1. Qualitative Data Analysis: An introduction Carol Grbich Chapter 3 : Classical Ethnography

2. Classical Ethnography • The design derives from Anthropology • It has been adapted from large scale tribal to small scale groups in urban settings (mini-ethnographies) • It is for researching ‘cultures’ • It is for describing a culture and its operation, rituals and belief systems using observational and other data.

3. Data analysis tools • Field note summariesandthemes • Cultural domain analysis (the development and explanation of the interconnected groupings that make up a culture) • Freelists (identifying what fits into a domain) • Pilesorts (identifying the internal structure of a domain) • Triads (identifying the hierarchies within a domain) • Taxonomies (organisation of knowledge into discrete categories) • Typologies (classification within one group) • Frame analysis (deliberate imposition of frames on the data) • Social network analysis (identification of social relationships) • Event analysis (intensive analysis of a key event

4. Field notes Covert or overt observations and collection of data re: • contextual information (economic, political and social organisations influencing or determining the setting) • language, customs and rituals, events, incidents, shared belief systems, attitudes and understandings of events, behaviour and actions

5. Cultural domain analysis Items and commonalities identified by participants as being within a ‘domain’: • initial data collection, • the identification of the major domains of data e.g. structures and rituals which serve to support, maintain and provide uniqueness to the particular culture under study • further data collection to elicit more detail or to clarify the types/parts of these domains

6. freelists, pilesorts, triads • Freelists – identifying items within a domain through group lists and item frequency • Pilesorts – to identify internal structure of the domain and similarities and relationships among items vie card sorting and frequencies • Triads – to identify hierarchies among items through separation via differences

7. Taxonomies and Typologies Taxonomies Data classification into discrete categories and subcategories (developed or imposed by the researcher) in a hierarchical manner Typologies Classification into one group/class by • collating all data relating to the particular issue • identifying variations, layers and dimensions • classifying into a type/types (subgroups)

8. Frame analysis Process: • Draw frames around transcripts of conversation (a frame is the smallest coherent group of words but frames can also be very broad) • Group frames into categories and name these • Develop larger groupings, often termed galleries (if useful) • Interpret and display

9. Social Network analysis Used to view the formation, dynamics, linkages, context and changes in social networks Process • Identify the people who constitute the group • Assess the relationships in terms of the focus of the research e.g.. lines of power, decision making etc • Produce a graphical analysis – show any changes over time • Confirm with the collection of other data over time

10. Event analysis Process • Describe the event – what actually happened?. Whose perspectives are represented? • What are the structural aspects of the event? Time, space, location, context and culture, • What meanings and actions can be interpreted in the context? How can what went on be explained? • What is the wider impact of the event? (historical links, future potential, or just the impact on those immediately involved) • Classify the event/s – either broadly or break them down into separate parts and place them in related groupings for scrutiny, theory development and writing up • How has the researcher’s representation of the event been affected by the fieldwork situation? their limited access to people? or by their own views developed within their own cultural grouping?