Nepal Earthquake Federation-wide Meta-evaluation

Nepal Earthquake Federation-wide Meta-evaluation: IFRC. Steve Powell (2020)

This report, written by Steve Powell, used an early version of Causal Map.

After the powerful earthquake which struck Nepal in April 2015, the International Red Cross Red and Crescent Movement (“the Movement”), among others, mobilized the full range of their resources to support the relief and recovery efforts, in line with Nepal government’s overall strategy, to support the Nepal Red Cross Society (NRCS) in leading the response. NRCS, IFRC and in-country Participating National Societies (PNSs) came to an agreement that individual partners will conduct their own final evaluations of individual projects, rather than a combined final evaluation. So it was proposed to also conduct a meta-evaluation of the individual final evaluations together with all other reviews and thematic studies conducted 2015 – 2019.

This report presents the results of that meta-evaluation.

A central part of the report was a qualitative synthesis of the summaries of over 30 evaluative reports. The methodology is described in the section beginning on p. 22. The design was partially deductive because some main high-level causal factors like Actions and Outcomes were pre-determined, and partly inductive because many lower-level factors were identified within these high-level groups.

The procedure was to read and analyse or “code” each of the main documents in turn. The focus was on the executive summary and conclusions sections of the primary documents, as these already represent an effort by the respective authors to summarise their own documents. The full text of the documents was considered mainly in order deepen understanding of the summaries.

This qualitative procedure, known as “coding”, made use of a very early version of qualitative text analysis software, Causal Map, later developed further by Bath SDR and the evaluator, which is specialised for evaluations because it makes it possible to capture reports of causal connections.

This coding approach was used in order to ensure that the reports were synthesised in a systematic and transparent way.