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  1. Farewell to What happened to qualitative = small? Lyn Richards

  2. A fiery horse with the speed of light, a cloud of dust, and a hearty – “Hi-Yo, Silver!” The Lone Ranger! With his faithful Indian companion, Tonto, the daring and resourceful masked rider of the plains led the fight for law and order in the early West. Return with us now to those thrilling days of yesteryear...   The Lone Ranger rides again!

  3. What’s the issue? • Qualitative research is still, in much of the literature, presented as a solo act. • Small is written as not only beautiful but morally or methodologically preferable. • As in the finest traditions of our culture, lone is noble. A powerful tradition needs a name – call it ‘Trad-qual’.

  4. What’s the issue? • In this context, new pressures for many reasons towards “team” and large projects; • Continuing rejection of these as “not really qualitative”; • But very little exploration of the reasons for the trends; • Still amazingly little clarity about what is “really qualitative”.

  5. What’s the message? • An extraordinarily perceptive lone researcher labours to create “indepth” understanding from small bodies of (amazingly rich) data and achieve interpretative breakthrough.

  6. What’s the problem? Lone-and-Small ideal needs rethinking. • In reality, qualitative research is often, even usually, just not like that. • Which is just as well, since that “ideal type” of lone researcher is far from ideal – indeed, might be regarded as dubious. • Yet the myth of the “loss” of the lone researcher in the precious small project has serious results for debate about trends and growth of method.

  7. 1. It’s not even usually like that. • Not lone • Not small • Breakthrough is not a method

  8. Not (usually) lone! • The literature has always ignored the normal use of research assistance (reports obscure or even deny the RA role and its significance) or colleagues. With his faithful Indian companion, Tonto, the daring and resourceful masked rider of the plains led the fight for law and order… • Group (or “team”) qualitative projects are now normal. (A note: given the corporate poisoning of the perfectly good word “team”, I’ve decided to use “group”.)

  9. Not (always) small • Projects break bounds of small scale – and always did - good and bad reasons. • The question couldn’t be answered small  • Comparison over time or place proved necessary  • The researcher didn’t know how to stop  • More recently, it’s normal to have qualitative research designed as large scale. For good  and bad  reasons!

  10. Breakthrough is not a method • Most literature that promotes the lone researcher ideal says little about what they do with data – or how breakthroughs can be validated. • A newer literature advising on handling data is interestingly free of the assumption that data are handled by a lone analyst.

  11. 2. And it’s often not the ideal! • Issues of lone researcher’s: • resources and skills; • research process. • Issues of small scale • Limited scope for establishing reliability or rigor; • Little and local theories.

  12. Loner’s resources and skills Lone researcher may have more trouble than those working in groups with: • Finding, understanding and balancing variety of viewpoints; • Providing all skills needed for the project; • Time! And competing demands; • Confidence and encouragement • Background and fit in the field to cover all aspects of the topic.

  13. Loner’s research process Lone researcher must achieve without help: • Weighing hunches and evidence; • Challenging assumptions and seeing the new; • Validating interpretations; • Getting the big picture. More likely than the group to get bogged in detail, unable to see and develop categories. In years of working with researchers, I’ve learned that those who work solo are always helped by discussion. Qualitative research by its nature is arguably best done in groups.

  14. Small project outcomes • Rigorous qualitative research requires: • Sufficient data for productive comparison; • Sufficient scope and exploration for confidence in “saturation”. • Theorizing in small project works only when • the question is small – and many aren’t; • the goal is only local theory – and what Strauss called local “islands” of theory may not be enough.

  15. So why is lone-and small ever ideal? Assumption probably has two sources: • In the education system - most lone researchers have little choice (graduate status, requirements of degrees etc.) • Longtime (now false) assumption that large scale data could not be managed if records were qualitative.. • Since these assumptions stay unchallenged, nobody asks why qualitative should be lone and small. (That’s how myths work.)

  16. 3. But myths have real results. Does it matter? Yes! From myths come • Great expectations • And odd explanations!

  17. Great expectations • Lone and small projects are cited as the ideal, so researchers strive for them. • Teams must meet Trad-qual standards assumed for small, “indepth” projects, e.g. • Line by line analysis • Detailed knowledge of cases and contexts • (It’s working both ways. Often, now, lone researchers are required to meet standards set for teams – coding consistency etc.)

  18. Odd explanations: enter software Part of the myth is that software is to blame for shift from lone to team, small to large. This needs serious investigation: • What did software offer – and what’s its relation to Trad-qual ideas? • Did software possibilities change method? • If so, why? Tools don’t change methods – researchers have to want to use them, then do so, and invent new methods with them.

  19. Software, groups and bulk data • Software of course is relevant to groups • Group members can better record and track and contribute to others’ interpretations; • merging and comparing projects is easy and reliable, offering new ways of collaborating. • And notoriously relevant for bulk data: • Computer handling of bulk data is rapid and (usually) safe, software does mechanical jobs; • Sophisticated combination of qualitative and quantitative analysis is possible, fairly easy and (if well done) powerful.

  20. What did software DO? None of these developments was in a straight line from Trad-qual ideas. But few were inimical to that tradition. For a start, distinguish between • changes that develop traditional methods in ways we couldn’t before – and arguably change the method (e.g. open coding from a node); • changes that are quite new or challenge tradition, allow us to handle data in new ways, opening new sorts of analysis. You know it’s new because names have to be invented (e.g. coding on).

  21. New tools for old methods? • Many, maybe most of the changes software brought neither encouraged nor required bulk data. They were designed as tools for Lone-and-Small research. • But the same tools made it possible to attempt handling of large quantities of qualitative data in ways that ensured: • Data processing could be relatively rapid; • Analysis could be rigorous; • Links could be made to quantitative analysis.

  22. New tools for old methods? So group and large qualitative projects became • possible; • much more common; • a new source of changed expectations.

  23. New methods for bulk projects: In this space, just two examples. • Mechanical coding gives effectively instant access: • text search • autocoding Not merely speeding projects – also changes coding practices as researchers delay fine coding till dimensions can be identified. • Handling of attributes alongside the unstructured data gives a quite different ability to find and pursue patterns and themes.

  24. New methods for qualitative teamwork: Challenges for teams are mainly about communication. Software made possible: • sharing and comparing interpretations; • defining and discussing categories as they are constructed; • presenting and reviewing alternative explanations and theories. Handling Qualitative Data (2005) first book teaching team techniques for each task – because teams demanded it.

  25. Software remakes teamwork: NVivo7 was the first QSR software design process specifically considering teams. A few examples: • sharing and comparing interpretations; • folders for memos, group nodes and sources in sets by author, link to content of memos; • defining and discussing categories; • linked memos for nodes, import structure of a researcher’s project to another’s; • presenting and reviewing alternative explanations and theories. • coding consistency report, model groups

  26. Software can also impede teamwork: Warnings to developers creating tools for teams • teams are far less tolerant than lone researchers of slow processes and risks. • tighter deadlines • more data and more complex management Team process is destroyed by delay and data damage.Need rapid retrievals and reports that are finely editable to suit the project’s needs. • Team qualitative research is currently highly problematic but evolving as we speak – two reasons why it would be useless to design software for what current teams currently do.

  27. Story so far… • Lone-and-small myth always needed challenging • Group-and-large became possible with software. But new tools alone can’t explain a methods shift – researchers have to want to use them! The software blame argument assumes researchers ran amok with scale just because they could. Instead, ask: why did some (not all!) researchers move to groups and large projects when software allowed them?

  28. “Software was a silver bullet..?” Said with scorn – those using software saw it as the answer to all their problems. Silver bullets would make an interesting thesis topic – (another time!) • "Silver?" Jim asks. "Why in the world would you want silver bullets?" The ranger explains that the silver bullets will be a symbol of justice. If software was a silver bullet to qualitative researchers, what was their problem needing magical and righteous solution (and who was being shot at)?

  29. What is the motivation to shift modes? Time to face the possibility that change was at least partly driven by frustration in some research areas at traditional projects. • Software didn’t require either groups or large projects; • But it supported research across even large groups; • Handling of large data bases became not only possible, but different - more rigorous, more productive of new insights than small projects.

  30. So how to rethink the assumptions? • Can we break the nexus of research setting and size? • Can we get the assumptions about what’s “really” qualitative out and look at them?

  31. Challenging assumptions (with a bit of dimensionalising…) Lone-and-Small are seen as necessary – and Group-and-Big as problematic - in three dimensions of qualitative method: • data handling • depth of interpretation • the process of theorizing.

  32. LONE as necessary… The lone researcher is seen as necessary (though note, not sufficient!) for • data handling that is consistent, one person’s concentrated work • depth of interpretation – one researcher “really knowing” • the process of theorizing – “aha”. (Theory won’t “emerge” if many people watch!) Hence GROUP research is regarded as problematic in all three dimensions.

  33. SMALL as necessary… A small data set is seen as necessary (not sufficient) for • data handling in sufficient detail • depth of interpretation – too much data means superficial reading or mechanical handling • theorizing that makes local theory out of the data, rather than merely apply prior theory. Hence LARGE projects can’t be really qualitative.

  34. But these are different dimensions! The researcher’s social setting and the data’s bulk may not be related. So why is Lone-and-Small contrasted with Group-and-Large? • My guess is it’s because they fall on different sides of the traditional dichotomy of qualitative and quantitative… but I thought we’d disposed of that years ago?

  35. Setting by size gives 4 types

  36. Group Small Projects (GSPs) – Many ways of having a group working qualitatively in a small project. • Mixed methods modes Pat’s lecture coming up – here note two of the many mixed methods ways of doing group small projects • Case study model –from a large project, deriving meaningful cases to study in detail – the small study falls out from the large and if well designed can systematically develop it. • Pilot study model – the traditional qual-first approach where a small study informs a survey.

  37. More Group Small Projects… And other group modes with no mixed methods aspect… • Group small projects that stay small • Task force model – small site studies, creating a local understanding,bringing them together for systematic comparison beyond “islands” of local theory. • Group self study –e.g. in action research, studying the one small site or project.

  38. Group Large Projects (GLPs) – is what they do qualitative? • Most such studies have qualitative data for: • delaying data reduction till informed by the data. • taking of categories out of the data (to use in quantitative analysis or in understanding a situation that wasn’t understood sufficiently to create a priori categories.) • Important in very important areas –wherever we don’t know in advance how people experience their situation. • epidemiology, project evaluation, policy research, community welfare…

  39. And so to the method! What scales to larger projects? With software tools, three critical aspects of qualitative method can scale up: • delaying data reduction (coding to retain not dispose of data); • using interpretative processes for taking categories out of the data; • learning from the data, finding new understanding. All are central to what we are trying to do when we work qualitatively.

  40. “Qualitative” is not threatened? What was central to qualitative research wasn’t the lone researcher in small scale. (What was central to truth and justice wasn’t a bloke in a mask, let alone the American Way.) • What’s central is research skills for listening to and learning from data; • May be inductive purpose, theory-testing or deductive. Qualitative research has many relationships to theory.

  41. “Qualitative” can be large? • Of course! Qualitative requires small only if it’s tautological – qualitative = small. • Most rules for handling data scale up: e.g. • attend to the words people themselves use and ensure you understand them – in vivo coding • be alert to recurrences; if it recurs, it matters • Quality of the research is another dimension– and it’s an open question whether large or small projects are more likely to be bad. • That’s not my job today. (But it’s a start to admit bad projects come in all sizes.)

  42. Of course, “qualitative” need not mean you like what they do! • Group-and-Large research is more likely than lone-and-small to be in the commercial “real world” (because of time constraints and the need to impress clients.) • But Lone Researchers have no guarantee of commercial innocence… • Yhe purposes to which a method is put represent yet another dimension.

  43. If qualitative projects are large… Of course other, different rules apply: • Different requirements for data management • Different analysis processes • Different rules for checking and validating conclusions. We need much more literature here. One of the greatest problems of large scale qualitative research is the tendency of researchers to assume it’s the same game played on a bigger field. (Join me in a book?)

  44. What’s to be done? • Break the nexus of lone-and-small to open new ways of thinking design; • Develop methods and standards of rigor appropriate to different research settings and data size; • Design software for small and large projects, with ways of helping the large – so that they help us do it better – and help research take new directions.

  45. The Lone Ranger’s progress “Since 1933, with his faithful companion Tonto, his silver bullets and his unwavering code of honor, this American icon has become an international symbol of truth and justice.” (website)” • radio series - 2,956 episodes, • comic books, books, • two movie serials, TV series (1949 - 1957) • a Saturday morning animated series • Probably a dozen websites, devoted to fanclubs, theories about racism/homophobia and jokes. Now! “the masked hero is set to ride onto the silver screen once again in 2007 with an all-new live action theatrical film” (and a new haircut).

  46. Whither the Lone Researcher? • Please be clear, this is not an argument against traditional qualitative research or against lone researchers in small projects. • It’s an argument for properly celebrating qualitative data analysis and the infinite variety of ways it can be used; • But it’s also a firm statement that rethinking of method is needed urgently. • I’m tired of the undifferentiated disapproval of group and large projects, and the narrow and limiting closed shop of Trad-qual. And I know both damage research.

  47. So to this conference… • Many sessions on researcher role(s) and project scale(s); • Many opportunities to question software tools and argue for issues of design; • And a wonderful open and welcoming setting for critical discussion.

  48. Let’s get on with the job of developing methods and standards for all the many appropriate uses of qualitative research.