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Docume nt and Text Analysis (in field-based research)

INFO 272. Qualitative Research Methods. Docume nt and Text Analysis (in field-based research). Studentship program. See handout Small grants $5000 to do supplemental fieldwork on ‘consumerization’ in existing field sites over the summer, funded by Intel

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Docume nt and Text Analysis (in field-based research)

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  1. INFO 272. Qualitative Research Methods Document and Text Analysis (in field-based research)

  2. Studentship program • See handout • Small grants $5000 to do supplemental fieldwork on ‘consumerization’ in existing field sites over the summer, funded by Intel • Ideally for PhD students already ‘in the field’

  3. Outline Classic Content Analysis Lightweight Document Analysis Heavy-duty Document Analysis Analyzing documents in context Analyzing the contents of documents in isolation Systematic collection and analysis of documents in context in order to define requirements, improve business processes [see Glushko 2005]

  4. Review of Readings • What accounts for incomplete, badly kept records? • What is the context within which records are produced?

  5. Classic content analysis

  6. Units and Dimensions • Syntax vs. Semantics • Units: Words, sentences, paragraphs, articles • Also, propositional units • “biotechnology, the most recent among post-war base technologies, enters the public arena in the 1990s” • “biotechnology enters the public arena in the 1990s” • “biotechnology is a base technology” • “biotechnology is a base technology of the post-war period” • “biotechnology is the most recent base technology” [Bauer and Gaskell]

  7. Method • Sample documents (can even do a random sample) • Divide documents into units • syntactical vs. semantic elements • Articles, words, sentences, themes, propositions • Construct a coding frame and assign codes to units • Calculate frequencies

  8. Word frequency in a 2315-word leaflet on Chronic Fatigue Syndrome produced by CFS patients [source: Prior]

  9. Purpose • Media monitoring – construct a continually updated evaluation frame (an open-system) • Comparisons (between newspapers, between audiences, against standards) • Construct indices (of societal values) – how people describe themselves and ideal partners in lonely hearts columns [Bauer and Gaskell]

  10. Document analysis: Lightweight

  11. Projective Interviewing • Incorporating collected documents into interviews

  12. Projective Interviewing J: “um, I kept the brochure, that said that the church was ‘changing destinies and taking new territories’ and I wondered if you could sort of explain what that means for the church?” M: “yeah, um, changing destinies means that people…look at their lives in a particular way. For example, people who would look at the patterns in their family and they may say well all our family, everybody is an alcoholic so I’m more likely to become an alcoholic or people looking to their families and say that we all come from very poor backgrounds so we are all likely to become poor and so you know, they have a mentality that predates and is based on what they’ve been told…”

  13. World Summit on the Information Society • Content analysis of collected documents • Combined with other forms of data to make an argument about ‘inclusiveness’

  14. Document analysis: Heavy-Duty

  15. Documents in business processes - method • Collect documents (iteratively and according to a logic of selection) • Create a document inventory • Classify the documents • Analyze the inventory • Contextualize docs in interviews • Recommendations [source: Bob Glushko]

  16. Readings: record of medical clinic consultation Examining document contents: • Identify categories • Ordering of text within a unit (i.e. a single entry in the medical record) • The geography of entries • What is not written (economy)

  17. Readings: record of medical clinic consultation Observing documents in the field: • Document within doctor/patient interaction • Written for what audience?

  18. Readings:Outcome of the Analysis Critique of motivation to digitize records: • What are the ‘bad’ organizational reasons for good clinical records? • Systematic data entry interferes with expressing ambivalence, subtlety, with strategic ordering and omission

  19. Document analysis: Final Thoughts

  20. Document characteristics [source: Bob Glushko]

  21. Interrogating your documents • Who is the author? Are they identified or not? • Is it bound with other documents and where is its placement? • What is the document material? • Is it written or printed? What can you say about the fonts, size? • Is a signature on a document required and what does it mean?

  22. In Summary • Limits of content analysis • Lightweight document analysis where documents support central research concern • Heavy-duty document analysis where documents are the central research concern

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