While combating social exclusion has been a key target of the European Union’s social policy in recent years, the concept remains contested and various ways of measuring its prevalence have been proposed. In the Netherlands a survey-based method has been in use since 2004, which refers to four theoretical elements of social exclusion: material deprivation, limited social participation, inadequate access to basic social rights and a lack of normative integration. In this article we propose an improved and more concise version of the instrument. Using focus groups and cognitive tests, the study first examined whether it adequately covers the different elements of social exclusion. Based on the results, the existing items were reformulated and supplemented. A revised questionnaire was then submitted to a new stratified sample of 650 respondents, randomly drawn from an online panel and a database of people without access to the Internet. The weighted outcomes may be regarded as representative for the entire adult Dutch population, although some caveats apply. Using nonlinear canonical correlation analysis, we identified a single underlying dimension in our new data set. This contains 15 items, with three to four indicators for each of the theoretical elements of social exclusion. According to our general index, just under 5 % of the Dutch population aged 18 years or older are faced with a serious degree of social exclusion. On the four subscales the figure ranges from 7 % (social rights) to 22 % (material deprivation).
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In its ‘Vienna Declaration’, the World Conference on Human Rights (1993) stated that ‘extreme poverty and social exclusion constitute a violation of human dignity’. The Council of Europe (1998) went a step further, in recommending that ‘social exclusion not only offends against human dignity and denies people their fundamental human rights; it also leads […] to phenomena of marginalization, withdrawal or violent reactions, thereby creating conditions which undermine the democratic foundations of our societies’. From this legalistic perspective – which has strong moral appeal – affirmative action has been propagated, in order to safeguard the rights of political refugees, migrant workers, indigenous people, ethnic minorities, women, children, disabled persons, homosexuals, transgender people, etc. To some extent the international human rights movement has been successful in achieving this goal, as shown by the adoption of the UN Convention on the Rights of Persons with Disabilities (2006).
Poverty can therefore best be assessed by comparing disposable income and other resources to budget standards set by experts and consensual methods (Walker 1987; Bradshaw 1993; Bradshaw et al. 2008; Bradshaw and Mayhew 2011). For the Netherlands this method has been elaborated in various studies (Soede and Vrooman 2008; Vrooman 2009; Hoff et al. 2010) and is used to monitor poverty on an annual basis (CBS/SCP 2011).
It should be noted that the actual policy objectives of EU countries with regard to these main indicators are rather diverse (EC 2011a). This is because each member state is free to translate the general Europe 2020 goal into specific targets, taking national circumstances and priorities into account. As a result, some countries have confined their aims to reducing or stabilizing the relative poverty risk (e.g. Estonia, Czech Republic), while others wish to reduce the number of people in jobless households (e.g. the Netherlands); and in several cases particularistic national goals have been set (e.g. Sweden, which pursues a falling share of long-term unemployed people, those on long-term sick leave, and those outside the labour force).
The original report on this project was published in Dutch (Hoff and Vrooman 2011).
The weighting variables are age, gender, ethnic origin, level of education, household size, region, gross annual income (four classes) and Internet access.
The canonical correlation is computed using the following formula: rd = ((K × Ed) − 1)/(K − 1), where d is the latent dimension (1), K is the number of sets (4), and E is the eigenvalue (0.53).
In the EU approach, a person is regarded as materially deprived when he or she cannot afford four out of nine consumer durables. However, three of these are goods which are present in virtually every Western European household: a colour TV, a telephone and a washing machine. In order to be classified as materially deprived, respondents in the more prosperous societies must therefore in fact lack four of the remaining six items, which is a fairly severe requirement (cf. Nolan and Whelan 2011). By contrast, our assessment of material deprivation is based on exceeding the threshold value on a subscale of four items that are more discriminative in affluent societies: insufficient financial means for a club membership, for visiting family or friends, for heating one’s home properly and not being able to meet an unexpected expense of € 1,000 (cf. table 3).
Jehoel-Gijsbers and Vrooman (2008a) used the 2006 wave of EU-SILC. They also applied nonlinear canonical correlation analysis to construct a social exclusion index, but their scale only covered material deprivation, limited social participation and inadequate access to basic social rights (confined to health care and housing). Information about the dimension ‘lack of normative integration’ was not available.
An English version of the extended social exclusion questionnaire (190 separate items) may be obtained from the authors.
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Vrooman, J.C., Hoff, S.J.M. The Disadvantaged Among the Dutch: A Survey Approach to the Multidimensional Measurement of Social Exclusion. Soc Indic Res 113, 1261–1287 (2013). https://doi.org/10.1007/s11205-012-0138-1
- Social exclusion
- Nonlinear canonical correlation analysis
- Social participation
- Normative integration
- Material deprivation
- Social rights