Intersections of Education for All and the Convention on the Rights of Persons with Disabilities: Explaining the Conflicting International Cadences of Inclusive Schooling
Bibliographic record
Abstract
Intersections of Education for All and the Convention on the Rights of Persons with Disabilities: Explaining the conflicting international cadences of inclusive schooling): Education for All (EFA) was encapsulated in a series of UN summits and conventions throughout the 1990s. In 2000, governments around the world adopted the Dakar Framework that addressed education for both development and the eradication of poverty. In 2006, changes in the global landscape for those with disabilities emerged with the Convention on the Rights of Persons with Disabilities (CRPD). Although the cadences differ, both the CRPD and EFA clearly identify inclusive education as one of the key strategies to address issues of marginalization and exclusion. Yet only 2 to 3 percent of those with disabilities go to school and, in the vast majority of education systems around the world, inclusive schooling remains extremely limited, if not non-existent.This paper centers on the CRPD embedded within the universal policy frameworks of Education for All. It explicitly draws attention to contradictions between the universal EFA and the disability-centric CRPD by assessing aspects such as hard-to-reach children, the invisibility of disabled persons on UNESCO’s statistical maps and in development agendas, and increasing segregation. We conclude that although progress of the CRPD is intimately connected to broad global education governance, the treaty is limited in maintaining an effective, proactive position within policy systems where it has constricted formal authority and financing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.044 |
| Scholarly communication | 0.016 | 0.015 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".