Explore the vast range of titles available.

The Netherlands faces a shortage of organ donors. Figures from Statistics Netherlands show that of Dutch residents aged 12 and over, only one in four is a registered organ donor. In July 2020, a new law has changed the system from ‘opt-in’ to ‘opt-out’, with the aim of increasing the number of registered donors. Under the new system, everyone is in principle automatically registered as a donor unless they decline permission for their organs to be used. But what are the drivers of organ donation? This question is particularly interesting in the Netherlands, not only because of the new law, but also in light of the diversity in social capital and religious involvement which may play an important role in the decision to donate. This paper explores the impact of social capital on organ donation. It uses a unique database which contains information on organ donation for the whole Dutch population over 12, enriched by the Survey on Social Cohesion and Wellbeing covering the period 2012–2017 (N = 45,645). Results demonstrate a linear increase in registered organ donors as individual social capital, measured by a composite index based on 17 participation and trust indicators, increases. The results further show that religion has a detrimental impact on organ donation. The paper also discusses the effects of the separate social capital indicators on organ donation and their policy implications.

The notion that naturalisation matters for the economic integration of immigrants is well established in the literature, but why and to whom that is, remains surprisingly ambiguous. The citizenship premium is traditionally assumed to result from increased labour market access and positive signalling towards employers, but these mechanisms fail to explain increased earnings derived from paid employment, which has been the predominant focus in most studies. We argue that naturalisation needs to be understood in the context of the life course, as immigrants anticipate rewards and opportunities of citizenship acquisition by investing in their human capital development. Insofar as naturalisation subsequently leads to higher earnings, we expect that the citizenship premium mostly reflects better employment opportunities rather than access to better paying jobs. To test these assumptions, we use high-quality register data from Statistics Netherlands, covering the period 1999–2011. These data contain almost all registered foreign-born individuals in The Netherlands ( N  = 74,531) and allow us to track immigrant cohorts over time. Results show that naturalisation confers a one-time boost in earnings after naturalisation, but particularly for migrants from economically less developed countries and unemployed migrants. Furthermore, earnings develop faster leading up to naturalisation than afterwards, consistent with the notion of anticipation. The relevance of citizenship for employed immigrants in part results from an increase in working hours, but is not explained by variation in labour market sectors. We conclude that citizenship matters in terms of earnings from labour, but that its impact is not universal and manifests predominantly leading up to naturalisation.

Statistics Netherlands (CBS) has recently developed the whole population network (Person Network) file, based on administrative microdata, which includes over a billion interpersonal relationships among approximately 17 million inhabitants of the Netherlands, spanning each year from 2009 onward. Additionally, over the past decade, CBS has conducted the annual Social Cohesion and Well-being (SSW) survey, gathering responses from 83,667 representative individuals on various indicators of social cohesion, including social contacts, volunteering, political participation, and trust in others and institutions. In this study, we construct a merged dataset linking the Person Network file and the SSW survey. We examine the associations between social network centrality and 17 indicators of social capital, including a composite index, and further analyze how family and neighbourhood network centrality relate to self-reported contact with family members and neighbours. While some statistically significant relationships are found, particularly for family centrality, the associations are generally weak, suggesting that current network abstractions capture limited aspects of actual social capital. The findings underscore the need for more refined and substantively meaningful network measures to better understand the structure and quality of social interactions.

Migration’s influence in shaping population dynamics in times of impending climate and population crises exposes its crucial role in upholding societal cohesion. As migration impacts virtually all aspects of life, it continues to require attention across scientific disciplines. This study aims to bridge the gap between theoretical understanding and practical application by integrating network analysis and regression methodologies within Migration Studies. In the study we employ network analysis to elucidate migration patterns at various geographical scales-city, country, and global. Additionally, regression analysis is discussed on an exploratory level, where we focus on the underlying factors driving migration, and identifying the key independent variables to enhance predictive accuracy. The study exposes distinct migration network structure and its features, and the consequences these have on conventional regression analysis applications. We conclude on the importance of methodological coherence and disciplinary integration, and highlight the avenues for enhancing the predictive power of migration models.

This paper discusses the limitations of harmonised sampling designs for survey research on immigrants in Germany and the Netherlands. Although the concepts for immigrants are largely similar in both countries, there are severe constraints when it comes to comparable sampling designs. While in the Netherlands a sample can be drawn from a national population register by Statistics Netherlands, this is impossible in Germany due to the decentralised setup of the population register and legal restrictions on merging existing databases. Harmonisation of immigrant statistics is thus less a problem at the concept level than in the implementation. Achieving a harmonised data collection on immigrants for Germany and the Netherlands will be a major challenge.

While international election observations missions often aim to present generalizable claims about the quality and integrity of an election, their findings are rarely based on a representative sample of observations, undermining the credibility of the missions. Bias in the selection of polling stations, among other things, can inflate or deflate the percentage of polling stations where observers find significant flaws. This article uses original data from Organization for Security and Co-operation in Europe (OSCE) election observation missions to illustrate the nature of the problem of selection bias in international election observation, and show how the percentage of ‘bad’ polling stations (in the absence of selection bias) can be estimated through a weighting procedure. The article finds that, while there is a strong degree of selection bias, this does not significantly impact the overall percentage of ‘bad’ polling stations that is reported by OSCE observation missions.

This paper outlines a regional and socio-demographic overview of languages and dialects used most often in and outside the home and on social media in the Netherlands based on a large-scale national representative survey by Statistics Netherlands conducted in 2019 among 7,652 people aged 15 years or older. 149 different languages/dialects were reported to be spoken at home, in other places or used for writing messages on social media. For 25 percent of the people surveyed, Dutch is not dominating at home: 8.2 percent speak another language than Dutch; 10.2 percent a regional language (Low Saxon 4.8 percent; Limburgish 3.4 percent, and Frisian 2.0 percent), and 5.3 percent dialect. The five most widely spoken other languages are English (1.6 percent), Turkish (0.9 percent), Moroccan Arabic/Berber (0.8 percent), Chinese/Mandarin (0.4 percent) and Polish (0.4 percent). 83 percent mostly use Dutch to write messages on social media with English following (35 percent).

This paper focuses on the measurement of social exclusion. As an illustration, we investigate how many people are socially excluded in the Netherlands. The study also inquired about whether social exclusion is correlated with certain background characteristics, such as gender, age, ethnicity and income. We develop an index based on 42 indicators ranging over four dimensions: (1) participation; (2) material deprivation; (3) access to basic rights; and (4) value orientations. The four dimensions were captured by the Dutch 2010 EU-SILC, in which a specific module on social exclusion was added (n = 10,124). A total of 4.2 % of the adult population show very low scores on at least two of the four dimensions, and thus can be considered socially excluded.

This paper integrates a set of independent social capital indicators into one index by using structural equation modeling (SEM) based on partial least squares estimation (PLS). The social capital index consists of two dimensions: participation and trust. In each of the two dimensions, three levels are distinguished: social (micro), organizational (meso), and political (macro). The main objectives of the index are to: (1) provide a coherent overview of social capital in the Netherlands; (2) monitor social capital over time; and (3) compare subpopulations. A broad spectrum of indicators is included, however, these are only weakly correlated and consequently treated as distinct. Therefore, traditional index development methods such as factor analysis and reflective modeling cannot be applied. Consequently, formative modeling in which the indicators are specified as causes rather than as effects is used. We employ the Permanent Survey on Living Conditions 2009 (POLS), administered face-to-face to 7,560 respondents in the Netherlands. We find that the index predicts well-being and health, which demonstrates nomological validity. Subsequently, bootstrapping is conducted to test the robustness of the index. And the 2009 index is replicated based on the 2010 POLS data. The replication shows that the 2009 model is relatively stable and results are robust. Finally, the model is extended by including volunteering and informal help, which changes the model but the results remain largely the same. This index, which is shown to be valid and robust, contributes to a further understanding of the concept of social capital.