What does it mean if ‘gender’ is statistically significant? Why we can’t interpret our results using the measures ‘man/woman’.

Abstract: This paper advances the following arguments: 1) statistical analyses that categorise participants as male or female produce statistical results that are conceptually unclear and therefore empirically imprecise; 2) the causal mechanisms at work when the sex/gender variable is statistically significant are unclear and under-theorized; 3) exploratory empirical research indicates the inclusion of both gendered attitudes and a sex variable has complex effects on the statistical significance of the sex variable, therefore inclusion of gendered attitudes measures are important to gain a better understanding from where sex and gender based variation comes. Using these exploratory results, I propose a different answer to the question first investigated by Pippa Norris. Whilst Norris found no evidence for the existence of an ideological ‘gender gap‘, my analysis has shown that such a gap does exist.There is a gender gap when measures of gender are included in the analysis, but there is (still) not an ideological sex gap in British men‘s and women‘s political attitudes.