Intensity, structure, and persistence of deprivation


Step 1 Select a dimension of ex/inclusion Open

Selected: Intersecting risks and drivers

Some groups are at a higher risk of exclusion and inequality, but the status of excluded often transcends a single group affiliation and lies at the intersection of multiple identities.  Being a female – as a factor – may not automatically put someone at a high risk of exclusion from the labour market. But being a Roma woman from an under-served rural community in Central and Eastern Europe increases the risk dramatically.


The traditional group-based approach to ex/inclusion is primarily concerned with identification and support, through social insurance, of excluded groups vulnerable to uninsured risks. More recent approaches focus on individual risks, pointing out that the group-based lens may not provide strong evidentiary basis to weigh policy options in the case of multiple sources of exclusion.  Applied individually, both of these approaches may suffer from errors and blind spots. Yet a combination of the two – i.e., an approach of intersecting risks and drivers – is feasible and has a solid policy value.


Four inclusive policy markers are used to operationalize this dimension.

Step 2 Select an Inclusive Policy Marker Open

Selected: Exclusion risks and their intersections

Policy and practice need to be mindful of group-specific conditions but go deeper in their risk analysis to capture cumulative disadvantages, as well as prevalence and intensity of exclusion and inequality as experienced by in real-life by the affected individuals, categories and groups. Three key points elaborate on why and how this issue can be approached.  

Step 3 Select a Policy Design Consideration

Selected: Intensity, structure, and persistence of deprivation

Inclusive measures weigh their breadth and depth in accordance with the real-life structure of the exclusion and inequalities they are set to untangle. For this, they need to both headcount the deprived – i.e., diagnose the prevalence – and to grasp the structure and number of deprivations the affected people face on average – i.e., diagnose the intensity of real-life deprivation. Diagnosing the links between different deprivations (if and how these are correlated; if there are patterns in their overlaps/cumulation) is equally required for the design of all all-round provisions.


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