Abstract
Using data from a 2017 survey of Czech academics this article examines the casualisation of working conditions in the Czech academic labour market (ALM) and explores gender, sectoral, and institutional inequalities through the lens of the theory of labour market segmentation. A hierarchical cluster analysis reveals three segments in the Czech ALM: core (40%), periphery (28%), and semi‐periphery (32%), which roughly align with work positions in the early, middle, and senior stages of an academic career. In the semi‐periphery gender is found to be a key factor in in determining working conditions, while in the periphery working conditions are most affected by the type of institution. In the core, gender differences are mainly reflected in the gender wage gap. The effects of casualisation on working conditions are found to be more pronounced in STEM fields than in the social sciences and humanities across the ALM, but wages are generally higher in STEM fields.
Highlights
Academic labour markets (ALM) in most countries have become more dynamic and competitive in recent decades but have simultaneously seen working condi‐ tions deteriorate
When we focus on hours worked, the statistical significance of gender differences disappears
Just under 40% of Czech academics work in the core segment of the academic market, and they include Czech Academy of Sciences (CAS)‐based senior researchers and HEI‐based full/associate profes‐ sors
Summary
Academic labour markets (ALM) in most countries have become more dynamic and competitive in recent decades but have simultaneously seen working condi‐ tions deteriorate (see, e.g., Kwiek & Antonowicz, 2015; Musselin, 2005). The article contributes to current research on the ALM’s transformation and casualisation in several ways It compares how gender, field, and institutional inequalities are manifested in different segments of the ALM instead of focusing on one ALM segment (e.g., early‐career women academics or seniors are com‐ mon focus topics in the current literature; see, e.g., Bagilhole & Goode, 2001; Bataille et al, 2017; Bozzon et al, 2017; Cidlinská, 2019; O’Connor, 2010). I describe the data and methods used to define and analyse segments of the ALM, and I conclude the article with a discussion of the findings and conclusions
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