Geographical mobility, children and career progress in British professional nursing.
Previous explanations for the proportional over-representation of men at all levels of the British professional nursing hierarchy above the basic grade are flawed as they use a gender-based framework of explanation. This study presents an empirical test of a non-essentialist explanation which examines geographical mobility as a criterion of exclusion from promotions which has a disproportionately positive effect on the promotion prospects of men. The study uses a national sample survey of 400 male and 400 female nurses. Data are collected on career histories and associated life events. Data are modelled as survival data using a form of the Cox proportional hazard model with residual heterogeneity to examine explanatory variables which affect the hazard of promotion. Geographical mobility, children, decade of qualification, employer moves, part time work and private sector working are all significant explanatory variables (P < 0.05) for the hazard of promotion. Gender is not a significant variable in its own right but two variables exhibit significant interactions with gender. Children negatively affect the career progress of men and women but women's career progress is affected most. Significantly, the effects of children are not due to career breaks or to part time working. Gender essentialist explanations have been shown to be inadequate. Institutional genderism through the process of gender differential application of apparently individualist criteria of exclusion has been exposed. There is now a requirement for policy makers and employers to review procedures in order to avoid these forms of structural institutional genderism and discriminatory practices in employment.
Ratcliffe
P
P
Department of Primary Health Care, St. Martin's College, Cumbria, England. p.ratcliffe@ucsm.ac.uk
D000328:Adult; D000367:Age Factors; D002322:Career Mobility; D002648:Child; D003625:Data Collection / Q000379:methods; D005190:Family; D005260:Female; D006801:Humans; D008297:Male; D009729:Nursing / Q000706:statistics & numerical data; D010865:Pilot Projects; D011287:Prejudice; D016016:Proportional Hazards Models; D013997:Time Factors; D006113:United Kingdom