Reading research findings – Kan and Laurie

This week, we revisited the two papers which were introduced in Week 4. As we move into considering data analysis, we were asked to consider a number of questions about each of them.  The second paper, by Paddock, is an account of a quantitative study into the allocation of housework tasks. 

Paper 2: Kan, M-Y., Laurie, H. 2016. Who Is Doing the Housework in Multicultural Britain? Sociology. Available: https://doi.org/10.1177/0038038516674674

Questions for discussion:

1. The researchers here conducted secondary analysis of an existing dataset (the UK Household Longitudinal Study https://www.understandingsociety.ac.uk . What are some advantages and disadvantages of secondary analysis for exploring this topic? (hint: there are some noted at various points in the paper)
   Key advantages:
   – access to a significant data set with over 30,000 respondents aged 16-64 years
   – this is an annual survey so comparative analysis over time can be undertaken
   Key disadvantages:
   – there is no way of knowing if the measures/questions have been ‘interpreted in the same way across all ethnic groups’ (p.7. and p.11).
   – there is a lack of accuracy with regard to self-reporting via survey estimates (compared with ‘more accurate time-diary estimates (p.7).
2. How does the concept of intersectionality allow the researchers to build on previous research in this area?
   Intersectionality is a means of overcoming what the authors of the paper refer to as the ‘ethnicity ‘blind” (p.2) focus of previous research on the domestic division of labour, ‘effectively ignoring potentially significant intersections between gender, ethnicity, socio-economic position and domestic labour’ (p.1). Intersectionality allows for the exploration of structural factors which may inform gender inequalities in the household, such as the ‘double penalties’ (p.4) which may affect ethnic women establishing themselves in the labour market. It also facilitates an examination of the domestic division of labour between men and women and how these might differ across ethnic groups (p.4).
3. Choose a term you aren’t familiar with from the Analysis Approach section of the article on page 8 and do some reading online to find out more about what it means (for example: cross-sectional analysis; multivariate OLS regressions; interaction effects). Can you learn enough about this to explain it in the discussion forum? (if you are already very familiar with statistical analysis, take an opportunity to comment on some other participants’ definitions).
   Multivariate OLS regressions:
   Multivariate regression allows more sophisticated exploration of the interrelationships among a set of variables. Multiple regression can tell you:

    – How well a set of variables is able to predict an outcome

   – Which variable in the set of variables is the best predictor

   – Whether a particular variable is still able to predict an outcome when the effects of other variables are controlled for (Pallant, 2005).* 
4. How do Kan and Laurie go about building a case for the interpretations they are making? How do they compel you, as a reader, to take their findings seriously? Share a specific example of how you think this is done in this article.
   – Extensive reference to other research in the field, including background and theoretical perspectives (p.3 – 4).
   – Explanation of the analysis approach adopted.
   – Systematic testing of hypotheses through an analysis of the data.
   – Acknowledgement of issues and problems with regard to analysis and interpretation of data: ‘It could be argued that survey data are a rather blunt instrument for fully understanding the complexities of the domestic division of labour…’ (p.18)
   – Highlighting the scope of their research and its consequent limitations: ‘Whilst we cannot provide any causal explanation for why we find differences in patterns of domestic labour across ethnic groups, the analysis shows clear associations between gender and ethnicity, education levels, employment status and gender attitudes’ (p.18)

*from https://www.academia.edu/3590600/Introduction_to_Multivariate_OLS_regression_lecture