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) 

• ADVANTAGES
• The national survey contains sufficient sample sizes of ethic minority groups, including boost samples, in order to generalise comparisons between multi-ethnic populations.
• It represents national sub populations
• It provides quantitative data to offset bias in past literature to qualitative studies in the UK and possible poor representation of the issues for the UK in non-UK quantitative studies.
• DISADVANTAGES
• It notionally applies only to heterosexually married or cohabiting couples.
• Since participants self-identify ethnicity, this will be of importance, especially where a choice of ‘Mixed’ is made.
• They also self-report housework hours – social desirability biases are therefore possible, although checks on this are in place (8).
• Religious affiliations are assumed to not be sufficiently orthogonal to yield results, yet there is no equality between religious affiliation and ethnicity – a South East Asian origin member could be Hindu, Muslim, Buddhist, Catholic, and so on …

2.   How does the concept of intersectionality allow the researchers to build on previous research in this area?

• Studies have shown (4), the significance of interactions between different important variables such as gender, ethnicity and socio-economic status. The researchers do not assume that either gender or ethnicity, etc. are primary determinants of inequalities and will allow them to test intersections between population distinctions and not treat each variable as orthogonal.

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).

• Since I have completed a course at MA level on Advanced Statistical Analysis in Psychological Research, this does not apply. However, happy to look at other contributions as they occr (or if they occur).

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.

• They  compare the descriptions yielded by the data to the expected results or hypotheses, qualifying thise expectations where suggested by data interpretations.
• They describe data graphically, using a range of chart types (10, 12), tables and written verbal descriptions.
• They use multivariate regression analysis to account for interactions and test for significant effects. They do not show interaction effects however from the analysed data (15). To some extent, they leave these for future studies (18).
• They suggest explanations (also supported by descriptive data (14), where possible.
• They summarise findings in relation to their hypotheses (18).