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 1. Field note summaries and themes 2. 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) 3. Taxonomies (organisation of knowledge into discrete categories) 4. Typologies (classification within one group) 5. Frame analysis (deliberate imposition of frames on the data) 6. Social network analysis (identification of social relationships) 7. 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?