Migrant Penalties in Educational Achievement

Second-generation Immigrants in Western Europe

Auteur: Borgna, Camilla
Éditeur: Amsterdam University Press
Collection: Changing Welfare States
ISBN: 9789462981348
eISBN Pdf: 9789048530991
Lieu de publication: Amsterdam , Netherlands
Année de publication électronique: 2017
Mois : Septembre
Pages: 210
Langue: Anglais

Légende

The integration of second-generation immigrants has proved to be a major challenge for Europe in recent years. Though these people are born in their host nations, they often experience worse social and economic outcomes than other citizens. This volume focuses on one particular, important challenge: the less successful educational outcomes of second-generation migrants. Looking at data from seventeen European nations, Camilla Borgna shows that migrant penalties in educational achievement exist in each one-but that, unexpectedly, the penalties tend to be greater in countries in which socio-economic inequalities in education are generally more modest, a finding that should prompt reconsideration of a number of policy approaches.

Cover
Table of Contents
Acknowledgements
1. Introduction
- 1.1 Children of migrants in Europe: which equal opportunities?
- 1.2 The promise of diversity-oriented methods
- 1.3 Structure of the book
2. Conceptual framework and case selection
- 2.1 Social inequalities in education
- 2.2 Educational systems as opportunity structures
- 2.3 Defining children of immigrants
- 2.4 Case selection: comparing immigration societies
- 2.5 Educational systems in Western Europe
3. The educational achievement of second-generation immigrants in Western Europe
- 3.1 Previous studies
  - 3.1.1 A double disadvantage
  - 3.1.2 The role of teachers, classrooms, and schools
  - 3.1.3 Cross-country differences
- 3.2 Migrant penalties in educational achievement
  - 3.2.1 Research questions and hypotheses
  - 3.2.2 Analytical strategy
  - 3.2.3 Data, operationalization, and models
  - 3.2.4 Results and discussion
- 3.3 Compound disadvantages
  - 3.3.1 Research questions
  - 3.3.2 Analytical strategy
  - 3.3.3 Operationalization: fuzzy-set calibration
  - 3.3.4 Results and discussion
4. The role of educational systems for migrant learning disadvantage
- 4.1 Previous studies
  - 4.1.1 Educational institutions and socioeconomic disadvantage
  - 4.1.2 Educational institutions and migrant learning disadvantage
  - 4.1.3 Cross-country explanatory studies
- 4.2 Hypotheses formulation
  - 4.2.1 Theoretically relevant dimensions of educational systems
  - 4.2.2 Contextual factors
- 4.3 Analytical strategy
- 4.4 Operationalization
  - 4.4.1 Variable construction
  - 4.4.2 Fuzzy-set calibration
- 4.5 Results from a variable-oriented approach
  - 4.5.1 Bivariate correlations
  - 4.5.2 Multivariate analysis
  - 4.5.3 Regression-tree analysis
- 4.6 Results from a diversity-oriented approach
  - 4.6.1 Assessing individual necessity and sufficiency
  - 4.6.2 Institutional configurations
  - 4.6.3 fsQCA: model construction and robustness checks
  - 4.6.4 Final fsQCA results and discussion
5. Conclusions
- 5.1 Key findings
- 5.2 Methodological contributions
- 5.3 Policy implications
- 5.4 Limitations and outlook
Appendix A: Appendix to Chapter 3
Appendix B: Appendix to Chapter 4
References
Index
List of tables and figures
- Tables
  - Table 2.1 – Sample sizes of G2 in all Western European countries
  - Table 2.2 – Indicators of schooling duration
  - Table 2.3 – Indicators of stratification, resources allocation, and standardization
  - Table 3.1 – Country-specific regressions of math scores estimated using replicate weights and plausible values
  - Table 3.2 – Advantage and disadvantage coincidence scores
  - Table 4.1 – Distribution of the source variables by country
  - Table 4.2 – Source variables, sets, and critical thresholds for calibration
  - Table 4.3 – Pearson’s correlation matrix of ‘Migrant achievement penalty,’ ‘Age at tracking,’ ‘G2 average (pre)school entry age,’ ‘Marginalization in low-performing schools,’ ‘Starting decade for mass immigration,’ and ‘Proportion of G2 with high linguisti
  - Table 4.4 – Coefficients and fit values of OLS regression of ‘Migrant achievement penalty’ on ‘Age at tracking,’ ‘G2 average (pre)school entry age,’ ‘Marginalization in low-performing schools,’ ‘Immigration decade,’ ‘Proportion of G2 with high linguistic d
  - Table 4.5 – Results of analysis of necessity for the presence and the absence of the outcome
  - Table 4.6 – Results of analysis of sufficiency for the presence and the absence of the outcome
  - Table 4.7 – Conservative solution of the minimization of the truth table for the presence of the outcome
  - Table 4.8 – Intermediate solution of the minimization of the truth table for the presence of the outcome
  - Table 4.9 – Intermediate solution of the minimization of the truth table for the presence of the outcome (recalibrated)
  - Table 4.10 – Conservative solution of the minimization of the truth table for the presence of the outcome (recalibrated)
  - Table 4.11 – Intermediate solution of the minimization of the truth table for the presence of the outcome (recalibrated)
  - Table 4.12 – Conservative solution of the minimization of the truth table for the absence of the outcome (recalibrated)
  - Table 4.13 – Intermediate solution of the minimization of the truth table for the absence of the outcome (recalibrated)
  - Table A.1 – Sample sizes used for individual-level analyses in Chapter 3, by country and migratory status
  - Table A.2 – Mean and standard deviations of math score, by country and migratory status
  - Table A.3 – Mean and standard deviations of ESCS, by country and migratory status
  - Table A.4 – Country-specific regressions of reading scores estimated using replicate weights and plausible values
  - Table A.5 – Country-specific regressions of science scores estimated using replicate weights and plausible values
  - Table A.6 – Means and standard deviations of HISCED, HISEI, CULTPOS, and WEALTH
  - Table A.7 – Source variables, thresholds and criteria for the fuzzy-set calibration of factors of advantage and disadvantage used in the fuzzy-set coincidence analyses
  - Table B.1 – Truth table for the presence of the outcome
  - Table B.2 – Conservative solution of the minimization of the truth table for the presence of the outcome
  - Table B.3 – Intermediate solution of the minimization of the truth table for the presence of the outcome
  - Table B.4 – Truth table for the presence of the outcome
  - Table B.5 – Truth table for the presence of the outcome (recalibrated)
  - Table B.6 – Conservative solution of the minimization of the truth table for the presence of the outcome (recalibrated)
  - Table B.7 – Conservative solution of the minimization of the truth table for the absence of the outcome
  - Table B.8 – Easy counterfactuals used in the truth table minimization to produce the intermediate solution for the presence of the outcome
  - Table B.9 – Easy counterfactuals used in the truth table minimization to produce the intermediate solution for the absence of the outcome
- Figures
  - Figure 2.1 – Venn diagram depicting the institutional dimensions (in textboxes) theoretically relevant for one or more manifest functions of educational system
  - Figure 3.1 – Overall underachievement and migrant achievement penalty
  - Figure 3.2 – Migrant penalties vs. socioeconomic penalties in educational achievement
  - Figure 3.3 – Typology of educational systems by Inequality of Educational Opportunity (IEO) driven by SES and migratory status
  - Figure 3.4 – Migrant penalties vs. socioeconomic penalties, for Turkish students only
  - Figure 3.5 – Set coincidence vs. correlation
  - Figure 3.6 – Differential coincidence of assets and achievement gaps
  - Figure 4.1 – Calibration of outcome and conditions
  - Figure 4.2 – Linear correlation plots between ‘Age at tracking,’ ‘G2 average (pre)school entry age,’ ‘Marginalization in low-performing schools,’ ‘Proportion of G2 with high linguistic distance,’ and ‘Migrant achievement penalty.’ Peculiar cases identified
  - Figure 4.3 – Results of regression-tree analysis of ‘Migrant achievement penalty’ on ‘Age at tracking,’ ‘G2 average (pre)school entry age,’ ‘Marginalization in low-performing schools,’ ‘Proportion of G2 with high linguistic distance’
  - Figure 4.4 Fuzzy-set plots of necessary institutional conditions for the presence (left) and the absence (right) of the outcome
  - Figure 4.5 Fuzzy-set plot of LATE ENTRY as a sufficient condition for the presence of the outcome
  - Figure 4.6 Venn diagram depicting all logically possible combinations of TRACKED, EARLY TRACKED, LATE ENTRY, early entry, MARGINALIZING
  - Figure 4.7 – Fuzzy-set plot of the whole solution for the presence of the outcome
  - Figure 4.8 – Fuzzy-set plot of the whole solution for the presence of the outcome (recalibrated)
  - Figure 4.9 – Paths to ‘SEVERE PENALTIES’
  - Figure 4.10 – Fuzzy-set plot of the whole solution for the absence of the outcome (recalibrated)
  - Figure 4.11 – Paths to ‘severe penalties’
  - Figure A.1 – Consistency of results with alternative model specification
  - Figure A.2 – Consistency of results with alternative model specification
  - Figure A.3 – Consistency of results with alternative model specification
  - Figure B.1 – Results of regression-tree analysis of ‘Migrant achievement penalty in science literacy’ on ‘Age at tracking,’ ‘G2 average (pre)school entry age,’ ‘Marginalization in low-performing schools,’ ‘Proportion of G2 with high linguistic distance’
  - Figure B.2 Results of regression-tree analysis of ‘Migrant achievement penalty in reading literacy’ on ‘Age at tracking,’ ‘G2 average (pre)school entry age,’ ‘Marginalization in low-performing schools,’ ‘Proportion of G2 with high linguistic distance’