Introduction: Inequality once more, with (some) feeling

Social science research has been attacked by neoliberal thinkers who allege that such research lacks economic objectives. In the face of neoliberal and positivist criteria for evaluating the social impact of social science inquiry, social science researchers are developing qualitative evaluation methodologies through which we can have direct contact with citizens. These qualitative methodologies declare our social responsibility as social researchers in addressing relevant problems, especially those affecting the most vulnerable people. From these qualitative methodologies, the most vulnerable groups are included in the assessment of the social impacts of social research. Some examples of people who have participated in this qualitative evaluation include women, youth, immigrants, and Roma organizations. Participants perceived social science researchers as being far from their social reality, but in this research, they began to overcome their skepticism that social science research can help to solve those problems affecting their everyday lives.

Missing data are nearly always a problem in research, and missing values represent a serious threat to the validity of inferences drawn from findings. Increasingly, social science researchers are turning to multiple imputation to handle missing data. Multiple imputation, in which missing values are replaced by values repeatedly drawn from conditional probability distributions, is an appropriate method for handling missing data when values are not missing completely at random. However, use of this method requires developing an imputation model from the observed data. This is typically a rigorous and time-consuming process. To encourage wider adoption of multiple imputation in social work research, a simple framework for designing imputation models is presented. The framework and its ability to generate unbiased estimates are demonstrated in a simulation study. KEY WORDS: missing data; multiple imputation; nonresponse ********** Missing data are ubiquitous in social research, and missingness or nonresponse can represent a threat to the validity of inferences because of undue effects on efficiency, power, and parameter bias (Shadish, Cook, & Campbell, 2002). Social work researchers are now addressing missing data in a more rigorous manner. Recently, Saunders et al. (2006) and Choi, Golder, Gillmore, and Morrison (2005) described important data imputation methods and dispelled misunderstandings regarding popular imputation methods, such as mean substitution. Recent advances in analytic methods, such as multiple imputation (MI), are taking hold in social work research. With MI, missing values are replaced with values repeatedly drawn from simulated conditional probability distributions (Schafer, 1997), thus creating multiple versions of the data set. Each version of the data set is analyzed according to the data analysis model, and the multiple results are combined into point estimates (Rubin, 1996). A critical task in MI is to devise an imputation model (Allison, 2002) or missing data model (Graham, Olchowski, & Gilreath, 2007), which involves specifying the measures that are putatively associated with the missing values. Although this process adds additional steps, the specification of an imputation model and the creation of multiple data sets can produce less-biased estimates in the presence of missing data across a wide variety of data analysis techniques (Schafer, 1997). Besides MI, there are many other methods for addressing missing data (Schafer, 1999; Schafer & Graham, 2002). An equally rigorous method known as direct or full information maximum likelihood (FIML) estimation can produce unbiased estimates and correct standard errors in the presence of missing data. When the number of imputations is sufficiently large, identical missing data models will produce the same estimates under MI and FIML (Graham et al., 2007). Unlike MI, FIML is limited to maximum likelihood analytic techniques and the missing data model must be included in the analysis model. Although we focus on MI, the steps we describe for developing an imputation model are equally appropriate for use in the missing data model for FIML. On the basis of the MI literature, this article describes a framework for developing an imputation model for use with any free or commercial software package that performs MI. BRIEF REVIEW OF MISSING DATA CONCEPTS Generally, both MI and a broad range of missing data issues have received ample attention in the applied literature (Graham et al., 2007). We briefly discuss the three types of distributions that describe the randomness of nonresponse given that this property has consequences for the development of an imputation model. For a discussion of general missing data concepts that are not critical to understanding our discussion of imputation model development, we refer readers to Schafer and Graham (2002). Distribution of Nonresponse The probability distribution of nonresponse--more frequently referred to as the missing data or nonresponse mechanism (Rubin, 1976)--is both an important factor in the decision to impute with MI and a context for the development of an imputation model. …

Contributions of M. N. Srinivas to the understanding of changing nature of caste, village and politics have been well documented and continue to be under focus several decades after his scholarly formulations on them. This article is an attempt to focus on the nature of changes that are occurring in the realm of his contributions to the field of social science research methods—especially to the tradition of intensive field research whether in rural or urban locales. Not only have the field sites’ amenability to research has undergone a major change, the institutional context in which social research is practised have radically transformed. This article is an attempt to track some such changes in both the contexts and to reflect upon the emerging challenges to social science research in general and the idea of ‘field’ research in particular. One of the questions it raises and attempts to answer is: Is sociology and social anthropology becoming more dependent on secondary data, and the source becoming a web than the field?

In this survey the author links the social science research on sports with the historical development of sports in Finland and with society at large. Apart from the basic task of discerning truths and facts based on the empirical reality of sports, social science research also has a critical and evaluative role in exploring problematic or neglected issues in physical culture. Is also challenges traditional wisdom in the mainstreams of sports, and contributes to a new policy and the planning of sports for man in society.

Debate has raged whether it is ever right to use children in conducting research in the social sciences. Some have argued that the use of a nonconsenting subject or a subject whose consent is often doubtful, such as is the case with children, is wrong whether or not there is any risk posed to the subject. Others support such research provided it involves no discernible risk to the children. Social science researchers may enlist children in their studies of social processes for a variety of reasons. Such research raises a number of complex ethical and legal problems and challenges that have unfortunately not been addressed in many countries including Botswana. For example, may the researcher obtain the information he needs based on the consent of the child or his parent or both? What are the obligations of the researcher who learns of secrets that the child would rather keep from his parents, to his own detriment? These are some of the questions that this article will attempt to address. It begins by showing why children constitute a special research population that deserve special attention. It then considers some of the fundamental ethical principles that usually apply in social research involving children. This is followed by an attempt to identify some of the legal principles that could be invoked to protect children in such situations. It is contended that the sensitive nature of children and the fact that their use in social research, whilst sometimes unavoidable and beneficial, carries certain risks that justify the

This paper illustrates how systems theory can be used in social work research design to understand the systemic issues associated with spousal care in rural Australia. Spousal caregiving is embedded within multiple formal and informal systems, including family, community, health and aged care practice, social policy, and social and cultural norms. It is therefore a complex phenomenon to explore in social research, with each of these systems interacting with and influencing other aspects of the care system. The purpose of this paper is to provide an illustration of a research design that explores this systemic complexity. The design is conceptually underpinned by the transformative paradigm; a critical approach that reflects social work principles of social justice. The methodology is based on an ecosystems approach to assessment, using multiple methods to explore interactions between systems of care at policy, practice and individual levels. This application of systems theory to research presents an innovative opportunity for social work research to reflect long-established practices of understanding complex phenomenon within its sociocultural context.

Environmental movements have always been a core subject of research within environmental sociology (Dunlap & Catton, 1979). Once largely the near sole purview of environmental sociologists, organized and collective efforts at social change in the name of the environment are now a central object of inquiry among scholars interested in social movements, business organizations, civic participation, resource governance and other topics. The result has been a marked increase in sociological research on environmental movements over the past couple of decades.

Harry Cassidy and Harold Innis, both of the University of Toronto, and both notable Canadian academics, became well known in their respective fields: Cassidy in social welfare and Innis in economic history. This article examines their quite individual approaches to university social science research during the 1940's. Cassidy's orientation was pragmatic and motivated by a Fabian outlook that a carefully laid foundation of facts was necessary in the process of social reform and for the development of progressive social welfare policies. Innis's approach to social science research was much more speculative and historical. It was his contention that long-range social science research carried out by universities could contribute to the restoration of a declining Western civilization. Since he never fully developed his position on research, this account is a synthesis based on his essays. This article, based on material in the University of Toronto Archives, reviews Cassidy's attempts during the forties to have an Institute for Research established at the University of Toronto, which would conduct research into problems of social security in Canada. Some current concerns regarding social science research in the university are discussed in the conclusion.

The paper is a result of a complementary advanced publication workshop accompanying the curriculum course exercises for PhD students, on the role of ICT in the research work of a scientist. This article examines the impact of digital technologies on social research, focusing on social media, open science, and generative artificial intelligence (GenAI). It discusses the benefits and challenges of recruiting research participants through social media, open science practices, and the application of GenAI in academic research. It also presents ethical and methodological aspects of these technologies, emphasizing the need to update ethical guidelines. The article concludes with recommendations for the integration of digital technologies in research, with an emphasis on developing technological competences and maintaining scientific standards.

The focus of this chapter is the use of video-diaries in social research. The aim is to examine and reflect upon the particular ethical terrain and situated ethics of using visual diary method in social science research with different participant groups who arguably present specific ethical concerns, including children and older people, people with disabilities (either physical, cognitive, or psychiatric), and older people. The authors present a discussion of the specific ethical considerations arising from the use of this method due to the particular type of data it generates, namely audio and moving visual data. As such, the process of creating a video diary and the procedures involved in collecting and analysing video diary data are fundamentally different from a paper-based (non-digital) diary. For these reasons, it is important to step back and reflect on the situated ethics, including the digital ethics encountered when using this method.

Much publicity has been given to attempts to discredit a belief in God on the grounds that such a belief does not sit well with scientific thinking in the physical and biological sciences. The present article seeks to argue that this stance overlooks the contribution of scientific methodologies in social science research. The article focuses on the methods of triangulation and of case study for establishing the validity and reliability of evidence in social research and concludes that the case study approach is valid for providing empirical scientific evidence for the existence of God.

The News of the Week article that reports on Senator Kay Bailey Hutchison (R-TX) questioning the need to fund social science research at the National Science Foundation is alarming and shortsighted (“Senate panel chair asks why NSF funds social sciences,” 12 May, p. [829][1]). Social science research is at the fundamental core of basic research and has much to contribute to the economic viability of the United States. Twenty years of direct and jointly funded social and ecosystem science research at Colorado State University's Natural Resource Ecology Laboratory has produced deep insights into environmental and societal impacts of political upheaval, land use, and climate change in parts of Africa, Asia, and the Americas. Beyond greatly advancing our understanding of the coupled human-environmental system, the partnership of social and ecosystem science has brought scientists and decision-makers together to begin to develop solutions to difficult problems. Insights from the social sciences about the vulnerability, sustainability, and resilience of social and environmental systems have greatly increased our understanding of the complex interactions of the world on which we depend. The contributions of social and ecological science for data analyses associated with spatial relationships, transfer of goods and services, valuation, and decision-making processes have improved our understanding of how human activities are altering environmental systems worldwide. These findings have become the core of policy and development decisions used throughout the world. It is critical that the NSF support social science funding and that, as budget decisions are made, the social science allocation should move forward equally with increases as in other basic and applied research. Failure to do so will further hinder U.S. competitiveness in the future and will slow transfer of knowledge and usefulness to the public. [1]: /lookup/doi/10.1126/science.312.5775.829a

In this essay, readings from three different areas are made to intersect in order to produce a conjecture. The first area is social-scientific methods and in particular recent discussion on theorizing. The second area is a sub-tradition that inspects crime and detective fiction as a reflection on social scientific research. The third type of readings are literary analyses of detective fiction. The conjecture is that a book of fiction—Roberto Bolano’s The Savage Detectives—can be used to think about a surprisingly unnoticed moment in discussions on social scientific theorization, namely the role of reading. New ideas in social science often require a self-genealogical work. When making new theories, social researchers need to read their antecessors in order to situate their work so it can actually make sense as a social scientific contribution. The fictionalized inquiry presented in The Savage Detectives can be read as a reflection on this specific theorizing operation.

This book guides social researchers and instructors in the practice of interpretive research. Interpretivism has an intuitive appeal to many social researchers, but they often feel ill-equipped to do it. Other social researchers tend to believe that interpretivism is a specialized niche with little relevance to their research practice. What has been lost is the awareness that interpretation is an explanatory logic and form of inquiry that is at the root of all social science research, including quantitative research. This book enables readers to better understand, reflect on, and improve the experience of doing interpretive research. The book’s unique angle is the centrality of experience in learning and teaching interpretive research. It pays special attention to the role of emotions in the learning process, and the way that negative emotions, such as doubt and anxiety, can impart learning. The book provides a novel approach to methods teaching by offering a set of heuristics and open-ended strategies of inquiry and discovery for improving the practice of research. It shows how emotions can be leveraged in the learning process. The book will benefit social researchers who are doing, or are interested in, interpretivism to turn their research into an enjoyable, productive, and imaginative experience.

One strand of criticism of the ‘cultural turn’ in geography and other disciplines is that it produces research that is of limited ‘usefulness’ and has disarmed academics. This paper argues that elements of the critique of the cultural turn are overstated. It then argues that criticism of the ‘usefulness’ of cultural research rests on simplistic assumptions concerning the relationship of the social research to users such as policy makers. The problem is depicted as largely related to the nature of the information flowing to ‘users’. Such assumptions are critiqued through discussing the concept of ‘use’, influences on the use of research, and models of relationships between ‘users’ and researchers. Finally, the paper argues that a key issue in the relationship between policy making and social sciences is the users’ expectations. A recent example from research in natural resource management (NRM) policy making shows that ‘users’ of social science research can have a questionable foundation from which to assess social research. This example also points to clear roles for cultural research in NRM. The problem of connecting with policy makers is multidimensional. It is one for social researchers as a whole and it includes the norms and practices regarding nature and natural resources of potential ‘users’.