Symeonaki Maria, Stamatopoulou Glykeria, Parsanoglou Dimitrios
Department of Social Policy, School of Political Sciences, Panteion University of Social and Political Sciences, 136 Syggrou Av., 17671 Athens, Greece.
SN Soc Sci. 2023;3(4):67. doi: 10.1007/s43545-023-00651-5. Epub 2023 Mar 22.
Precarity has been established as a central theoretical issue in labour market research and numerous attempts have been made in the past to provide indicators that measure it. Precarity has also been present in political discourse and linked to specific new forms of employment (temporary, part-time, insecure, and atypical amongst others) and certain social groups often defined as vulnerable groups (youth, women, ethnic minorities). However, precarity still remains a phenomenon that needs to be quantified with the use of reliable data. The present paper aims at providing a methodology for measuring individuals that are in precarious employment with data drawn from the EU-Labour Force Survey (EU-LFS). Thus, it presents a way of identifying individuals in the core of precarity and others that belong to this set to a lesser degree. More specifically, four different levels of precarity are identified and the methodology is illustrated and tested for a specific case study, that of Greece. However, the proposed technique can be applied with no or minor modifications to other data sets of EU member states, where the common EU-LFS questionnaire is used. An effort is also made to recognise the socio-demographic characteristics of the individuals that are identified as being precarious belonging to the four levels of precarity and to specify their differences. The analysis yields that as we move from the fist level of weak precarity to the last one of strong precarity the individuals become younger, worse paid and better educated.
The online version contains supplementary material available at 10.1007/s43545-023-00651-5.
不稳定已被确立为劳动力市场研究中的一个核心理论问题,过去曾多次尝试提供衡量它的指标。不稳定也出现在政治话语中,并与特定的新就业形式(临时工、兼职、无保障和非典型等)以及某些常被定义为弱势群体(青年、妇女、少数族裔)相关联。然而,不稳定仍然是一种需要利用可靠数据进行量化的现象。本文旨在提供一种利用欧盟劳动力调查(EU-LFS)数据来衡量处于不稳定就业状态个体的方法。因此,它提出了一种识别处于不稳定核心状态的个体以及其他在较小程度上属于该群体的个体的方法。更具体地说,确定了四种不同程度的不稳定,并针对希腊这一特定案例研究对该方法进行了说明和测试。然而,所提出的技术可以在不做或仅做微小修改的情况下应用于使用通用欧盟劳动力调查问卷的欧盟成员国的其他数据集。还努力识别被确定为处于四种不稳定程度的不稳定个体的社会人口特征,并明确他们之间的差异。分析结果表明,随着我们从第一级的轻度不稳定状态过渡到最后一级的高度不稳定状态,个体变得更年轻、收入更低且受教育程度更高。
在线版本包含可在10.1007/s43545-023-00651-5获取的补充材料。