Session Information
02 SES 12 C, Inclusion I: Skills & Identity
Paper Session
Contribution
Enabling active, constructive and fruitful participation in society is generally accepted as a goal for education (Nicaise 2012, Essomba 2012, Zemaitaityte 2014). In the latest ranking of happiness 2015-2018, for example, Finland, Norway, Denmark, Iceland and Sweden are all among top ten countries (Helliwell, Layard & Sachs, 2018). That said, it could be argued that the Nordic countries have succeeded in promoting successful participation in society. Because they have managed to make their citizens relatively happier than other countries, they have succeeded in creating inclusive societies.
At the same time it is acknowledged that social inclusion is a many-sided and multilayered phenomenon. It is dependent on the broadness of perspective taken into inclusion, and whose perspective is taken as a starting point. There is no agreement on what is counted as a satisfactory level of social inclusion and how much various indicators of inclusion should be emphasized if the level of inclusion is estimated. These indicators of inclusion can include employment, satisfactory familial life, the level of consumption, the number of memberships in various societies, or other participation in civic society in one or more roles. Individual´s interpretation of his or her level of (satisfactory) social inclusion may also be in contrast to that of a policy-maker counting the costs of unemployability. Furthermore, some forms of participation (employment) may take time away from other forms of participation that an individual could personally value more (like hobbies or familial activities). The role of education for social inclusion can be seen as important, because a strong correlation has been found between level of education and the poverty risk of households (Nicaise 2012).
VET forms a considerable part of youth education in many countries and it promotes employability. Therefore VET´s affects regarding labour market success have been an issue of research interest for a long time (e.g. Shavit & Muller 2000). Employment and related income also create opportunities for other societal participation. Therefor employment is often taken as an important indicator of social inclusion.
In the Nordic countries, labour market has many similar characteristics, like centralized bargaining, industrial relations based on seeking consensus and that the labour protection is relatively strong (Jorgensen 2018). However, their VET systems differ with respect to their position in the education system, and the stratification of VET and general education on the upper secondary level. Thus, they form an interesting group of countries for the comparison of VET´s effects on social inclusion. Often, it is considered that apprenticeship –based VET systems have stronger labour market outcomes than school-based VET systems. However some results considering short-term and long-term labour-market outcomes of general and vocational upper secondary education suggest that VET graduates may be in the long run disadvantaged compared with others (e.g. Hanushek, Schwerdt, Wössmann, & Zhang, 2017). The effects of education on occupational rewards have been found dependent on the stratification and standardisation of VET systems (Allmendinger, 1989).
In order to study VET education´s relations with social inclusion we utilize PIAAC 2011 data to compare how Nordic countries with traditionally more school-based models of VET (Sweden and Finland) differ from those with a more mixed (Norway) or work-based model of VET (Denmark).
In this presentation, we explore first, how does the human capital gained in different forms of VET differ (RQ 1). Secondly we compare the findings from Nordic countries with respect to how does the human capital gained through basic education, VET or higher education relate to different levels of social participation (RQ2).
Method
The study utilizes ‘The Programme for the International Assessment of Adult Competencies (PIAAC)´ 2011 data. Altogether the Nordic data consists of 22389 adults’ (age 16–65 years) responses, as the numbers of respondents from Nordic countries were the following: Swedish n=4469; Danish n=7328; Norwegian n=5128; Finland n= 5 464 adults. PIAAC data were gathered from both a background questionnaire and a test of literacy, numeracy and problem-solving skills in technology-rich environments (TRE). The data (PIAAC 2011) provides a rich source of data for analysing a number of labour market issues. These include the relationship of proficiency in information-processing skills and other components of human capital to employment and wages. It is also possible to explore the effectiveness of the labour market in ensuring a good match between workers’ qualifications and skills and the demands of their jobs. (OECD 2012). Furthermore, the data enables the Nordic country comparisons of the cultural engagement, political efficacy, social trust and health, the elements of which were included in the questionnaire. We focus on Nordic countries´ comparisons. First, we describe (RQ1) How does the human capital gained in different forms of VET differ? In order to study the differences between school-based and work-based models of VET in terms of their outcomes with respect to human capital, we compare more school-based models of VET (Sweden, Finland) with those representing more mixed and apprenticeship-based models of VET (Norway, Denmark). Secondly we explore (RQ2) How does the human capital gained through basic education, VET or higher education relate to the indicators of some dimensions relevant to social participation (employability, cultural engagement, political efficacy, social trust and health). The analysis will be conducted in two phases. First, we will apply descriptive statistics to illuminate how does the human capital gained in different forms of VET differ. Second, we will use more sophisticated statistical methods taking into account the sampling design in order to study the differences between school-based and work-based models of VET in terms of their outcomes with respect to human capital. In this study PIAAC sample weights are used. Weighting incorporates several features of the survey: the probabilities of the selection of the units, the non-response and differential response rates among subgroups, for example. The weights ensure that the data and the conclusions are representative of the target population (Mohadjer, Krenzke, Vand de Kerckhove & Hsu 2013).
Expected Outcomes
The previous comparisons of Nordic countries based on PIAAC data have shown, for example that the adults´ level of participation in non-formal and formal education is lower among those who have only basic school as their highest level of education (Fridberg et al. 2015). This study focusses on the relations of education to other dimensions of social participation (employability, cultural engagement, political efficacy, social trust and health). The outcomes of the study deepen understanding about Nordic countries’ differences with respect to the relations of VET and social inclusion. The findings also enhance further discussion on the complex and multilayered role of the relations of VET and social inclusion.
References
Allmendinger, J. (1989). Educational Systems and Labor Market Outcomes. European Sociological Review, 5(3), 231-250. Retrieved from http://www.jstor.org/stable/522338 Dieckhoff, M. (2007). Does It Work? The Effect of Continuing Training on Labour Market Outcomes: A Comparative Study of Germany, Denmark, and the United Kingdom. European Sociological Review, 23(3), 295-308. Retrieved from http://www.jstor.org/stable/4621224 Essomba, M.-À. (2012). Immigration, society and education in the EU: Towards an educational policy promoting full social inclusion, Cultura y Educación, 24:2, 137-148, DOI: 10.1174/113564012804932074 Fridberg, T., Rosdahl, A., Halapuu, V., Valk, A., Malin, A., Hämäläinen, R., . . . Mellander, E. (2015). Adult Skills in the Nordic Region : Key Information–Processing Skills Among Adults in the Nordic Region. Nordic Council of Ministers. TemaNord, 2015:535. doi:10.6027/TN2015-535 Hanushek, E. A., Schwerdt, G., Wössmann, L., & Zhang, L. (2017). General education, vocational education, and labor-market outcomes over the lifecycle. Journal of Human Resources, 52, 48-87. Helliwell, J., Layard, R., & Sachs, J. (2018).World Happiness Report 2018, New York:Sustainable Development Solutions Network. https://s3.amazonaws.com/happiness-report/2018/WHR_web.pdf Mohadjer, L., Krenzke, T., & and Van de Kerchove, W. 2013. Survey Weighting and Variance Estimation. Technical Report of the Survey of Adult Skills. (PIAAC). Chapter 15. OECD. http://www.oecd.org/skills/piaac/_Technical%20Report_17OCT13.pdf OECD (2012). Literacy, Numeracy and Problem Solving in Technology-Rich Environments: Framework for the OECD Survey of Adult Skills,OECD Publishing. Nicaise, I. (2012) A smart social inclusion policy for the EU: the role of education and training. European Journal of Education 47 (2), 327-342. Jørgensen, C. H.(2018). Vocational education and training in the Nordic countries: Different systems and common challenges. In C.H. Jorgensen, O. J. Olsen & D. Persson Thunqvist (Eds.) Vocational Education in the Nordic Countries: Learning from Diversity (pp. 2-28). Oxon: Routledge. Shavit, Y. & Muller, W. (2000) Vocational Secondary Education, European Societies, 2:1, 29-50, DOI: 10.1080/146166900360710 Zemaitaityte, I. (2014) Older adult education in Lithuenian aging society. Older adult education in Lithuanian ageing society. SHS Web Conferences 30, 00023 (2016). DOI: 10.1051/shsconf/20163000023
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