The maps are not always to scale. They are illustrative in nature and may not reflect the exact boundaries of the depicted areas. The designations employed and the presentation of material on this map do not imply the expression of any opinion whatsoever concerning the legal status of any country, territory, city or area or its authorities, or concerning the delimitation of its frontiers or boundaries on the part of the SeeD or its partners.
The illustration above is called a heatmap. Heatmaps illustrate regional differences to help identify areas of concern or priority to tailor policies and programmes, and to improve resource allocation more precisely. The heatmaps demonstrate the value of an indicator measured on a scale from 0 to 10, where 0 represents complete absence of the measured phenomenon in society and 10 represents its strong and prevalent presence. Only the differences higher than 0.5 points are considered statistically significant. You can find out more about how the scores are calculated under the methodology section.
Editorial notes
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Path Analysis
Path Analyses (Models) represent relations between different indicators based on advanced statistical analysis including regression, network analysis and structural equation modelling. In models, the relationships are directional, and they should be read from left to right. When an indicator is part of a model, we call them ‘drivers’, as they drive (positively or negatively) other indicators they are linked to. In a model, the indicator that all the drivers are influencing and predicting is called an ‘outcome’. Outcomes are at the right end of the model, and they are usually our end goals that we want to influence in the long term. We run models to understand how best to create positive change on an outcome, such as constructive citizenship or migration tendency. Red connecting lines in models represent a negative relationship and blue connecting lines represent a positive relationship between indicators. Thicker the arrows, stronger the relationship between the indicators. Models have predictive power, they should not be confused with correlations, where lines represent associations but they are not directional.
Indicator Details
The sankey charts below illustrate the way an outcome is constructed by showing the indicators that make up the outcome. You can check the glossary description of all indicators by typing the indicator name into the glossary search box top right corner of this page. Please note that all indicators that have an asterisks (*) have been reverse coded when calculating the overall outcome score.
Indicator Details
The sankey charts below illustrate the way an outcome is constructed by showing the indicators that make up the outcome. You can check the glossary description of all indicators by typing the indicator name into the glossary search box top right corner of this page. Please note that all indicators that have an asterisks (*) have been reverse coded when calculating the overall outcome score.
Compare Groups
Here you can explore demographic groups such as gender and age for the indicator selection above.
Regions
Groups
Explore Indicators
This visualization presents the score of each indicator of the currently selected dimension. The score of each indicator is the weighted mean of its sub-indicators.
Indicator Correlations
This visualization presents the relationships between the indicators of the currently selected dimension. The number of the arrows represent how strongly correlated the different indicators are on a scale from 0 (not at all) to 1 (totally). The closer the number is to 1 the more highly correlated two indicators are.
