Abstract
The paper concentrates on the problem of age discrimination in the labour market and the way it can be conceptualised and measured in a multi-disciplinary way. The approach proposed here combines two understandings of age discrimination—a sociological and legal one, what allows for a fuller and expanded understanding of ageism in the workplace. At the heart of the study is a survey carried out in Poland with a sample of 1000 men and women aged 45–65 years. The study takes a deeper and innovative look into the issue of age discrimination in employment. Confirmatory factor analysis with WLSMV estimation and logistic regressions were used to test the hypotheses. The study shows that age discrimination in labour market can take on different forms: hard and soft, where the hard type of age discrimination mirrors the legally prohibited types of behaviours and those which relate to the actual decisions of employers which can impact on the employee’s career development. The soft discrimination corresponds with those occurrences, which are not inscribed in the legal system per se, are occurring predominantly in the interpersonal sphere, but can nevertheless have negative consequences. Soft discrimination was experienced more often (28.6% of respondents) than hard discrimination (15.7%) with higher occurrences among women, persons in precarious job situation or residents of urban areas. The role of education was not confirmed to influence the levels of perceived age discrimination.

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Notes
Prohibition on discrimination was added to the labour code by way of an amendment dated 24 August, 2001 and then altered due to the subsequent code amendments dated 14 November, 2003 and 21 November, 2008. In October 2010 the Act on the Implementation of Certain Provisions of the European Union in the Field of Equal Treatment was passed by the Parliament.
2241 people were sampled and contacted. 1000 respondents who met the inclusion criteria (age 45-65, active in the labour market) were interviewed. Individuals who were retired or received sickness or disability benefits but declared that they were still active in the labour market were included in the research.
The survey was financed by the Polish Ministry of Science and Higher Education within a doctoral research grant.
Previous measures of ageism included: the Attitudes Towards Old People Scale (Kogan 1961); the Fraboni Scale of Ageism (Fraboni et al. 1990) measuring the affective component of ageism; the Palmore Ageism Survey (Palmore 2001); a prescriptive ageism scale (North and Fiske 2013) focusing on prescriptive beliefs concerning potential intergenerational conflicts. Most of these tools measure the cognitive and affective dimensions of ageism and are not designed to study workplace discrimination. Yet this is the aim of the Nordic Age Discrimination Scale (Furunes and Mykletun 2010), which incorporates six items which are supposed to measure the perception of age discrimination among employees. However, it does not assess the experiences of age discrimination among older workers, which might still be disparate from the general view of employees about age discrimination in their workplace.
One of the difficulties faced by researchers when trying to measure age discrimination is the multiple meanings and interpretations of the term “discrimination” in the population. The term has been used extensively in various European Union social campaigns in recent years, and certainly raised awareness of the problem of discrimination, but it has nevertheless also contributed to many false conceptions of what discrimination is (Stypińska 2015). Hence, usage of this word in survey questionnaires poses several analytical and later interpretative problems, as respondents might hold very different ideas and convictions of what discrimination means.
PKD is related to the international Statistical Classification of Economic Activities in the European Community (NACE).
We tested: (1) leaving out item 1 (not hired because of age) slightly improves the model (CFI = 0.989, RMSEA = 0.023) as it correlated only weakly with other variables; item 1 was, however, included in the model because it performed relatively well in CFA (with R 2 = 0.51) and was important for theoretical reasons; (2) connecting item 7 (lower value of outcomes due to age) with both factors was suggested by modification indices and slightly improved the model (CFI = 0.985, RMSEA = 0.026), it also had theoretical premises (in this case the legal interpretation depends on other aspects, like repeatability, intense or consequences—it might be, but does not have to be illegal), but due to complexity in interpretation and further analysis it remained as a measure of the second factor only.
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Stypinska, J., Turek, K. Hard and soft age discrimination: the dual nature of workplace discrimination. Eur J Ageing 14, 49–61 (2017). https://doi.org/10.1007/s10433-016-0407-y
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DOI: https://doi.org/10.1007/s10433-016-0407-y