Qualitative Data Analysis: An Introduction

1. Qualitative Data Analysis: An Introduction Carol Grbich Chapter 6. Grounded Theory

2. Grounded Theory • Use for exploring relationships or observing micro interaction • Use where little previous knowledge exists • Developed by Barney Glaser and Anselm Straus who wanted to develop theory from data in the real world Current versions include: Barney Glaser’s version Anselm Strauss’ version • Kathy Charmez’ constructivist Grounded theory version • Postmodern and conjoint orientations

3. Grounded theory assumptions • Assumptions underpinning GT- Symbolic Interactionism presumes reality is constructed and social processes can be created and changed by interactions among people, • ‘Meaning’ is constructed through symbols, signs and language, and our ability to take the position of others through the ‘I’ (the uninhibited self) and the ‘me’ (the societal controls reflected in the attitudes, values and behaviours of significant others). • The focus in grounded theory is - the empirical, social world ‘out there’ viewed as comprising many different layers, and public and private views.

4. Differences between Strauss & Glaser Glaser Strauss Style discovery verification Question problem + variations dimensionalising & critiquing Process emergent directions coding & hypothesis testing Lit. review ongoing from 1st when categories emerge - if desired Category identification Coding constant comparison 3 levels of data fracturing Open coding words, lines, sections words, lines paragraphs Axial coding unnecessary meticulous procedure Selective coding core variables only core categories to other categories Theory theory generation theory verification

5. Strauss’ grounded theory • Dimensionalising and sub -dimensionalising (research question) • Open coding (data opening up through questioning) • Memos (detailed summation of observation and data linking to concepts and literature) • Axial coding (grouping of categorical data) • Selective coding (linking of core categories with memos and literature • Integration (putting it all together)

6. Glaser’s Grounded theory • No data fracturing • Constant comparison of incident to to incident and to emerging concepts • Use of open coding, theoretical sampling and constant comparison techniques • Group emergent categories, generate connections and link to literature

7. Theoretical sensitivity • A process of becoming steeped in the literature using the ‘variables’ emerging from the data and seeking conceptual and theoretical connections to provide interpretations in the generation of new theory (Glaser) • Linking of data and theory more for verification rather than generation of new ideas but being careful not to let existing views bias your perceptions. (Strauss)

8. Development of formal theory • Identify the core category to be developed • Open code and write memos of an example of the data in which this category occurs • Theoretically sample in a range of different areas • Continue until a wide range of sources have been covered Strauss (1987:241-2) Criteria for evaluating substantive / formal theory • Fit – the link between the theory and the arena where it will be used to provide insight needs to be clear • Understandability – will the theory be meaningful to those who don’t work in the area from which the data has been collected? • Generaliseability – the theory needs to be meaningful in a large range of areas • Control – does the theory empower users within the field with knowledge to improve their situation? (adapted from Glaser and Strauss, 1967:237)

9. Criticisms of Grounded Theory • A focus on a quasi-objective centred researcher • Existing theories cannot be ignored by avoiding a literature review, the researcher invariably comes to the research topic bowed under the weight of intellectual baggage from his/her own discipline. • There is a focus on a complex method and confusing and overlapping terminology rather than data. • Poorly integrated theoretical explanations tend to be the outcome

10. Charmez’s Constructivist Grounded Theory : differences Researcher and researched • She challenges the previously ‘objective’ distant nature of the relationship between researcher and participants • She refocusses on researchers and their critical reflective role in the recognition and management of their biases Data accountability • Immersion in and transposing raw data into memos is one suggested way of keeping close and accountable to data (maintaining participants voices) • Using non-scientific writing styles closer to the literary options available in postmodern approaches forefronts voices of the researched