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Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation

In recent years, global attention to disability inclusion in humanitarian and development contexts, notably comprising disability inclusion within the Sustainable Development Goals, has significantly increased. As a result, UN agencies and programmes are increasingly seeking to understand and increa...

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Detalles Bibliográficos
Autores principales: O’Reilly, Claire F., Caffrey, Louise, Jagoe, Caroline
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8507717/
https://www.ncbi.nlm.nih.gov/pubmed/34639630
http://dx.doi.org/10.3390/ijerph181910334
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author O’Reilly, Claire F.
Caffrey, Louise
Jagoe, Caroline
author_facet O’Reilly, Claire F.
Caffrey, Louise
Jagoe, Caroline
author_sort O’Reilly, Claire F.
collection PubMed
description In recent years, global attention to disability inclusion in humanitarian and development contexts, notably comprising disability inclusion within the Sustainable Development Goals, has significantly increased. As a result, UN agencies and programmes are increasingly seeking to understand and increase the extent to which persons with disabilities are accounted for and included in their efforts to provide life-saving assistance. To explore the effects and effectiveness of such measurement, this paper applies a complexity-informed, realist evaluation methodology to a case study of a single measurement intervention. This intervention, ‘A9’, was the first indicator designed to measure the number of persons with disabilities assisted annually by the United Nations World Food Programme (WFP). Realist logic of analysis combined with complexity theory was employed to generate context-mechanism-outcome configurations (CMOC’s) against which primary interviews and secondary data were analysed. We show that within the complexity of the WFP system, the roll-out of the A9 measurement intervention generated delayed, counter-intuitive and unanticipated effects. In turn, path dependency and emergent behaviours meant that the intervention mechanisms of yesterday were destined to become the implementation context of tomorrow. These findings challenge the current reliance on quantitative data within humanitarian-development disability inclusion efforts and contribute to our understanding of how data can best be leveraged to support inclusion in such contexts.
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spelling pubmed-85077172021-10-13 Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation O’Reilly, Claire F. Caffrey, Louise Jagoe, Caroline Int J Environ Res Public Health Article In recent years, global attention to disability inclusion in humanitarian and development contexts, notably comprising disability inclusion within the Sustainable Development Goals, has significantly increased. As a result, UN agencies and programmes are increasingly seeking to understand and increase the extent to which persons with disabilities are accounted for and included in their efforts to provide life-saving assistance. To explore the effects and effectiveness of such measurement, this paper applies a complexity-informed, realist evaluation methodology to a case study of a single measurement intervention. This intervention, ‘A9’, was the first indicator designed to measure the number of persons with disabilities assisted annually by the United Nations World Food Programme (WFP). Realist logic of analysis combined with complexity theory was employed to generate context-mechanism-outcome configurations (CMOC’s) against which primary interviews and secondary data were analysed. We show that within the complexity of the WFP system, the roll-out of the A9 measurement intervention generated delayed, counter-intuitive and unanticipated effects. In turn, path dependency and emergent behaviours meant that the intervention mechanisms of yesterday were destined to become the implementation context of tomorrow. These findings challenge the current reliance on quantitative data within humanitarian-development disability inclusion efforts and contribute to our understanding of how data can best be leveraged to support inclusion in such contexts. MDPI 2021-09-30 /pmc/articles/PMC8507717/ /pubmed/34639630 http://dx.doi.org/10.3390/ijerph181910334 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
O’Reilly, Claire F.
Caffrey, Louise
Jagoe, Caroline
Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation
title Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation
title_full Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation
title_fullStr Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation
title_full_unstemmed Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation
title_short Disability Data Collection in a Complex Humanitarian Organisation: Lessons from a Realist Evaluation
title_sort disability data collection in a complex humanitarian organisation: lessons from a realist evaluation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8507717/
https://www.ncbi.nlm.nih.gov/pubmed/34639630
http://dx.doi.org/10.3390/ijerph181910334
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