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Challenges and strategies when exploiting data on ethnicity from social survey datasets. Paul Lambert, University of Stirling
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Paul Lambert, University of Stirling
Talk presented to the NCRM seminar ‘What is ethnicity? What methods best capture it?’, part of the NCRM series ‘’Promoting methodological innovation and capacity building in research on ethnicity’, University of Essex, 14th May 2010.
This work draws upon materials from the GEMDE project, a component of DAMES (www.dames.org.uk), an ESRC funded research Node working on ‘Data Management through e-Social Science’
..our response is usually too conservative..
- It’s sparse - It’s collinear (e.g. to age)
- It’s dynamic (cf. comparative research)
‘ethnic identity’; nationality, parents’ nationality; country of birth; language spoken; religion; ‘race’
Social theory is dynamic, fluid, ‘intersectional’, but representative empirical analyses struggles to engage with its terms
Empirical studies are bivariate; descriptive; use low numbers of groups & normalising assumptions
This is ‘conservative’ because..
Choices about recoding, boundaries, contrasts made
[e.g. RAE analysis: Lambert & Gayle 2009]
Management itself influences analytical approaches
1. Arithmetic standardization to re-scale metric values
[zi = (xi – x) / sd]
2. Ex-ante or Ex-post harmonisation
[during data production, or adaptation after the event]
3. Measurement or Meaning/Functional equivalence
[Much comparative research flounders on the apparent impossibility of measurement equivalence and lack of options for functional equivalence, e.g. Van Deth, 2003]
‘One size doesn’t fit all so we can’t go on’
(because of non-linear relations between categories and shifting underlying distributions)
(even if measurement equivalence seems possible)
‘Effect proportional scaling’ using parents’ occupational advantage
..Some options for data on ethnicity..
[e.g. Lambert and Penn, 2001]
[cf. Prandy, 1979; Bennett et al., 2009]
Research applications tend to select a single simplifying collinear categorisation of a concept
To make statistical analyses more robust we should…
=> …development over 2010...