| Literature DB >> 33869442 |
Arno Van Hootegem1, Bart Meuleman1, Koen Abts2.
Abstract
The large inflow of asylum-seekers in recent years has heralded a diversification in adopted asylum policies across European societies. Although a growing body of research has addressed these versatile approaches and their implications for the European integration project, insight into the social basis of these restrictive or open asylum policies remains underdeveloped. Hence, the current study provides detailed insight into public preferences for asylum policies and offers a new understanding of how these attitudes are affected by diverging socio-economic realities across Europe. In addition, this paper considers the role of individual factors that coincide with publicly adopted frames in contemporary asylum debates. In particular, to explain how contextual differences reflect on opinion climates, the impacts of the policy, economic, and migratory context are studied. On the individual-level, we focus on threat perception and human values, which represent humanitarian, economic, and cultural frames. To explore these relations, data on 20 countries from the European Social Survey Round 8 (2016) are analyzed through a multilevel structural equation modeling approach. Results indicate that, on the contextual-level, only unemployment rates have a significant impact and, rather surprisingly, lower unemployment rates provoke a more negative opinion climate. Yet, this relationship seems to be largely driven by some specific countries that are characterized by large unemployment rates and relatively positive opinion climates simultaneously. The migratory and policy context, on the other hand, do not influence attitudes toward asylum policy. This indicates that it is not necessarily the countries facing the largest inflow of asylum-seekers or issuing the most positive decisions on asylum applications that have the most restrictive opinion climates. As shown by the important roles of human values and threat perceptions, which represent widely adopted frames, public discourses seem much more important in explaining attitudes toward asylum policy across Europe.Entities:
Keywords: attitudes toward asylum policy; economic context; human values; migratory context; multilevel structural equation modeling; policy context; threat perceptions
Year: 2020 PMID: 33869442 PMCID: PMC8022488 DOI: 10.3389/fsoc.2020.00035
Source DB: PubMed Journal: Front Sociol ISSN: 2297-7775
Figure 1Conceptual model with hypotheses.
Figure 2Model with estimated empirical relationships.
Figure 3Means (ȳ) and standard deviations (sd) of attitudes toward asylum policy in 2002 and 2016.
Standardized parameter estimates and posterior probability intervals of a model predicting attitudes toward asylum policy (N = 31,596).
| Female (ref) | ||||||||||
| Male | 0.026 | [0.013 to 0.040] | −0.085 | [−0.099 to −0.069] | 0.001 | [−0.011 to 0.012] | −0.054 | [−0.065 to −0.043] | 0.037 | [0.024 to 0.051] |
| 0.172 | [0.158 to 0.186] | 0.028 | [0.013 to 0.044] | 0.004 | [−0.008 to 0.017] | −0.018 | [−0.030 to −0.005] | 0.018 | [0.004 to 0.032] | |
| Lower (secondary) | 0.022 | [0.008 to 0.038] | −0.027 | [−0.043 to −0.011] | 0.000 | [−0.012 to 0.013] | 0.029 | [0.017 to 0.042] | −0.044 | [−0.059 to −0.030] |
| Higher secondary (ref) | ||||||||||
| Tertiary | −0.075 | [−0.091 to −0.060] | 0.098 | [0.082 to 0.114] | −0.096 | [−0.109 to −0.083] | −0.089 | [−0.102 to −0.076] | −0.009 | [−0.024 to 0.006] |
| Comfortable (ref) | ||||||||||
| Coping | 0.018 | [0.003 to 0.033] | −0.076 | [−0.092 to −0.060] | 0.061 | [0.048 to 0.073] | 0.063 | [0.051 to 0.075] | −0.024 | [−0.038 to −0.011] |
| Difficult | 0.010 | [−0.005 to 0.025] | −0.065 | [−0.081 to −0.048] | 0.105 | [0.093 to 0.117] | 0.114 | [0.102 to 0.126] | 0.000 | [−0.015 to 0.014] |
| Very difficult | −0.001 | [−0.015 to 0.014] | −0.044 | [−0.059 to −0.029] | 0.085 | [0.074 to 0.097] | 0.090 | [0.079 to 0.102] | 0.027 | [0.014 to 0.042] |
| Service | −0.001 | [−0.017 to 0.014] | 0.027 | [0.010 to 0.043] | −0.028 | [−0.041 to −0.016] | −0.032 | [−0.045 to −0.020] | −0.008 | [−0.023 to 0.006] |
| Blue collar (ref) | ||||||||||
| White collar | 0.000 | [−0.020 to 0.020] | 0.053 | [0.032 to 0.073] | −0.050 | [−0.066 to −0.034] | −0.058 | [−0.075 to −0.042] | −0.004 | [−0.023 to 0.014] |
| Self–employed | −0.015 | [−0.031 to 0.000] | 0.038 | [0.021 to 0.055] | −0.017 | [−0.030 to −0.003] | −0.029 | [−0.042 to −0.016] | 0.012 | [−0.002 to 0.027] |
| Unemployed | −0.014 | [−0.029 to 0.001] | 0.057 | [0.040 to 0.073] | −0.010 | [−0.023 to 0.002] | 0.008 | [−0.004 to 0.021] | −0.014 | [−0.028 to 0.000] |
| Retired/non–active | 0.006 | [−0.014 to 0.027] | 0.086 | [0.063 to 0.107] | −0.068 | [−0.086 to −0.051] | −0.072 | [−0.089 to −0.055] | −0.057 | [−0.076 to −0.037] |
| 0.290 | [0.276 to 0.304] | 0.082 | [0.067 to 0.096] | −0.098 | [−0.110 to −0.085] | −0.102 | [−0.115 to −0.090] | −0.047 | [−0.062 to −0.033] | |
| Rural area (ref) | ||||||||||
| Big city, suburbs or town | −0.061 | [−0.074 to −0.047] | 0.014 | [0.000 to 0.028] | −0.038 | [−0.049 to −0.027] | −0.055 | [−0.066 to −0.044] | −0.011 | [−0.024 to 0.001] |
| Not safe (ref) | ||||||||||
| Safe | −0.046 | [−0.060 to 0.032] | 0.063 | [0.048 to 0.078] | −0.103 | [−0.115 to −0.092] | −0.089 | [−0.100 to −0.078] | −0.024 | [−0.038 to −0.011] |
| 0.392 | [0.372 to 0.413] | 0.325 | [0.304 to 0.345] | 0.168 | [0.142 to 0.194] | |||||
| −0.412 | [−0.431 to −0.393] | −0.328 | [−0.347 to −0.310] | −0.286 | [−0.311 to −0.261] | |||||
| 0.272 | [0.255 to 0.289] | |||||||||
| 0.328 | [0.310 to 0.347] | |||||||||
| 0.169 | 0.050 | 0.261 | 0.205 | 0.497 | ||||||
| 0.001 | [−0.444 to 0.444] | |||||||||
| −0.171 | [−0.703 to 0.412] | |||||||||
| −0.581 | [−0.914 to −0.114] | |||||||||
| 0.382 | [−0.201 to 0.861] | |||||||||
| 0.497 | ||||||||||
PPI, posterior probability interval;
P < 0.05; X.
Figure 4Scatterplot of country means of attitudes toward asylum policy and average unemployment rates between 2011 and 2016.