INCLUD-ED
WORKING PAPER WP 11
THE IDENTIFICATION OF GAPS IN THE STATISTICAL DATABASES REGARDING THE CONNECTION OF EDUCATION AND EMPLOYMENT, HEALTH, HOUSING AND
POLITICAL PARTICIPATION
dr. Natalija Vrečer Slovenian Institute for Adult Education Ljubljana, October, 2009
Project 3: Social and educational exclusion and inclusion. Social structure in the European knowledge based society.
Contents
1.	Executive summary.............................................................................................................................3
2.	Introduction.........................................................................................................................................4
3.	Methodology.......................................................................................................................................6
4.	Employment........................................................................................................................................9
4.1	Indicators on employment analysed.............................................................................................9
4.2	The results of previous research on education and employment..............................................11
4.3	The Identification of gaps in databases pertaining to education and employment in a dialogic discussion with end- users and social agents....................................................................................13
5.	Health................................................................................................................................................18
5. 1 Indicators on health analysed....................................................................................................19
5.2 The results of previous research on education and health.........................................................20
5. 3 The identification of gaps in databases pertaining to education and health in a dialogic discussion of end-users and social agents.........................................................................................22
6.	Housing .............................................................................................................................................. 25
6.1	Indicators on housing analysed...................................................................................................25
6.2	The results of previous research on education and housing......................................................26
6.3	The identification of gaps in databases pertaining to education and housing in a dialogic discussion of end-users and social agents.........................................................................................27
7.	Political participation.........................................................................................................................30
7.1. Indicators on political participation analysed............................................................................30
7.2 The results of previous research on education and political participation.................................35
7. 3 The identification of gaps in the area of political participation in a dialogic discussion of end-users and social agents ...................................................................................................................... 36
8.	Conclusion ......................................................................................................................................... 40
9.	References.........................................................................................................................................42
1. Executive summary
The working paper was done in the scope of Workpackage 11 of Project 3 of the Included Project. The specific objective for Workpackage 11 was to analyse educational exclusion and inclusion and its connection to social exclusion and inclusion in the different areas of society (i.e. employment, health, housing and political participation) (Annex 1, Crea, 2006: 37).
In order to reach this objective the partners of the Included project did the secondary analysis of existing datasets and thus they identified the relationship between educational exclusion/inclusion and social exclusion and inclusion in European Union. Statistics on employment, health, housing, education and political participation were collected from European databases, and member states databases. The following databases were used: EUROSTAT, OECD, EUROBAROMETER, European Social Survey, World Values Survey and national statistics offices.
The objective of this working paper is to identify the gaps of data not covered in existing databases. The identification of gaps served to identify the data or indicators which are unavailable and which are necessary to confirm the knowledge provided by theoretical contributions as for example the analysis of literature which was done in Workpackage 10. The indicators which do not provide a connection with education were considered gaps of information as well; therefore the attention was paid to them as well. The identification of gaps was also based on a dialogical discussion with end-users (members of vulnerable groups) and social agents (such as NGO's, public administrations' and other entities' representatives). The interviews with end-users and social agents confirm our findings.
In suggesting new data and indicators we followed the principle of selectivity and suggested only those that seem absolutely necessary. In all four fields of society: employment, health, housing, political participation we found out that data are usually not gathered for vulnerable groups, especially for Roma and persons with disabilities. As those groups of people are still marginalized in contemporary societies, we need such
data also for vulnerable groups in order to encourage the change of exclusionary policies into more inclusionary ones.
2. Introduction
This working paper entitled The identification of gaps in the statistical databases regarding the connection of education and employment, health, housing and political participation was written in the scope of Workpackage 11, Project 3 of the Included project (Strategies of inclusion and social cohesion in Europe from education, funded by European Commission, in the scope of the 6th framework programme). The general objective of Project 3 was to study how educational exclusion affects diverse areas of society (i.e. employment, housing, health, political participation) and what kind of educational provision contributes to overcome it (Annex 1, Crea, 2006: 5). The specific objective for Workpackage 11 was to analyse educational exclusion and inclusion and its connection to social exclusion and inclusion in the different areas of society (i.e. employment, health, housing and political participation) (Annex 1, Crea, 2006: 37).
In order to reach this objective the partners of the Included project did the secondary analysis of existing datasets and thus they identified the relationship between educational exclusion/inclusion and social exclusion and inclusion in Europe (EU 25). Statistics on employment, health, housing and political participation were collected from European databases, and member states databases. The following databases were used: EUROSTAT, OECD, EUROBAROMETER, European Social Survey, World Values Survey and national statistics offices.
Crea, (University of Barcelona, Spain) did the analysis of the statistics on the connection between education and employment, Duk, (Donau-Universitaet Krems, Austria) did the analysis of the statistics on the connection of education and health, UNIFI (University of Florence, Italy) did the analysis of the statistics on the connection of education and housing and BISS (Baltic Institute of Social Science, Latvia) did the analysis of the statistics on the connection of education and political participation. The main objective of this secondary data analysis was to obtain indicators on educational
exclusion/inclusion and the connection that these have on social exclusion and inclusion. Special attention was paid to five vulnerable groups (women, youth, ethnic minorities, migrants, people with disabilities). This working paper is based on the results of other partners' working papers in the specific areas of society.
After this analysis was done, the task of SIAE was to identify the potential gaps of data not covered in existing databases. The identification of gaps served to identify the data or indicators which are unavailable and which are necessary to confirm the knowledge provided by theoretical contributions as for example the analysis of literature which was done in Workpackage 10. The indicators which do not provide a connection with education were considered gaps of information tool; therefore the attention was paid to them as well. The identification of gaps was also based on a dialogical discussion with end-users (members of vulnerable groups) and social agents (such as NGO's, public administrations' and other entities' representatives). This Working paper includes also the orientations for the EU to cover the gaps identified by end-users and social agents.
In proposing the indicators which are needed in EU databases, we followed the criteria of selectivity, which refers to the selection of choice of indicators, namely Bevc et al (2005) think that it is better to limit the choice to the smaller number of most important indicators of wider scope which are easily manageable and reviewed. According to the authors mentioned, if we do not have enough indicators, we cannot see clearly the object of our observation, but if we have too many indicators we are in danger that we will not see the forest for the trees. Bevc et al (2005) mention the example of European Commission in creating the empirical base for monitoring the implementing of the Lisbon strategy. In 2000 there were 27 strategic structural indicators, however, the number grew to 107 indicators in 2002. In 2003 they decided to include only 14 key indicators, the rest of them were included in the subsidiary database.
The interview results show that the interviewees in general agree with our
suggestions for new data or indicators. However, one interviewee who is a university professor dealing with housing issues commented that it is not only the problem of getting missing indicators, but we also have to make better use of already existing indicators.
In the Working paper we firstly present our methodology, then we present the existing indicators that we analysed for each of the four sectors of society: employment, health, housing, social and political participation. Then we write about the results of our previous research, then follow our suggestions for new data and indicators for each aforementioned area of society, the analysis of the interviews follows.
3. Methodology
The identification of gaps in the statistical databases regarding the connection of education and employment, health, housing and political participation was done on the basis of the selection of relevant indicators and on the analysis carried out in the different areas of study provided by the above-mentioned partners. The identification of gaps was also based on a dialogical discussion with end-users and social agents; therefore we did the interviews as well. Namely, it is the emphasis of critical communicative methodology developed by CREA to research with the people and not on people (Flecha, Gomez, 2004). Thus people become active participants in the research process, as the latter is based "on dialogue and information exchange among researchers and researched social agents" (Flecha, Gomez, 2004: 129).
We did 12 standardised open-ended interviews in Slovenia in the fields of employment, health, housing and political participation. In the field of employment we did 3 interviews: 1 with an end-user, a person excluded from employment and 2 with social agents (1 with a person from the public administration who works on employment and 1 with a person from the NGO related to employment - trade union). In the field of health we did 3 interviews as well: 1 with an end-user, a person excluded from health services and 2 with social agents (1 with a person from the public administration who works on health and 1 with a person from the NGO related to health). In the field of housing we did 3 interviews as well: 1 with an end-user, a person excluded from housing and 2 with social agents (1 with a person from the public administration who works on housing and 1 with a university professor who deals with housing issues). In the field of political participation we did 3 interviews as well: 1 with an end-user, a person excluded from political participation and 2 with social agents (1 with a Slovenian parliamentary and 1 with a person from the NGO related to political participation).
Areas of society (4)	Persons to be interviewed (12)		
Employment	A person excluded from employment	A person from administration who works on employment	A person of the NGO related to employment
Health	A person excluded from health services	A person from administration who works on health services	A person of the NGO related to health
Housing	A person excluded from housing	A person from administration who works on housing	A university professor dealing with housing
Political participation	A person excluded from political participation	A member of the Slovene parliament who is very active regarding political participation	A person of the NGO related to political participation
The interviews were transcribed verbatim and coded. We endeavoured for the anonymity of all the participants in the research process.1 Each transcript code includes the following information: person (E- excluded person, P - a member of public administration or a parliamentary, N - NGO member or a university professor); technique (I - interview); area (E - employment, He - health, Ho - housing, P - political participation); gender (F - female, M - male); the number of interview (1-3 for each area of society).
1 The interview sheets with their real names are available in our private database in order to assure confidentiality.
Code	Description of an interviewee
EIEF1	Person excluded from employment. Female. She holds B. A. in andragogy.
PIEF2	Policy maker at the Employment Service of Slovenia. Female. She has a university degree.
NIEM3	Ngo member. Male. An assistant to the general secretary of trade union SVIZ - Education, Science and Culture Trade Union of Slovenia. He has a university degree.
EIHeF1	Person excluded from employment. Homeless female. She has accomplished vocational secondary school.
PIHeF2	Policy maker at the National Public Health Institute. Female. She has postsecondary vocational education.
NIHeF3	NGO member of Europa Donna, Association of oncological patients. Female. Retired. She has M. A.
EIHoM1	Excluded from housing. Male. He has accomplished vocational school.
PIHoF2	Policy maker, a directress of the Housing fund of the Municipality of Ljubljana. Female. She holds a university degree.
NIHoF3	Researcher in housing issues Faculty of Social Sciences, Ljubljana. Female. She holds Ph.D.
EIPM1	Excluded from political participation. Male. He has accomplished primary school.
PIPF2	Member of a Slovenian parliament very active in political participation issues. Female. She holds M.A.
NIPM3	Member of the Association of erased inhabitants of Slovenia. Legal representative of the so called "erased" people. Male. He holds LLM.
4. Employment
4.1 Indicators on employment analysed
Educational attainment, employment and unemployment
■	Employment by sex, age and highest level of education attained (EUROSTAT)
■	Employment rates by sex, age groups and highest level of education attained (%) (EUROSTAT)
■	Employment rates and educational attainment (2006) (Education at a Glance, 2008)
■	Unemployment by educational attainment, age and sex (EUROSTAT)
■	Unemployment rates and educational attainment, by gender (OECD)
■	Trends in employment rates by educational attainment (OECD)
■	Trends in unemployment rates by educational attainment, (OECD)
■	Activity rates by sex, age groups and highest level of education attained (EUROSTAT)
■	Active population by sex, age groups and highest level of education attained (EUROSTAT)
■	Inactive population by sex, age groups and highest level of education attained (1000) (EUROSTAT)
■	Employment status (World Values Survey)
■	How long unemployed (World Values Survey)
■	Year last in paid job (European Social Survey)
■	Main activity, last 7 days. All respondents. Post coded (European Social Survey)
Educational attainment and earnings
■	Relative earnings from employment by level of educational attainment and gender (OECD)
■	Relative earnings of the population with income from employment (2006 or latest
available year) (Education at a Glance, 2008)
■	Differences in earning between females and males by level of educational attainment (OECD)
■	Mean hourly earnings by economic activity, sex, educational attainment (EUROSTAT)
■	At risk of poverty rates by educational level (EUROSTAT)
■	In-work at risk of poverty rates by educational level. (EUROSTAT)
■	Income (World Values Survey)
■	Get paid appropriately, considering efforts and achievements (European Social Survey)
Educational attainment, employment and age
■	Employment by sex, age and highest level of education attained (EUROSTAT)
■	Employment rates by sex, age groups and highest level of education attained (%) (EUROSTAT)
■	Unemployment by educational attainment, age and sex (EUROSTAT)
■	Unemployment rates by sex, age groups and highest level of education attained (%) (EUROSTAT)
■	Youth transitions from education to working life in Europe / LFS 2000 (EUROSTAT)
■	Young people social origin, educational attainment and labour outcomes in Europe (EUROSTAT)
■	Activity rates by sex, age groups and highest level of education attained (EUROSTAT)
■	Active population by sex, age groups and highest level of education attained (EUROSTAT)
■	Inactive population by sex, age groups and highest level of education attained (1000) (EUROSTAT)
Educational attainment and the quality of job
■	Employed in service sector and occupational status of recent school-leavers (EUROSTAT)
■	Employment by sex, occupation and highest level of education attained
(EUROSTAT)
■	Full-time and part-time employment by sex, age groups and highest level of education attained (1000) (EUROSTAT)
■	Job mismatches and their labour market effects among school leavers in Europe (EUROSTAT)
■	Often exploited in your job (World Values Survey)
■	Job satisfaction (World Values Survey)
■	Satisfaction job security (World Values Survey)
■	Profession/job (World Values Survey)
■	Nature of tasks: manual vs. Cognitive (World Values Survey)
■	Nature of tasks: routine vs. Creative (World Values Survey)
■	Nature of tasks: independence (World Values Survey)
■	Employment status (World Values Survey)
■	Total contracted hours per week in main job overtime excluded (European Social Survey)
■	Total hours normally worked per week in main job overtime included (European Social Survey)
■	Allowed to decide how daily work is organised (European Social Survey)
■	Allowed to influence policy decisions about activities of organisation (European Social Survey)
■	Employment contract unlimited or limited duration (European Social Survey)
■	Find job interesting, how much of the time (European Social Survey)
■	Find job stressful, how much of the time (European Social Survey)
■	Employment relation (European Social Survey)
4.2 The results of previous research on education and employment
Let me first summarize briefly some results of the previous research on education and employment done in the scope of the Included project. Crea (2008) found out that there is a connection between being excluded from education and being unemployed or experiencing more difficulties in the labour market. Higher levels of education lead to better opportunities in the labour market. Crea (2008) found out that lower levels of education, dropping out, lack of literacy skills, leaving the education system at an early age are connected to immediate problems in searching for the job and long-term
unemployment. There is a connection between exclusion from education, lack of literacy skills, lower qualifications and the stability of jobs, lower salaries, non-standard employment contracts and lower productivity (Hibett, Fogelman, Manor, 1997; Hartley, 1989 in Crea, 2008). Low levels of education affect not only employees but also employers and a society as a whole. Especially vulnerable groups regarding exclusion from education and employment are youth excluded from education, female migrants and ethnic groups (Kettunen, 1997; Wolber, 2000; Descy 2002 etc., in Crea, 2008). The aforementioned coordinators of the Included project mention also that exclusionary practices in education such as dropping out, truancy, tracking and streaming create segregation and exclusion from the labour market. The authors agree that further education, higher educational level, inclusion in the lifelong learning process and better literacy skills increase employment duration, chances of being reincluded in the labour market and higher quality and stability of employment.
The results of the secondary data analysis confirmed these findings. Crea (2009) found out that the levels of education have an impact on employment and unemployment rates, earning and job quality. Namely, the existing data related to employment reveals connections between educational exclusion/inclusion, measured as the level of education attained, and social exclusion/inclusion in the field of employment. Educational inclusion has positive long-term effects on workers' life, it is related to better employment conditions such as employment rates, earnings or the job quality (Crea, 2009). As regards gender, the same institution found out that the inequalities of women are maintained at all levels, however, for low educated women, these inequalities even increase. The quality of job contracts is also influenced by the level of education that a person attained.
People with low education are more likely to work without a contract, to work more contracted hours, while people with higher education are more likely to have higher rates of unlimited contracts. Besides, people with higher education have higher salaries and are less at the risk of poverty than people with low educational levels attained are. Lower education is also connected to higher occurrence of jobs mismatches (Crea, 2009).
4.3 The Identification of gaps in databases pertaining to education and employment in a dialogic discussion with end- users and social agents
The objective of these interviews is to analyse the educational exclusion and inclusion and its connection to social inclusion and exclusion from employment. Specifically, the objective is to identify which information is necessary to analyse how the inclusion/exclusion from education is connected to the inclusion/exclusion from employment.
The interview results confirmed our suggestions for additional indicators or data in the field of employment.
In our research we analyse the connection between educational exclusion/inclusion and social exclusion/inclusion with special emphasis on people of some vulnerable groups: women, migrants, cultural groups, youth and people with disabilities. Some of this data allows analysing whether there are differences by gender and by age, and other data does not provide this information. We as well as our interviewees think that this is relevant information that should be available. As the person excluded from employment mentioned we need this information, because it is harder for women to get the job than for men and it is especially hard to find a job for people after 50.
Early tracking is viewed by many authors and previous results of the Included project as a negative practice in educational system which leads to social exclusion. The authors emphasize that early tracking which is based on the division of students according to academic abilities is viewed as a negative practice, which prevents inclusion into higher education and university, which decreases opportunities for achieving employment and better quality and highly paid jobs. Such tracking system creates prejudices and low expectations for some vulnerable groups, like people with disabilities and contributes to their social exclusion. The Included project has already collected some data on tracking. It would be important to have the data on the countries and educational systems that practice early tracking and its different forms. The person excluded from education told us that we need to collect the data on early tracking and endeavour to abolish it, because as she gave the example of Germany they found out that pupils were in reality not divided according to their abilities but according to the social status of their parents (EIEF1). She also gave the example of Slovenia where the students of elite grammar schools mostly have highly educated parents. The same person also thinks that in
education we have to endeavour for equal opportunities and abolish early tracking, so that pupils and students from social margin can develop and get their opportunities (EIEF1). The representative of the trade union stated that it is important that children learn to accept diversity in the classroom, therefore tracking system needs to be abolished (NIEM3).
The situation is similar with streaming systems. According to the Included project streaming is a negative practice that leads to social exclusion. We think that we need to gather the data on such streaming practices in EU. The Included project gathered some of this data. The person excluded from employment thinks that we need to describe and analyse the streaming systems in EU countries in order to see their strengths and weaknesses so that situation can be improved (EIEF1). The policy maker in the area of employment stated that she is against streaming which is still practiced in Slovenia, because it lowers self-esteem and motivation of some pupils. She thinks that if children are in mixed ability groups they learn solidarity, because they help each other. According to her opinion our societies are too competitive and this is what children learn already at school. The same person thinks that we should develop talents in every pupil and not to categorize them into groups according to the so called different abilities (PIEF2).
It would also be important to have the data on school dropouts, namely school dropping out is the next obstacle to employment, because school dropouts have limited employment opportunities (Miller & Porter, 2007; Gilbert, 1993, in Crea, 2008), they are unemployed for longer periods (Hartley, 1989, in Crea, 2008) and they are unemployed more times through their life. However, the current situation is that not all European countries collect the data on school dropouts, but it would be important for each country to collect them and to enable comparison with other countries. Namely, as den Boer et al. (2006) write the ambition of EU is according to Lisbon goals to become the most competitive knowledge based society and to achieve this goal, the EU states have among other things to reduce the EU average of early school leaving (the percentage of 18-24- year- olds with no more than a lower secondary education (ISCED-2) who are not completing any further education and training. In 2000, the average was 17.2% and in 2004, 15.9%.The goal is for this age group to reach 10% in the year 2010. However, den Boer et al. (2006) write that work towards this goal is only slowly progressing. The policy maker from the area of employment thinks we need the exact data on dropouts, because »we cannot afford to lose them«, we have to help them with counselling and help them to get at least national professional qualifications (PIEF2). Slovenia has excellent educational programme for dropouts - PLYA. PLYA is an abbreviation for SIAE's
educational programme Project Learning for Young Adults, which was awarded in 2007 with the European Regional Champions Award by the Committee of the Regions in cooperation with the magazine The Parliament Regional Review - Shortlist Brochure, in order to highlight and celebrate the best ideas, innovations and cases of good practices of social policy in the European Union regions. The project is especially designed for dropouts to enhance social and educational inclusion. Despite the fact that the PLYA programme is considered successful, it is constantly underfunded and it does not include all the dropouts in Slovenia.
Data from Eurostat on Youth transitions from education to working life in
Europe/ LFS 2000 (2000) are gathered only for four European countries (Austria, Belgium, Spain and Romania) and thus it is difficult to identify a general trend, therefore we would need the data for EU 27 in order to identify a trend.
The same is true for the data on the proportion in precarious employment by educational level which is available only for 6 countries (Austria, Spain, France, Italy, the Netherlands and Romania) and thus we cannot identify a clear trend as far as the impact education has on the rates of precarious employment for young people. We would need this data for EU 27. The person excluded from employment is of the opinion that some governments might not be interested in gathering this data, because they want to hide that they did not do enough for the employment of youth (EIEF1).
As it is evident from the number of indicators that Crea analysed from the European databases, there are plenty of them that connect employment to education, however, they usually do not include vulnerable groups (as, for example, migrants, persons with disabilities and ethnic groups (e.g. Roma). We need that indicators which connect education and employment would include the aforementioned vulnerable groups, because the members of these groups are often socially excluded, they have difficulties finding employment and their access to employment and education is often limited. As the person excluded from employment told us we need to collect this data, but she said we have to find an appropriate way to collect it:
"Yes, it would be important to gather this data, but I wonder what would be an appropriate way to collect this data, I do not know what would be acceptable to ask the individuals, because of the protection of personal data. If we deal with the collected data in an ethical way it is sensible to collect it, especially due to the fact that we need to have this data so that it becomes evident from the statistics whether they are depriveleged and that they belong to the margin of a society and then non-governmental organisations or someone else would be able to demand the change of public policies, (s)he would achieve that with this data. Unless we have the data, unless we can prove with statistical analysis or scientific research that they belong to the margin of society and that they are depriveleged, this is damaging for them" (EIEF1).
This person excluded from employment remarked that maybe it is not in the interest of ruling elites to have such data on marginal groups gathered, maybe they do not want that marginal groups take a central position in a society, because then they would compete for the jobs with them and their children. She thinks that maybe the ruling elites do not want that such data are collected maybe also due to the fact that then it would be seen that they did not rule well, because there were so many socially excluded people (EIEF1).
The policy maker in the area of employment is of the opinion that if we can not include the data on the aforementioned vulnerable groups in the statistical databases, because it is, for example, difficult to access them, then we need special research that will focus on them (PIEF2). The representative of the trade union in the educational sector emphasized that there are no members of vulnerable groups in Slovenia among teachers. If there are Roma teachers, they are only in schools with a lot of Roma, but not in schools where there is low percentage of Roma. The problem is also in the fact that teachers have to have undergraduate education, but Roma with such education are rare (NIEM3).
We enumerated the interviewees the aforementioned results on the connection of education and employment previously researched in the scope of the Included project and requested the interviewees if according to their opinion there are some other aspects to be analysed. The person excluded from employment told us that it should be researched how all which is characteristic for lower and higher educated is later on transferred to future generations. She thinks that it is so in most of the cases, so very
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often the children of low educated get low paid and more unsecure jobs as well. She also thinks that we should research the situations of pregnant women in Slovenia who do not get jobs, because their employers discriminate them. She thinks that education is important because it equips people with skills and competences and if one does not have the competence to learn how to learn one does not know how to search for information, one is not even aware of his/her needs and capacities. She compares this situation of low educated to the caste system where one is limited in advance (EIEF1). The same interviewee also thinks we need to gather the data on non-formal learning and about the possibilities for non-formal learning (EIEF1). The person excluded from employment thinks that when we gather the data on educational level attained, it would be sometimes interesting to gather the data also on the educational level of their parents, because the education of their parents has a strong influence on the education of their children. The policy maker from the area of employment thinks we need to research and encourage the cooperation between the state (policy makers) and social partners who should endeavour together to develop policies which would enable training of low educated and to develop educational programmes which are not classroom based. She also thinks that it is a pity that Slovenia did not decide to do PIAAC research (Programme for International Assessment of Adult Competencies), because the results of this research would show us exactly what educational programmes and training to design (PIEF2). The representative of the trade union thinks that we need the research on violence in schools toward teachers which is on the increase (NIEM3).
The person excluded from employment also thinks that low educated have ICT competence less developed and therefore they have more difficulties in finding a job and writing their CV. This holds true also for migrants who do not know the language of the receiving society and are therefore more prone to be excluded from employment. Education gives you the knowledge with which you get included in employment more easily. Another fact is that the longer you get educated, the stronger your social network and then you again have more chances to get employed (EIEF1). The policy maker in the area of employment stated that very often low educated are not aware of the importance of lifelong learning, therefore they are even more often excluded from employment. Sometimes they refuse training and prefer to depend on social benefits instead of accepting retraining for another job and become employed (PIEF2). The trade union representative said that it is a good thing in educational sector in Slovenia that also those with low education get unlimited contracts as for example cooks, cleaning ladies and janitors, but the situation in other sectors is less favourable for low educated (NIEM3).
The experience of being excluded from employment
The policy maker from the area of employment thinks that those who are especially excluded from employment in Slovenia are dropouts, the other group are those who have professions which are in excess supply. Such professions are in Slovenia in social sciences and humanities, in administration etc. Those people the professions of whom are not competitive in the labour market face problems as well, such as sewers, for example. The problem is that no one trains the latter for another job (PIEF2).
The person whom we interviewed was unemployed when we agreed on the date of the interview. However, after a couple of days she was offered a job, which she decided to take. We still performed the interview with her because she had had her experience of unemployment.
She explained her experience of unemployment: "Yes, I was unemployed. The problem that appears is when you finish your studies, when you perform all the duties and suddenly you remain in an empty space, you have to get on somehow. You have more time, however, you do not know or you cannot use it for earning money. You wish to work, but you cannot find the employment. You have the capital but you cannot use it. You cannot come into contact with employers, however, I understand them, they have a lot of job applications...I think what is most important is to stay in the contact with your profession and social network, that you are mobile in a society and do also occasional works such as translations, proof-reading, collecting articles on everything which is connected to your profession that you get certain knowledge, what is also important is to get some money for everyday life... Even if you help someone mind the baby or you translate and you are not paid, only to get connections, experience and this helps you. ...You have to be proactive and everything is possible" (EIEF1).
5. Health
5.1 Indicators on health analysed
Educational attainment and health care
■	Consultation of a medical doctor during the past 12 months, by sex, age and highest level of education attained (EUROSTAT)
■	Consultation of a dentist during the past 12 months, by sex, age and highest level of education attained (EUROSTAT)
■	Breast cancer screening by age and highest level of education attained (EUROSTAT)
■	Cervical cancer screening by age and highest level of education attained (EUROSTAT)
Educational attainment, health problems, illness, injuries and restrictions
■	In-patient hospitalisation during the past 12 months by sex, age and highest level of education attained (EUROSTAT)
■	Day-patient hospitalisation during the past 12 months by sex, age and highest level of education attained (EUROSTAT)
■	People having a long-standing illness or health problem, by sex, age and highest level of education attained (EUROSTAT)
■	Activity restriction in the past 6 months by sex, age and highest level of education attained (EUROSTAT)
■	Cutdown in activities over the past 2 weeks because of health problems, by sex, age and highest level of education attained (EUROSTAT)
■	Relative standardized incidence rate of accidental injuries at work by educational attainment level and sex (EUROSTAT)
■	Hampered in daily activities by illness, disability, infirmary or mental problem (European Social Survey)
Educational attainment and less favourable health behaviour
■	Body mass index (BMI) by sex, age and highest level of education attained (EUROSTAT)
■	Smokers by number of cigarettes by sex, age and highest level of education attained (EUROSTAT)
■	Smokers by sex, age and highest level of education attained (EUROSTAT)
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■	Previous smoking behaviour of non-smokers by sex, age and highest level of education attained (EUROSTAT)
■	Consumption of alcohol (percentage of people who drunk any alcohol the last 12 months) by sex, age and highest level of education attained (EUROSTAT)
Educational attainment and subjective health
■	Self-perceived health by sex, age and highest level of education attained (EUROSTAT)
■	Subjective general health (European Social Survey)
5.2 The results of previous research on education and health
The literature review showed that education effects health (Ross and Wu, 1995; Cutler and Lleras-Muney, 2006; WoBman and Schutz, 2006 etc.). The lack of education can be seriously detrimental to health. People with lower levels of education die younger and live more years with disability than people with higher levels of education (Ivancic, Mirceva, Vrecer, 2008). Each additional year of schooling reduces mortality rates by 8% (Elo and Preston, in Deaton, 2003). In order to postpone mortality and disability we must prevent health problems and disabilities from an early age. The literature review showed that gender is important factor in terms of health. In EU countries women live longer than men but not as healthy as men. Low educated single mothers, teenage pregnant women, unemployed and migrant women are at particular risk. Education is an important mechanism for improving women's social and economic status. Namely, it is evident from the literature that socioeconomic status influences health as well, education being its main indicator, because it affects the other indicators: occupation and income. It is evident from the literature that people with low economic status have shorter life expectancy than people with higher economic status. Thus poverty affects mortality and disability as well, it is the cause and consequence of disability (DFID, 2000). Disabilities often limit access to education and employment, people with disabilities are least likely to be employed, they are often excluded from education, thus they are often socially excluded as well and their life expectancy is lower than that of people without disabilities who find employment more easily and have more
access to education. Education is the only way out of vicious circle of poverty and disability, which cause social exclusion (Ivancic, Mirceva, Vrecer, 2009).
The data on the influence of socio-economic on health are relevant also for the migrants. Namely, the latter are often poor and in worse health, they have difficult job conditions, besides, downward mobility is characteristic for them (Rammel, 2008). The same author describes the situation of Roma in EU, which is not good - they live in shanty-towns and have difficult access to health care. As an example of best-practice she mentions migrants' friendly hospitals initiative on EU level which aims at strengthening the role of hospitals as regards the health and health literacy of migrants. The project aims at creating migrant and minority-friendly hospital setting (Bischoff, 2006 in Rammel, 2008). Rammell (2008) thinks that policies aimed at transforming social exclusion in education and health regarding migrants are connected to welfare policies that fight poverty and social exclusion.
The findings of the secondary analysis of European databases confirm the results of the literature review that the education affects health problems, illnesses and injuries. Hager (2009) found out that the respondents with lower educational levels attained tend to have in-patient hospitalisations more often than people with higher educational attainment. The data also indicates that women tend to have more in-patient hospitalisations then men. At the same time the respondents with lower educational levels attained tend to have long-standing illnesses or health problems more often than the respondents with higher educational level attained. Low educated are more prone to risk behaviour, namely, the respondents with low education smoke more cigarettes per day (20 or more) than people with higher educational level attained. Men tend to smoke more than women. Besides, people with lower educational levels attained tend to perceive their own health as bad more often than people with higher educational levels attained (Hager, 2009).
5. 3 The identification of gaps in databases pertaining to education and health in a dialogic discussion of end-users and social agents
The objective of these interviews is to analyse the educational exclusion and inclusion and its connection to social inclusion and exclusion from health. Specifically, the objective is to identify which information is necessary to analyse how the inclusion/exclusion from education is connected to the inclusion/exclusion from health.
The interview results confirmed our suggestions for additional indicators or data in the field of health.
In the literature it was found out that there is a general trend in EU countries of reduced mortality (Cavelaars et al., in Ivancic, Mirceva, Vrecer, 2008). However, many studies throughout Europe have reported a higher level of morbidity and mortality of people with a lower educational level (Elo and Preston in Deaton, 2003). There is a lack of data in the European databases regarding the mortality rate by age, sex and educational attainment. Namely, this data is collected on the national basis mainly by some countries, but we would need the data on the European level in order to follow the European trends and to enable comparisons. The member of NGO dealing with health issues who herself is a cancer survivor said we need such data in order to endeavour for healthy ageing (NIHeF3).
The aforementioned indicators pertaining to education and health do not take all vulnerable groups into account. It would be a good idea to develop those indicators which would include vulnerable groups (as, for example, migrants, cultural groups such as Roma and Sinty and persons with disabilities).
The data on Pregnancies by age and educational attainment are not available for all EU countries, but we would need them for EU-27 in order to see the trend. Namely, it was found out in the literature review (Ivancic, Mirceva, Vrecer, 2008) that low educated mothers are pregnant younger than more educated ones. And group at particular risk regarding health are women who are young mothers having low level of education (Goran, Whitehead, in Ivancic, Mirceva, Vrecer, 2008). Besides, the probability of teenage motherhood and the probability of giving birth outside of wedlock are decreasing with the educational level of mothers (WoBman and Schutz, 2006).
For the USA and some countries there exists the Indicator Subjective life expectancy by age, sex and highest educational level attained. This is connected to the question until which year do you expect to live. We would need this indicator to be available for EU-27 in order to enable comparison and to see the trend.
The indicator Accidental injuries at work is available for 12 EU countries only. We think we need this data available for other countries of EU-27 as well. The person excluded from health said that we need more qualitative health and safety at work, because we have so many work accidents in Slovenia, especially among construction workers who are usually migrants. She thinks that companies which do not perform high-quality health and safety at work should be sanctioned (EIHeF1).
The indicators Self-perceived health, People having a long-standing illness or health problem and Activity restriction are available for EU-25, Iceland and Norway. Since Romania and Bulgaria are part of EU too, we think we need these indicators to be available for these two countries as well.
The indicators Subjective general health and Hampered in daily activities by illness, disability, infirmary or mental problem are available for 24 EU countries. We need this data to be available for EU-27.
The indicators for in-patient hospitalisations during the past 12 months by sex, age and highest level of education attained and day-patient hospitalisation during the past 12 months by sex, age and highest level of education attained are available only for some EU countries. We need them for the rest of the EU-27 countries as well in order to identify a trend in European Union.
The indicator Accidental injuries at work allows us to see the differences between men and women, however, the data for different age groups were not available. We need this data also for different age groups.
We enumerated the interviewees previous results of the Included project and asked them if they think there are some other aspects to be analysed. The policy maker from the field of health suggested that the problem is where it is optional for people to provide, for example, the highest educational level attained, but people do not write it and then sometimes the analysis shows that the data is not good. She said that we need complete data to achieve good results (PIHeF2). The policy maker from the field of health also stated that they usually only get data from the current illness due to which one seeks medical help and not the data on other chronical illnesses or disabilities or membership to the vulnerable group and then it is hard to get a whole picture from the statistics, because you do not have enough data available. But the problem is in what way to collect that data which analysts would need (PIHeF2). The member of NGO dealing with health stated that we need to research whether non-formal education on health prevention is sufficient in each specific EU state (NIHeF3). She thinks it is important that people who overcame illnesses teach others how to overcome them.
The policy maker from the field of health and NGO member said that the problem of low educated is that they do not recognize the need for health prevention. At the National Public Health Institute they have the centre for promotion, where they try to educate different vulnerable groups regarding health. According to their experience it is more difficult to motivate low educated people than those with higher educational levels attained. The member of NGO dealing with health noticed that people with lower education are inclined to view their illness as a destiny on which they have no influence, while people with higher education are more inclined to fight the illness with a change of life-style and so on (NIHeF3).
The experience of the exclusion from health
The policy maker in the field of health stated that in Slovenia youth are especially vulnerable as regards health. This is due to the fact that they cannot take care for themselves and are dependent on others. Another vulnerable group are women and also Roma, unemployed, less educated and migrants who do not speak the language of the receiving country and do not understand the instructions for safe work (PIHeF2).
The person whom we interviewed as the one excluded from health does not have health insurance. However, in Slovenia basic medical insurance is free of charge, for additional insurance we have to pay additionally. In order to get basic medical insurance free of charge, one has to fill in the application form and submit it in the town where one has
24
permanent residency and then the municipality pays for the basic insurance. Our interviewee has not filled in and submitted the application yet, therefore, she is without health insurance. She said that low educated should have more training on health issues as they are not informed enough. Another problem that she mentioned is that one cannot find information in one place, because they are in different places. The problem is also that homeless face digital exclusion and as a consequence they have even less information (EIHeF1).
She explains her experience of being excluded from health: " Yes, of course, this is my personal problem, because I have to collect so many documents and to write something. It is my fault...I have to go to another town Polhovgradec to submit the application. I will do it one day, I have not managed to do it up to know, something always happens and I do not have the time. Every day there are so many things to be done, it is a nut house... Up to now I mainly had toothaches. One Friday afternoon I went to Metelkova Health Centre...and told them that I do not have basic health insurance and if they can do something to calm down my tooth. She did it and wrote on a piece of paper what she did and she said to me to file the application for health insurance as soon as possible, but I am still without it...This is my fault, we can say I am lazy, I procrastinate..." (EIHeF1).
She also mentioned that homeless people in Slovenia do not have many rights and thus they are also without home care if they are sick. They have to stay under the blue sky, if they are sick, she said. She also called attention to the fact that social security in Slovenia (approximately 230 EUR) is not sufficient to hire a room or a flat and that is a big problem (EIHeF1).
6. Housing
6.1 Indicators on housing analysed
■	Household characteristics by employment (EUROSTAT)
■	Household by educational level of the head of the household (EUROSTAT)
■	Jobless households (EUROSTAT)
■	Number of people in household (World Values Survey)
■	Do you live with your parents + age (World Values Survey)
■	House or apartment (World Values Survey)
■	Do you own your home or rent it (World Values Survey)
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■	Number of people living regularly as member of household (European Social Survey)
■	Lives with husband/wife/partner, etc. (European Social Survey)
■	Feeling about household's income nowadays (European Social Survey)
6.2 The results of previous research on education and housing
The right to adequate housing is a basic human right, it is laid down in many basic international human rights documents, such as, for example, The Universal Declaration of Human Rights (1948), Article 25(1), the International Covenant on Economic, Social and Cultural rights (1967) Article 11(1) and the Convention on the Elimination of all Forms of Racial Discrimination (1969), Article 5 (e)(iii) and other documents. The literature review revealed that adequate housing is one of the most important aspect of social inclusion. Low educated usually have worse housing conditions (Campani, Salimbeni, Chiappelli, 2008). Education is a significant element that influences the access to better housing conditions. However, literature review shows that the two variables, education and housing are not connected in a linear way but through the variable poverty (Mircea and Dorobantu, 2008). The same authors state that access to education is not so much conditioned by their housing conditions but more by their socio-economic status and linguistic skills. Campani, Salimbeni, Chiappelli (2008) found out that placement and housing stability contribute to better educational and employment outcomes of youth in transition to adulthood. Programmes based on housing policies aiming at social integration should strengthen the inclusion in social networks of family, kin and friends. It is important that subsidized housing is available for the homeless families with the services available such as drop-in centres. It is also important that integrated services are provided, where treatment is combined with residential care programmes. For the most vulnerable groups policies aimed at social inclusion must take into account their needs in terms of housing. Mixed housing policies are recommended, which prevent segregation of the poorest in the same neighbourhood. Social housing should be provided for young adults with disabilities (Campani, Salimbeni, Chiappelli, 2008). Mircea and Dorobantu (2008) found out that poor housing conditions affect educational achievements of migrant children, namely stable and affordable housing may provide children with enhanced opportunities for educational success. The attention of those authors was called to the fact that in some urban areas migrants live in ghettos and are highly represented in certain schools, it is evident from that that housing policies have a powerful effect on school recruitment.
It was found out in the working paper of Campani, Salimbeni, Chiappelli (2009) that only a few statistics link a person's educational level and housing condition, therefore we give in the following chapter some suggestion which statistics should link a person's educational level with housing condition.
6.3 The identification of gaps in databases pertaining to education and housing in a dialogic discussion of end-users and social agents
The objective of these interviews is to analyse the educational exclusion and inclusion and its connection to social inclusion and exclusion from housing. Specifically, the objective is to identify which information is necessary to analyse how the inclusion/exclusion from education is connected to the inclusion/exclusion from housing.
The interview results confirmed our suggestions for additional indicators or data in the field of housing. However, a university professor who deals with housing issues called attention to the fact that we should also make better use of existing databases (NIHOF3).
As revealed by Campani, Salimbeni and Chiappelli (2009) most of the literature review examined in WP 10 was focused on urban areas connected to educational achievement especially regarding poor areas and ghettos. However, in the statistical databases these variables are not taken into consideration.
The above mentioned indicators are not connected to education (except one: Household by educational level of the head of the household Eurostat), however, it would be useful that they were connected to education. Besides, those indicators do not include vulnerable groups as, for example, youth, women, migrants, ethnic groups and people with disabilities. We would need such data in order to assess the level of exclusion of vulnerable groups from housing in comparison with the rest of the population. We would also need data that it will allow us analysing whether there are differences by age and gender. The policy maker from the field of housing stated that we especially need the data which will allow us analysing differences by age, because elderly people need different flats. Those flats which have many floors and no elevator or other adaptations are especially problematic. She claims it would be important to know who the owners are and who the tenants according to their age are in order to plan future policies (PIHoF2).
The following indicators also exist in the databases, however, they are not connected to education, but it would be useful if they were connected to education as well. These
27
indicators are: Burden of the housing costs by tenure status and socio-economic status (Eurobarometer), Burden of the housing costs by type of household and income group (Eurobarometer), Households living in overcrowded conditions by type of household and income group (Eurobarometer), and the following indicators from Eurostat: Material deprivation for the dimension "housing", Expenditure - Tables by benefits and currency -housing function, Housing expenditure in percentage of total expenditure by type of household and tenure status, Number of private households, Persons living in private households, Total number of lone parent households, Lone parent households as a percentage of all households with dependent children, In-work at risk of poverty rates by household type, In-work at risk of poverty rates by work intensity of the household, Distribution of population by work intensity of the household, Average household size, Mean and median income by household type, At-risk-of-poverty rate, by work intensity of the household, At-risk-of-poverty rate, by accommodation tenure status and by gender and selected age, At-risk-of-poverty rate, by household type, Mean consumption expenditure by household and per adult equivalent.
We would also need the data on number of people living in social housing by age, sex and highest educational level attained since social housing contributes a lot to more equal access to housing, especially for the members of vulnerable groups with low income. Here it would first be very important to define what social housing is.
We think that we need to collect data on the number of homeless people in EU countries so that we can help them in a more efficient way.
According to the literature review low income and poverty are very common among single mothers, they also face a disproportionate loss of disposable income through housing expenditures (Campani, Salimbeni, Chiappelli, 2008), therefore we need to gather data on lone parents by household type and highest education attained.
European Union states are facing demographic changes, the number of active population is decreasing, therefore we would need higher fertility rates. A study by Kulu and Vikat, 2007 in Ojala, Kaalikoski, 2008) suggests that housing type has a great effect on fertility (more than the education level of a husband or wife). The authors found out that in Finland fertility is highest among people living in single-family houses and lowest among those residing in apartments. We think it would be important to gather data on fertility differences by housing type and highest educational level achieved also for other countries.
Poverty is very often characteristic for people with disabilities. They often lack financial means to live independently, because they cannot afford to pay for housing. We think that we need data on people with disabilities and household type and highest education attained.
Migrants and some cultural groups (as, for example, Roma) very often live in bad housing conditions. We need to gather data on migrants and cultural groups by household type and highest level of education attained in order to encourage policies that would improve their housing conditions. The policy maker from the field of employment is of the opinion that migrants lived in better conditions in socialism, nowadays, in capitalism they are very often exploited and live in bad conditions. She said that states probably do not want the data on their bad housing conditions (PIHoF2). The university professor who deals with housing issues stated that migrants are in Slovenia especially discriminated from housing, because the Slovene citizenship is a pre-condition for acquiring non-profit flat and many migrants do not have it, because the pre-condition for acquiring it is ten years of permanent residency in Slovenia. Those who have the citizenship of other EU countries can get social flats more easily. She also mentioned that in Slovenia many other Slovene people who do not belong to vulnerable groups live in bad housing conditions (NIHoF3).
We enumerated the interviewees the main results of the literature review and asked them whether there are some other aspects to be analysed. The policy maker stated that we need more data on women who are the victims of violence according to their educational level attained. The problem in Slovenia is that the victim of violence is very often the victim of homelessness, although the law clearly states that a violent person has to move out of the flat. The problem is because a violent man has nowhere to live and thus he stays in the flat and endangers his wife and children. The policy maker also states we need the statistics on private lease (PIHoF2). The university professor dealing with housing mentioned that it is not enough if we gather statistics on how much the persons in a household earn, because we cannot rely solely on the data on current salary, the situation is completely different if a person has been unemployed for the last twenty years (NIHoF3). She also stated that we do not need to collect all statistical data each year, it is enough if we do it every couple of years, so that we see the trend. Her opinion is also that we sometimes have some data, but the problem is often that statistical reports are not published regularly, she misses regular reporting.
The answers to the question whether low levels of education have other consequences in housing than those revealed by the above-mentioned literature review were the following: The person excluded from housing said that those homeless who have lower education are even more excluded from social networks, they are lonelier than those with higher education (EIHoM1). Interviewees also stated that in Slovenia we find people from all levels of education among the homeless, however, those with lower levels of education prevail. The university professor who deals with housing issues confirmed the results from the literature review that low educated people usually have lower salaries which enhances exclusion from housing (NIHoF3).
The experience of being excluded from housing
The interviewee who has experience of being homeless explained that being excluded from housing is often connected to other problems such as drugs and alcohol. He stated:
"If you want to stop drinking, it is not enough that you stop drinking, if you want to cease to be homeless, it is not enough that you get a flat, you have to learn how to function, to learn ethics and how to organize your life. I have come half way, more is difficult, because the society does not allow more...When you are on the street, this drains all your energy and strength... Only that how you live to the further moment, this takes all your strength" (EIHoMl).
7. Political participation
7.1. Indicators on political participation analysed
Educational attainment, political participation and political action
Voting
■	Voted in recent parliament elections by highest education level attained, sex, age and ethnic minorities; World and European Values Survey
■	Voted in last national elections (vote) by highest education level attained, sex, age and ethnic minorities; European Social Survey
Involvement in political groups and parties
■	Belong to local political action by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Close to any political party by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Feel closer to a particular party than all other parties by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Belongs to political party by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Active/inactive membership of political part by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Unpaid work political parties and groups by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Unpaid work local political parties and action groups by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Worked in political party or action group last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Political party, last 12 months member by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Political party, last 12 months participated by highest education level attained, sex, age and ethnic minorities; European Social Survey
Involvement in various non-governmental organizations
■	Could take an active role in a group involved with political issues by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Worked in another organization or association last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Belongs to labour union by highest education level attained, sex (x001), age and ethnic minorities; World and European Value Survey
■	Trade Union, last 12 months member by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Trade Union, last 12 months participated by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Active/inactive membership of labour union by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Unpaid work labour union by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Belong to human rights group by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Unpaid work human rights group by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Belongs to women's group by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Unpaid work women's group by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Belongs to peace movement by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Unpaid work peace movement by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
Symbolic action
■	Contacted politicians or government officials last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Political action: signing a petition by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Signed petition last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Political action: joining in boycotts by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Boycotted certain products last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Political action: attending peaceful demonstrations by highest education level attained, sex, age and ethnic minorities; World and European Values Survey
■	Political action: attending lawful demonstration by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Taken part in the lawful public demonstrations last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Worn or displayed campaign sticker last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Political action: joining unofficial strikes by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Participated illegal protest activities last 12 months by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Political action: occupying buildings or factories by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Political action: damaging things, breaking windows, street violence by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
Educational attainment, political participation: information, awareness,
discussion
Information and awareness
■	How often follows politics in the news by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Interest in politics by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Making mind about political issues by highest education level attained, sex, age and ethnic minorities; European Social Survey
Daily discussions about politics
■	Discuss politics, current affairs, how often by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	How often discusses political matters with friends by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Sharing with partner political view by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Sharing with parents political view by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
Educational attainment, political participation: attitude and values
Politics and democracy
■	Politics too complicated to understand by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Politics important in life by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Importance of democracy by highest education level attained, sex, age and ethnic minorities; World and European Values Survey
■	Having a democratic political system by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Using violence for political goals not justified by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Respect for individual human rights by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
Satisfaction with democracy
■	Satisfaction with democracy in a country by terminal education age, sex and age; Eurobarometer
■	Satisfaction with democracy in the EU by terminal education age, sex and age; Eurobarometer
Trust and confidence to the institutions
■	Trust in a country's parliament by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Confidence to a Government by highest education level attained, age and ethnic minorities; World and European Value Survey
■	Confidence to a Parliament by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Confidence to Political parties by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Confidence to the Local/Regional government by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Trust in politicians by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Trust in European Parliament by highest education level attained, sex, age and ethnic minorities; European Social Survey
■	Confidence in the EU by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
■	Confidence in the Labour Union by highest education level attained, sex, age and ethnic minorities; World and European Value Survey
7.2 The results of previous research on education and political participation
According to the Commission of the European Communities (2006) education particularly influences the processes of democratisation, the development of civic institutions, human rights and political stability. The literature review showed that educational attainment is related to active citizenship
(voting, being aware and following politics, participating in politics or volunteering in community service) (Ojala, Kaalikoski, 2008). The probability of voting is 8.5 higher for people with higher education in comparison with people with primary school (Hoskins et al., in Ojala; Kaalikoski, 2008). The authors agree that high school civic knowledge and extracurricular activities are predictive of voting and volunteering, thus schools are important places for citizenship education, which is a preparation for active citizenship. Ojala, Kaalikoski (2008) write that vulnerable groups are often absent from democratic dialogues, therefore their political engagement needs to be improved.
Some authors write that migrants are politically active regardless of their education and the level of literacy, however, this holds true only for their participation in NGOs. As regards participation in voting, this participation of migrants is very often limited due to their legal status, namely, very often they cannot vote, because they do not have citizenship of a receiving state (Atger, 2008). Oldman (in Atger, 2008) writes that the political participation of migrants is influenced by their length of stay in the receiving country, the reasons of why they came abroad, their political ideas and values, their knowledge of a political system of a receiving country, their identification with the receiving country and the structure of political opportunities in a receiving society. Castles (in Atger, 2008) says that nowadays most migrants lack opportunities for political participation. This especially holds true for undocumented migrants who lack the opportunities for political participation to a large extent , because they do not have a legal status.
The analysis of secondary data provided by European Social Survey, Eurobarometer and World and European Value Survey confirmed the results of the literature review that there is a tendency that formal education, in particular tertiary education, has a positive impact on active citizenship (Ojala, Kaalikoski, 2008). The members of vulnerable group with very low educational attainment show to be less active to take part in political activities. The analysis of the statistical data showed that people with lower education do not value politics as very important aspect of their life as much as people with higher education do: only 5.9% of people who completed elementary education value politics as important and 12.15% of people with higher education value it as important aspect of their life (BISS, 2009). The same institution also found out that women with lower education show the least interest in politics.
7.3 The identification of gaps in the area of political participation in a dialogic discussion of end-users and social agents
The objective of these interviews is to analyse the educational exclusion and inclusion and its connection to social inclusion and exclusion from political participation. Specifically, the objective is to identify which information is necessary to analyse how the inclusion/exclusion from education is connected to the inclusion/exclusion from political participation.
The interview results confirmed our suggestions for additional indicators or data in the field of political participation.
As it is evident from the above indicators regarding education and political participation, they are numerous. While we can find indicators including different vulnerable groups such as youth, women, migrants, and sometimes even ethnic minorities, there are no indicators pertaining to education and political participation which include people with disabilities. However, it is often the case that people with disabilities are excluded from political participation, therefore we need indicators on education and political participation which would include people with disabilities. It was found out in the literature review (Ojala, Kaalikoski, 2008) that people with disabilities have lower levels
of political participation including being involved in community life, attending meetings and voting. Besides, it was found out in the same report that the civic knowledge of people with disabilities is weaker because they are usually less educated. However, beside the lack of indicators on the relation between education and political participation of people with disabilities, even research on the aforementioned topic is scarce (Ojala, Kaalikoski, 2008). The person who has the experience of exclusion from political participation stated that people with disabilities are even more depriveleged as regards political participation than people with lower education. He thinks they are completely marginalized and out of politics, they do not have a representative in the parliament in Slovenia (EIPM1). The member of parliament said we should pay attention whether technical barriers are removed for the persons with disabilities to vote, if the access to the polling station is available for them (PIPF2).
It would also be interesting to have the data on the relation between education and political participation for some cultural groups, especially for Roma. The
person who had been for many years excluded from political participation noted that Roma people do not have a representative in the Slovene parliament (EIPM1). He said that the same holds true for the members of ex-Yugoslav nations in Slovenia who still do not have a status of a minority and consequently no representative in the parliament. Only two official ethnic minorities Italians and Hungarians, which are far less numerous than the members of ex-Yugoslav nations, have each a representative in the parliament. He claims that if ethnic minorities and other vulnerable groups do not have a representative in the parliament, they are not motivated to vote (EIPM1). The member of NGO dealing with political participation agrees that we need the data on the relation between education and political participation of Roma, because approximately 80% of asylum seekers in Slovenia are low educated Roma from Bosnia-Herzegovina and Kosovo who are excluded from political participation (NIPM3).
The following indicators do not include ethnic minorities, however, it would be useful if they included ethnic minorities:
Satisfaction with democracy in a country by terminal education age, sex and age; Eurobarometer
Satisfaction with democracy in the EU by terminal education age, sex and age; Eurobarometer.
However, the member of parliament stated that according to the Slovene constitution people are not obliged to declare their nationality and it is difficult to gather such data (PIPF2).
The indicators in European Social Survey are available for EU-19 countries. We think it would be important that they were available for all EU countries in order to see a trend. The person with the experience of exclusion from political participation said it is important that we have the data for all EU countries, he thinks Slovenia is not truly democratic state yet and needs to be compared to other states (EIPM1).
We enumerated our interviewees the above-mentioned results of the literature review and statistical analysis and asked them if there are any other aspects to be analysed. Among the answers there are the following: The person who was for many years excluded from political participation as the member of the so called "erased people" of Slovenia which will be explained later on considers that we need to research the participation of vulnerable groups in NGOs, he says it is important that the members of vulnerable groups such as migrants, asylum seekers, Roma and women join in NGOs and advocate their rights (EIPM1). The member of parliament stated that we need to research those educational programmes that contribute to social inclusion but which maybe are not so interesting for the market (PIPF2). The member of NGO dealing with political participation stated that we need to research whether the status of employment (whether the contract is unlimited or limited) influences political participation. According to him those who have unlimited contracts feel more secure and more active in political participation. The same holds true with those with permanent residency in comparison with those with temporary residency (NIPM3).
The answers to the question whether low levels of education have other consequences in political participation than those revealed by the above-mentioned literature review were the following:
"Education has a strong influence on political participation. Those who have higher education are more successful, especially in politics than people with lower education" (EIPM1).
The member of the Slovene parliament who is very active regarding political participation stated that low educated if a part of the civil society sometimes do not articulate their demands that good as those who have higher education. She gave the example of civil society dealing with the rights of homosexuals in Slovenia, the members of which have usually tertiary education and who act very proactively and advocate their rights very
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well. According to her opinion low educated very often do not act proactively enough, if they join civil society initiatives, they usually just oppose some idea (PIPF2). The member of NGO dealing with political participation stated that when low educated get included as the members of civil society, there are certain advantages if they participate from their experience, however, they tend to oversimplify matters and are more prone to manipulations than those with higher educational levels attained (NIPM3).
The experience of being excluded from political participation
The member of parliament stated that people who are to a large extent excluded from political participation are asylum seekers, new ethnic minorities (members of ex-Yugoslav nations), poor people, illiterate people and other low educated people, those who do not speak the Slovenian language and the so called "erased" people (PIPF2). The member of NGO added to that that homeless people who have no permanent residency are excluded from political participation as well as labour migrants with temporary residence (NIPM3).
The person who has been excluded from political participation for many years is a member of the "erased" people in Slovenia. Those are approximately 25,700 people who were on the 26th of February, 1992 erased without notice from the registry of permanent inhabitants, therefore they lost the status of permanent residency. Among the "erased people" there were only the members of ex-Yugoslav nations. As a consequence of losing permanent residency they also lost their jobs, flats, pensions, social security and health insurance. The situation of many has been only partially resolved at the end of the first decade of the 21st century, many of them have got Slovene citizenship, but most of them remain unemployed, because they had such a long-term experience of unemployment. The new Ministry of Interior, Katarina Kresal, is trying to solve some of the remaining problems, however, she faces strong resistance from the Slovene opposition and many other officials of the Ministry of Interior (NIPM3). She was already interpellated by the opposition due to the fact that she tries to solve the problems of the "erased", however, she successfully advocated the interpellation in the parliament. As the "erased" people did not have permanent residency or the Slovene citizenship they were completely excluded from political participation as well, they were not allowed to vote. The question of the compensation for the losses and human costs has not been resolved as well.
The member of "erased" people explained: "I lost my job, health insurance, family, home, I lost everything, in one night I became homeless. I have suffered the consequences of being "erased" for 12 years, however, I suffer even today, because of that. I have such consequences that I became handicapped. I have invalid pension, but because I was not allowed to work for 12 years, it is very low...It will not be better until the court in Strasbourg decides other way... I am sure I will not get compensation. To get compensation from the state, this is a game of lotto, if you get it or not. Because if you owe to the state, it will take it away from you immediately, but this is not the case if it is the state that owes you. I am sceptical if we ever get compensations..." (EIPM1).
8. Conclusion
The working paper was done in the scope of Workpackage 11 of Project 3 of the Included Project. The specific objective for Workpackage 11 was to analyse educational exclusion and inclusion and its connection to social exclusion and inclusion in the different areas of society (i.e. employment, health, housing and political participation) (Annex 1, Crea, 2006: 37).
In order to reach this objective the partners of the Included project did the secondary analysis of existing datasets and thus they identified the relationship between educational exclusion/inclusion and social exclusion and inclusion in European Union. Statistics on employment, health, housing and political participation were collected from European databases, and member states databases. The following databases were used: EUROSTAT, OECD, EUROBAROMETER, European Social Survey, World Values Survey and national statistics offices.
The objective of this working paper was to identify the gaps of data not covered in existing databases. The identification of gaps served to identify the data or indicators which are unavailable and which are necessary to confirm the knowledge provided by theoretical contributions as for example the analysis of literature which was done in Workpackage 10. The indicators which do not provide a connection with education were considered gaps of information as well, therefore the attention was paid to them as well. The identification of gaps was also based on a dialogical discussion with end-users
(members of vulnerable groups) and social agents (such as NGO's, public administrations' and other entities' representatives). The results of the interviews confirm the results of previous research and our suggestions for additional data and indicators.
In the selection and definition of indicators it is ideal if we use the well-defined theoretical model for a particular field as a starting point (Bevc et al, 2005), therefore we used the results of literature review in the scope of Workpackage 10 as a starting point. Indicators can not only describe societal conditions and trends, explain social situations, detect social problems etc. but also predict future societal conditions and processes (Bevc et al, 2005).
Some indicators, which exist on the national levels (collected by national statistics offices) should be included in the European databases as well in order to enable the comparison between member states. We can expect that if indicators are provided for more countries and allow comparison, their operative function increases and they can be even more useful to be used in policy development and planning (cf. Bevc et al, 2005). Besides, international comparisons in different fields are important, because they tell us if a national community is developed in particular field, it tells where it lags behind and where it has to enforce endeavours for further development. International comparisons also tell us where our comparable advantages (Bevc et al, 2005) are.
In the selection of indicators we following the principle of selectivity, namely, the limitation to the smaller number of most important indicators of wider scope guarantees better manageability and transparency (Bevc et al., 2005).
The fact that indicators in the European databases in different areas of society do not or very often do not include the members of vulnerable groups, particularly Roma and people with disabilities reflects their marginalized position in society. Their voices are not represented in the statistics, which is comparable to the fact their voices are not heard enough in contemporary societies. In order to improve their position in societies, we need to pay attention to their status also in the statistics. If they were included in the European databases, this might encourage policy makers to include them more in the policies and thus they would have a chance that their marginalized condition gets
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improved. Namely, we cannot be satisfied with the level of our democracies, if the voices of persons with disabilities and other most vulnerable groups are not included in them.
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