Big Qual: A Guide to Breadth-and-Depth Analysis

Foreword
About the Contributors
Preface
How to Use This Book
	Resources
	References
Acknowledgements
About the Book
Contents
About the Authors
Abbreviations
List of Figures
List of Tables
Part I: From Big Qual to the Breadth-and-Depth Method
	1: The Place and Value of Large-Scale Qualitative Data Analysis
		1.1	 Introduction
		1.2	 What Is Big Data?
		1.3	 Big Data and Qualitative Research
		1.4	 Breaking Methodological Borderlines
		1.5	 Big Opportunities for Qualitative Research
		1.6	 In Search of Breadth and Depth
		1.7	 Big Qualitative Data Analysis
		1.8	 Computers, Computing, and Qualitative Data
		1.9	 Capabilities and Skills
		1.10	 Conclusion
		1.11	Resources
		References
	2: Introducing the Breadth-and-Depth Method
		2.1	 Introduction
		2.2	 The Metaphorical Foundations of the Method
		2.3	 An Overview of the Four Steps
			2.3.1	 Step One: ‘Aerial Surveying’—Overviewing the Qualitative Data and Constructing a Corpus
			2.3.2	 Step Two: ‘Geophysical Surveying’—Approaches to Breadth Analysis Using ‘Data Mining’ Tools
			2.3.3	 Step Three: ‘Test Pit Sampling’—Preliminary Analysis
			2.3.4	 Step Four: ‘Deep Excavations’—In-Depth Interpretive Analysis
		2.4	 The Relationship Between Theory and Method
			2.4.1	 Deduction
			2.4.2	 Induction
			2.4.3	 Abduction
			2.4.4	 Retroduction
		2.5	 Benefits of the Method for Qualitative and Quantitative Researchers
		2.6	 Key Considerations
			2.6.1	 Epistemological Issues
			2.6.2	 The Nature of Data in the Breadth-and-Depth Method
			2.6.3	 Quality
			2.6.4	 Generalisability
		2.7	 Getting Started
		2.8	 Resources
		References
Part II: An Enquiry-Led Overview of Qualitative Research Data Sets
	3: Sourcing and Searching for Suitable Data Sets
		3.1	 Starting your Breadth-and-Depth Project
		3.2	 What Do We Mean by Qualitative Data?
		3.3	 Where Can I Find Data?
			3.3.1	 Introducing the Archive
			3.3.2	 Qualitative Archives—A Growing Infrastructure
			3.3.3	 Where Can I Find Archived Qualitative Data Sets?
		3.4	 Community Archiving
		3.5	 Problematising Archiving and Reuse
		3.6	 How to Search an Archive
			3.6.1	 Accessing the Archive—Issues to Consider
			3.6.2	 Data Quality and the Politics of the Archive
		3.7	 Outside and Alongside the Archive
		3.8	 Moving Your Search Strategy Forward
		3.9	 Resources
		References
	4: ‘Aerial Surveying’: Overviewing the Data and Constructing a Corpus
		4.1	 Introduction
		4.2	 The Aerial Survey
		4.3	 Understanding Metadata and Meta-Narratives
			4.3.1	 Using Metadata to Audit Your Data Sets
		4.4	 Working with Metadata—Challenges
			4.4.1	 Closeness and Distance
			4.4.2	 Data Harmonisation
			4.4.3	 Constructing your Corpus
		4.5	 Assembling Your New Corpus
			4.5.1	 Using Metadata to Create a New Corpus
			4.5.2	 Data Management
		4.6	 Conclusion
		4.7	 Resources
		References
Part III: Moving Between Breadth and Depth in Qualitative Analysis
	5: ‘Geophysical Surveying’: Recursive Surface ‘Thematic’ Mapping Using Data Mining Tools
		5.1	 Introduction
		5.2	 CAQDAS Software Not the Only Tool in the Box
		5.3	 Surface Sifting, Not ‘Mining’ as Depth
		5.4	 Capacity, Knowledge, and Skill Required
		5.5	 Basics of Computer Text Analysis and ‘Text Mining’
			5.5.1	 Throwing Away ‘Stop Words’
			5.5.2	 Word Counting: Comparing Frequencies and ‘Keyness’ of Words
			5.5.3	 The Framing of Words
			5.5.4	 RAKE (Rapid Automatic Keyword Extraction)
			5.5.5	 Other Approaches to Keyness
			5.5.6	 Clusters of Words as ‘Topics’
			5.5.7	 The Document-Term Matrix and ‘Bag of Words’ Approach
			5.5.8	 Latent Dirichlet Allocation (LDA)
			5.5.9	 Visualisation
		5.6	 Conclusion
		5.7	 Resources
		References
	6: ‘Test Pit Sampling’: Preliminary Analysis
		6.1	 Introduction
		6.2	 Moving from Breadth to Depth
		6.3	 The Metaphorical Foundations of Test Pit Sampling
		6.4	 The Logic of Identifying Samples and Choosing Cases
		6.5	 The Transition from Step Three to Step Four
		6.6	 Conducting Cursory Readings
		6.7	 Key Areas for Consideration
		6.8	 Resources
		References
	7: ‘Deep Excavations’: In-Depth Interpretive Analysis
		7.1	 Introduction
		7.2	 Metaphorical Foundations
		7.3	 Cases for Deep Excavation
		7.4	 Qualitative Analysis
		7.5	 Forms of In-Depth Interpretive Analysis
		7.6	 Mixing and Matching Interpretive Analyses
		7.7	 Bringing Depth Back into Conversation with Breadth
		References
Part IV: Reflecting on the Implications of Large-Scale Qualitative Analysis
	8: Ethics and Practice
		8.1	 Introduction
		8.2	 Ethical Practice and Constructing a Corpus
			8.2.1	 Issues of Data Sovereignty
			8.2.2	 Overcoming Exclusion in the Archives
		8.3	 Working with Integrity at Scale
			8.3.1	 Research Integrity
			8.3.2	 Establishing the Nature of Consent
			8.3.3	 Risks of Data Linkage
			8.3.4	 Centrality of Context
			8.3.5	 Reliance on Computational Tools and Algorithms
		8.4	 Working with Care
			8.4.1	 Caring for and About Researchers’ Investments
			8.4.2	 Shifting Connectedness to Data
			8.4.3	 Researcher Well-Being
			8.4.4	 Caring about Environmental Impact
			8.4.5	 Ethic of Care Framework
		8.5	 Resources
		References
	9: Big Qual and the Future of Qualitative Analysis
		9.1	 Introduction
		9.2	 The Emergence of Big Qual
		9.3	 Overview of the Breadth-and-Depth Method
		9.4	 Stepping out of the Methodological Borderlines
		9.5	 Challenges and Limitations
		9.6	 Moving the Integrative Field Forward
		9.7	 Resources
		References
Author Index
Subject Index