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'Corpus Construction' as an alternative logic of sampling

This .INFO article discusses the iterative model of research and the process of corpus construction in qualitative research. Topics covered include defining field sites, selecting subjects, data gathering, analysis, and the importance of competence and innovation in research. It also explores different approaches to sampling, including total enumeration, random sampling, and systematic selection. The article concludes by challenging notions of representativeness and emphasizing the importance of theory building.

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'Corpus Construction' as an alternative logic of sampling

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  1. INFO 272. Qualitative Research Methods 'Corpus Construction' as an alternative logic of sampling

  2. The Iterative Model 1) research topic/questions 2) ‘corpus construction’ 3) data gathering Field work 4) analysis 4) more analysis Desk work 5) write-up

  3. ‘Corpus Construction’

  4. ‘Corpus Construction’ • Defining the sites and subjects of field-based research • Making decisions about your field site(s) – how a social phenomenon of interest is mapped out onto spatial terrain • Selecting people to follow, observe and/or interview • Selecting media / artifacts from the setting for further analysis

  5. Competence and Innovation • Competence (Bauer and Gaskell) • Systematic • Issues of public accountability • Innovation (Becker) • Challenge conventional thinking

  6. Doing Innovative Research • Starting Where You Are (Lofland and Lofland) • Commitment and Curiosity • Access and ‘getting in’ • Willingness to go where others won’t • The inconvenient and uncomfortable • The illegitimate

  7. Approaches to Sampling Populations • Total enumeration (i.e. census) • Statistical random sample • Snowball sample (iteration again) • Convenience sample (bad)

  8. Random vs. Systematic • ‘Corpus Construction’ • Typifies unknown attributes • Systematic selection to some alternative rationale (not a convenience sample) • Random Statistical Sampling • Distribution of already known attributes • What can be said about the sample generalizes to the whole population • Popular misconception – the greater the # in the sample, the more accurate

  9. Mapping the Unknowable Social strata, functions and categories (known) Representations (unknown) Varieties of: Belief Attitudes Opinions Stereotypes Ideologies Worldviews Habits Practices [Bauer and Gaskell]

  10. Mapping the Unknowable • Iteration until Saturation • Don’t collect too much data [logistical limits]

  11. Problems of Social Strata in Cross-Cultural Research

  12. Demographic Form

  13. Extending Selection Strategies: Sampling for ‘Innovation’ • Identify the case that is likely to upset your thinking and look for it – (the counter-example) e.g. addicts of opiate drugs • If someone says it has already been studied, its probably time to study it again. • Studying the non-serious and the ‘boring’

  14. Selection from Observation • Description (in field notes) is a selection from what is observed – we do this implicitly [Becker] • done well creates new categories and ideas that ‘get around conventional thinking’

  15. Selecting Field Sites • Some work is clearly ‘sited’ • Some is not (amorphous social settings) – and therefore locating such work will be more involved • Sites may be ‘open’ or ‘closed’

  16. In Conclusion - Representativeness? • The problem of unknowable populations • Rather than ‘representativeness’ we are seeking ‘range’ and diversity in the social phenomenon under study • For what purpose? Challenging notions of what is ‘natural’ or ‘universal’ about a phenomenon – theory building rather than theory testing/refinement

  17. For Tuesday • Read Lofland and Lofland section on logging data • Read UC guidelines for protection of human subjects • We will discuss your first activity – a participant-observation exercise

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