Description
Book SynopsisThis upper-level textbook presents a new approach to large scale qualitative analysis – the pioneering breadth-and-depth method. It covers the strengths and deployment of “big qual” as a distinct research methodology. The book will appeal to students and researchers across disciplines and methodological backgrounds.
The growing availability of large qualitative data sets presents exciting opportunities. Pooling multiple qualitative data sets enhances the possibility of theoretical generalisability and strengthens claims from qualitative research about understanding how social processes work.
Given the evolving possibilities that big data offers the humanities and social sciences, this book will be a must-have resource, building capacity and provoking new ways of thinking about qualitative research and its analysis.
Table of ContentsPART 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. ‘Ariel 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 Harmonization
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 Key Areas for Consideration
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 Researcher’s 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
