severe mental illness challenge social work faculty to prepare students with salient, useful knowledge and skills. This teaching module, which utilizes the International Pilot Study of Schizophrenia: Five-year follow-up findings (Leff et al., 1992) is applicable to practice, human behavior in the social environment, and policy courses. The module examines the findings of a large scale, longitudinal study of individuals diagnosed with schizophrenia in nine countries. The learning process encourages students to think critically about the cross-cultural applicability of western diagnosis, treatment, and service provision models, to learn more about cultural constructions of illness and well-being, and to explore the nature of systemic and other barriers that prevent individuals with severe mental illness from obtaining services.

Nursing Research on the Health of Widows

1988 ◽  
Vol 10 (2) ◽  
pp. 15-16 ◽  
Author(s):  
Margarita Kay
Keyword(s):  
Social Work ◽  
Longitudinal Study ◽  
Mexican American ◽  
Coping Styles ◽  
Cross Cultural ◽  
Scientific Process ◽  
Practical Applications ◽  
University Of Arizona ◽  
Academic Capital ◽  
The University

What can one do with a scholarly research project? Shall it sit in a library, to be read only by other scholars? Is it to profit only the investigators who get academic capital from the study? Coping and Health Among Older Urban Widows was a cross-cultural, longitudinal study of how Anglo and Mexican-American widows coped with bereavement and how their coping styles related to their health. The study was awarded to the Southwestern Institute for Research on Women (SIROW) at the University of Arizona and conducted by a team representing several disciplines: anthropology, gerontology, nursing, medicine, sociology, and social work. Here I want to discuss practical applications of our findings. I think that grant recipients must show how to convert into practice what they learned when they followed the careful scientific process that made the award possible. The National Institute of Aging awarded approximately a quarter of a million dollars to this study.

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