Causes-of-Effects versus Effects-of-Causes

2012 ◽  
Author(s):  
Gary Goertz ◽  
James Mahoney
Keyword(s):  
Social Science ◽  
Quantitative Research ◽  
Research Question ◽  
Social Science Research ◽  
Case Analysis ◽  
Science Research ◽  
Individual Case ◽  
Mixed Method Research ◽  
Causal Factors ◽  
Cross Case Analysis

This chapter examines two approaches used in social science research: the “causes-of-effects” approach and the “effects-of-causes” approach. The quantitative and qualitative cultures differ in the extent to which and the ways in which they address causes-of-effects and effects-of-causes questions. Quantitative scholars, who favor the effects-of-causes approach, focus on estimating the average effects of particular variables within populations or samples. By contrast, qualitative scholars employ individual case analysis to explain outcomes as well as the effects of particular causal factors. The chapter first considers the type of research question addressed by both quantitative and qualitative researchers before discussing the use of within-case analysis by the latter to investigate individual cases versus cross-case analysis by the former to elucidate central tendencies in populations. It also describes the complementarities between qualitative and quantitative research that make mixed-method research possible.

Principled Machine Learning Using the Super Learner: An Application to Predicting Prison Violence

2018 ◽  
Vol 48 (3) ◽  
pp. 698-721 ◽  
Author(s):  
Valerio Baćak ◽  
Edward H. Kennedy
Keyword(s):  
Machine Learning ◽  
Social Science ◽  
Research Question ◽  
Social Science Research ◽  
Science Research ◽  
Adaptive Methods ◽  
Prison Violence ◽  
Data Set ◽  
Super Learner ◽  
Data Adaptive

A rapidly growing number of algorithms are available to researchers who apply statistical or machine learning methods to answer social science research questions. The unique advantages and limitations of each algorithm are relatively well known, but it is not possible to know in advance which algorithm is best suited for the particular research question and the data set at hand. Typically, researchers end up choosing, in a largely arbitrary fashion, one or a handful of algorithms. In this article, we present the Super Learner—a powerful new approach to statistical learning that leverages a variety of data-adaptive methods, such as random forests and spline regression, and systematically chooses the one, or a weighted combination of many, that produces the best forecasts. We illustrate the use of the Super Learner by predicting violence among inmates from the 2005 Census of State and Federal Adult Correctional Facilities. Over the past 40 years, mass incarceration has drastically weakened prisons’ capacities to ensure inmate safety, yet we know little about the characteristics of prisons related to inmate victimization. We discuss the value of the Super Learner in social science research and the implications of our findings for understanding prison violence.

Organising: creating research worlds

2020 ◽  
pp. 79-110
Author(s):  
Paul Thompson ◽  
Ken Plummer ◽  
Neli Demireva
Keyword(s):  
Social Science ◽  
Quantitative Research ◽  
Research Council ◽  
Social Research ◽  
Social Science Research ◽  
Science Research ◽  
Academic Disciplines ◽  
Community Studies ◽  
Central Statistical ◽  
Major Section

This chapter looks at how social research gradually became organized through the work of our pioneers. It starts by looking at the growth of both universities and academic disciplines (like anthropology and sociology) as key backgrounds for understanding the growth of organized research. A major section discusses a range of early research agencies — the Colonial Research Council, Political and Economic Planning (PEP), the Institute of Community Studies, the CSO (Central Statistical Office), the SSRC, Social Science Research Council, and the UK Data Archive. Some new university-based centres are also considered: medical social science at Aberdeen, methods at Surrey and the BCCS (Birmingham Centre for Contemporary Cultural Studies). There are brief discussions of the Banbury Study with Meg Stacey and Colin Bell; and the Affluent Worker study. The chapter closes with some pioneering work on quantitative research, longitudinal studies and the rise of computing.

Literature Review

2021 ◽  
pp. 158-162
Author(s):  
Mathieu Ouimet ◽  
Pierre-Olivier Bédard
Keyword(s):  
Social Sciences ◽  
Literature Review ◽  
Social Science ◽  
Research Question ◽  
Relevant Literature ◽  
Social Science Research ◽  
Science Research ◽  
The Social ◽  
Academic Researchers ◽  
Review Protocol

This chapter highlights literature review. Reviewing the published literature is one of the key activities of social science research, as a way to position one’s academic contribution, but also to get a bird’s eye view of what the relevant literature says on a given topic or research question. Many guides have been created to assist academic researchers and students in conducting a literature review, but there is no consensus on the most appropriate method to do so. One of the reasons for this lack of consensus is the plurality of epistemological attitudes that coexist in the social sciences. Before initiating a literature review, the researcher should start by clarifying the need for and the purpose of the review. Once this has been clarified, the actual review protocol, tools, and databases to be used will need to be determined to strike a balance between the scope of the study and the depth of the review.

5. Finding Answers: Theories and How to Apply Them

2020 ◽  
pp. 123-158
Author(s):  
Sandra Halperin ◽  
Oliver Heath
Keyword(s):  
Social Science ◽  
Research Question ◽  
Social Science Research ◽  
Science Research ◽  
Theoretical Framework ◽  
Different Types ◽  
Independent Variable ◽  
Key Terms ◽  
The Relationship

This chapter shows how to develop an answer to a particular research question. It first considers the requirements and components of an answer to a research question before discussing the role of ‘theory’ in social science research, what a ‘theoretical framework’ is, and what a hypothesis is. It then explores the three components of a hypothesis: an independent variable, a dependent variable, and a proposition (a statement about the relationship between the variables). It also looks at the different types of hypotheses and how they guide various kinds of research. It also explains why conceptual and operational definitions of key terms are important and how they are formulated. Finally, it offers suggestions on how to answer normative questions.

scholarly journals Study Designs for Quantitative Social Science Research Using Social Media

2020 ◽  
Author(s):  
Leticia Bode ◽  
Pamela Davis-Kean ◽  
Lisa Singh ◽  
Tanya Berger-Wolf ◽  
Ceren Budak ◽  
...  
Keyword(s):  
Social Media ◽  
Social Science ◽  
Computer Science ◽  
Quantitative Research ◽  
Social Science Research ◽  
Basic Research ◽  
Science Research ◽  
Social Media Data ◽  
Computer Scientists ◽  
Media Data

Social media provides a rich amount of data on the everyday lives, opinions, thoughts, beliefs, and behaviors of individuals and organizations in near real-time. Leveraging these data effectively and responsibly should therefore improve our ability to understand political, psychological, economic, and sociological behaviors and opinions across time. This article is the first in a series of white papers that will provide a summary of the discussions derived from meetings of social scientists and computer scientists with the goal of creating consensus for how social and computer science could converge to answer important questions about complex human behaviors and dynamics using social media data. We present three basic research designs that are commonly used in social science and are applicable to research using social media data: qualitative observation, experiments, and surveys. We also discuss a fourth design that is primarily informed by computer science, non-designed data, but that can inform social science research. After a brief discussion of the general approach of these designs and their applicability for use with social media data, we discuss the challenges associated with their use with social media data and potential solutions for “convergence” of these methods for future quantitative research in the social sciences.

Scope

2012 ◽  
Author(s):  
Gary Goertz ◽  
James Mahoney
Keyword(s):  
Social Science ◽  
Quantitative Research ◽  
Causal Model ◽  
Social Science Research ◽  
Science Research ◽  
Model Fit ◽  
Empirical Testing ◽  
Qualitative And Quantitative ◽  
The Relationship ◽  
Causal Complexity

This chapter focuses on scope conditions in qualitative and quantitative research. It begins with a simple example, Hooke's law from physics, to illustrate the concept of “scope.” It then considers some of the most popular “within-model” responses to causal heterogeneity problems, showing that the option of changing the causal model to address causal heterogeneity issues is more attractive to quantitative researchers than to qualitative researchers. It also examines how the existence of causal complexity and concerns about fit with data can lead scholars to use scope conditions. Finally, it discusses the relationship between empirical testing and the proposed scope of theories and suggests that issues of scope raise Fundamental Tradeoffs in social science research, including tradeoffs concerning the tension between generality and parsimony, and between generality and issues of model fit.

Triangulation Approaches in Accounting Research

2020 ◽  
pp. 186-200
Author(s):  
Koholga Ormin
Keyword(s):  
Social Science ◽  
Quantitative Research ◽  
Social Science Research ◽  
Science Research ◽  
Accounting Research ◽  
The Social ◽  
Research Findings ◽  
Data Source ◽  
Single Data ◽  
Science Disciplines

Accounting research, like many other social science disciplines, has gradually moved from qualitative to quantitative research with an emphasis on the use of multiple evidence or methods in the conduct of research. This chapter explores the concerns and implications of triangulation in the conduct of research in the social sciences, particularly in the field of accounting. Based on evidence from existing literature, the chapter submits that triangulation is an important strategy for enhancing the quality of accounting research. Accounting researchers, like those from other social science disciplines, often adopt triangulation when investigating a complex phenomenon whereby using a single data source or method may not allow an exhaustive investigation to fully understand it, hence the inability to reach a dependable conclusion. Despite the concerns and implications of use of triangulation in accounting and social science research, the chapter concluded it is a relevant approach especially at a time when adequate evidence and analytical rigor is required to substantiate research findings.

Introduction

2012 ◽  
Author(s):  
Gary Goertz ◽  
James Mahoney
Keyword(s):  
Qualitative Research ◽  
Quantitative Research ◽  
Research Question ◽  
Social Science Research ◽  
Science Research ◽  
Quantitative And Qualitative Research ◽  
The Social ◽  
The Two Cultures ◽  
Mathematical Foundations ◽  
The Relationship

This book investigates the relationship between the quantitative and qualitative research traditions in the social sciences, with a particular focus on political science and sociology. It argues that the two traditions are alternative cultures with distinctive research procedures and practices, each having its own values, beliefs, and norms. The book considers the ways in which the traditions differ in terms of methodology, such as type of research question, mode of data analysis, and method of inference. It suggests that the two traditions draw on alternative mathematical foundations: quantitative research is grounded in inferential statistics (that is, probability and statistical theory), whereas qualitative research is (often implicitly) rooted in logic and set theory. This chapter discusses the book's approach to characterizing and comparing the two cultures of social science research and explains what is distinctive about qualitative research.

5. Finding Answers

2017 ◽  
Author(s):  
Sandra Halperin ◽  
Oliver Heath
Keyword(s):  
Social Science ◽  
Research Question ◽  
Social Science Research ◽  
Science Research ◽  
Theoretical Framework ◽  
Different Types ◽  
Independent Variable ◽  
Key Terms ◽  
The Relationship

This chapter shows how to develop an answer to a particular research question. It first considers the requirements and components of an answer to a research question before discussing the role of ‘theory’ in social science research, what a ‘theoretical framework’ is, and what a hypothesis is. It then explores the three components of a hypothesis: an independent variable, a dependent variable, and a proposition (a statement about the relationship between the variables). It also looks at the different types of hypotheses and how they guide various kinds of research. It also explains why conceptual and operational definitions of key terms are important and how they are formulated. Finally, it offers suggestions on how to answer normative questions.

Qualitative Versus Quantitative Research Strategies: Contrasting Epistemological And Ontological Assumptions

2012 ◽  
Author(s):  
Siti Fatimah Bahari
Keyword(s):  
Mixed Methods ◽  
Social Science ◽  
Mixed Method ◽  
Quantitative Research ◽  
Social Science Research ◽  
Science Research ◽  
Research Strategies ◽  
Intensive Research ◽  
Alternative Research

Kertas kerja ini membincangkan bagaimana strategi penyelidikan kualitatif (intensif) dan kuantitatif (ekstensif) berbeza dengan membandingkan aspek–aspek epistemologi dan ontologi dan bagaimana kepercayaan dan pandangan ini menepati objektif intelektual yang berbeza. Pertama sekali kertas kerja ini membincangkan kepentingan memahami falsafah dalam penyelidikan sains sosial dan hubungannya dengan strategi penyelidikan kualitatif (intensif) dan kuantitatif (ekstensif). Kemudian, perbincangan diteruskan dengan membandingkan dua jenis strategi penyelidikan ini berhubung dengan orientasi utama terhadap peranan teori, anggapan–anggapan epistemologi dan ontologi. Anggapan–anggapan epistemologi yang dibincangkan dalam kertas kerja ini termasuklah intepretivism bagi strategi penyelidikan kualitatif (intensif) dan positivisme bagi strategi penyelidikan kuantitatif (ekstensif). Manakala anggapan–anggapan ontologi yang dibincangkan dalam kertas kerja ini meragkumi subjectivism/constructivism bagi penyelidikan kualitatif (intensif) dan objektivisme bagi strategi penyelidikan kuantitatif (ekstensif). Seterusnya bahagian kedua kertas kerja ini, menerangkan bagaimana dua jenis strategi penyelidikan ini menepati objektif intelektual. Akhirnya, sebagai kesimpulan kertas kerja ini membincangkan strategi penyelidikan alternatif iaitu kaedah campuran (mixed methods) yang boleh diaplikasikan dalam penyelidikan sains sosial. Kata kunci: Kualitatif; kuantitatif; epistemologi; ontologi; strategi penyelidikan This paper attempts to discuss how qualitative (intensive) and quantitative (extensive) research strategies differ by contrasting epistemological and ontological aspects and how these beliefs and views fit with their different intellectual goals. Firstly, this paper discusses the importance of understanding philosophy in social science research and its relation to qualitative (intensive) and quantitative (extensive) research strategies. Then it develops by contrasting these two types of research strategies in relation to the principle orientation to the role of theory, epistemological and ontological assumptions. Epistemological assumptions consist of interpretivism for qualitative (intensive) research strategies and positivism for quantitative (extensive) research strategies. Whereas ontological assumptions constitute subjectivism/constructivism for qualitative (intensive) research and objectivism for quantitative (extensive) research strategies. Further it will explain how these two types of research strategies fit the different intellectual goals and finally concludes by discussing an alternative research strategi namely mixed method that may be employed in social science research. Key words: Qualitative; quantitative; epistemology; ontology; research strategies

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