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Thanks for this interesting discussion on the challenges of combating
discrimination in education.

One obstacle which CESR has identified in its work in different countries is the reductive understanding of discrimination among many education policy–makers.
One of the most valuable contributions of recent human rights thinking on discrimination is the expansive scope of the concept included in human rights interpretations (such as the recent General Comment of the UN Committee on Economic, Social and Cultural Rights on discrimination). However, this understanding of discrimination is rarely reflected in the practice. Even well-intentioned efforts to tackle discrimination are all too often limited to ensuring formal rather than substantive equality. They rarely address the societal roots of discrimination and frequently fall short of recognizing an obligation to redress historical patterns of inequality. As a result, education policy frequently neglects the positive measures needed to eliminate the conditions which prevent girls, indigenous people, rural dwellers or the poor from accessing and benefiting equally from the educational system.

Governments often present disparities in education as the natural or inevitable consequences of historical inequalities, rather than the result of their own policy choices. A simple but powerful tool for exposing discrimination in education policy is using statistical data to make disparities visible and trace them back to the policy failures that give rise to them.

Just to give an example, in a recent project assessing the rights to education, health and food in Guatemala, we used development data to visualize disparities of education outcomes in a compelling way. For example, the tree graph in Fig 12 of this factsheet shows intersecting disparities in youth literacy - literacy levels among non-indigenous urban men meet the Latin American average, whereas literacy levels among indigenous, rural women are the same as those in Burundi. [See: http://www.cesr.org/downloads/Guatemala%20Fact%20Sheet.pdf]. Tracking disaggregated indicators over time made visible the lack of progress in reducing gender disparities in primary completion, a hidden problem if one only looks at aggregate level progress.

We then looked at which populations where benefitting most from some of the key policy interventions aimed at making education more available, accessible, appropriate and of better quality. By contrasting indicators such as number of girls receiving grants or children benefitting from school food programs with data on school
desertion, we were able to show at a glance how the areas with the highest desertion rates (and highest percentage of poor and indigenous people) were those which least benefited from these programs. Analysis of basic budget data revealed that education spending as a whole was disproportionally benefitting the rich, and that specific programs such as scholarships intended for disadvantaged children were in fact
mostly going to the richest 20% of the population.

So this is just to back up the point Peter mentions in his earlier posting about using indicators. Analysed in the light of human rights principles, indicators and statistical data can certainly help build the case that disparities of outcome are the result of discrimination in policy.