Dunkley, Ria ORCID: https://orcid.org/0000-0003-0238-7344 and Franklin, Alex 2017. Failing better: the stochastic art of evaluating community-led environmental action programs. Evaluation and Program Planning 60 , pp. 112-122. 10.1016/j.evalprogplan.2016.11.005 |
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Abstract
This article provides insights into the evaluation of a government-funded action for climate change program. The UK-based program aimed to reduce CO2 emissions and encourage behavioral change through community-led environmental projects. It, thus, employed six community development facilitators, with expertise in environmental issues. These facilitators supported and learnt from 18 community groups over an 18-month period. The paper explores the narratives of the six professional facilitators. These facilitators discuss their experiences of supporting community groups. They also explain their contribution to the wider evaluation of the community-led projects. This paper reflects on the facilitator experience of the program’s outcome-led evaluation process. In turn, it also explores how the groups they supported experienced the process. The facilitator’s narratives reveal that often community-group objectives did not align with predefined outcomes established through theory of change or logic model methodologies, which had been devised in attempt to align to program funder aims. Assisting community action emerges in this inquiry as a stochastic art that requires funder and facilitator willingness to experiment and openness to the possibilities of learning from failure. Drawing on in-depth accounts, the article illustrates that a reflexive, interpretive evaluation approach can enhance learning opportunities and provides funders with more trustworthy representations of community-led initiatives. Yet, it also addresses why such an approach remains marginal within policy circles.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Geography and Planning (GEOPL) |
Subjects: | H Social Sciences > H Social Sciences (General) |
Publisher: | Elsevier |
ISSN: | 0149-7189 |
Date of First Compliant Deposit: | 9 November 2016 |
Date of Acceptance: | 6 November 2016 |
Last Modified: | 23 May 2023 18:52 |
URI: | https://orca.cardiff.ac.uk/id/eprint/95960 |
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