Lessening the unknown: An unintended consequences knowability classification schema for international development projects
Year: 2025
Type: article
Abstract: This article introduces the Unintended Consequences Knowability Classification Schema, a typological tool to support evaluators in classifying unintended consequences based on their knowability. Drawing on gaps in the literature, the Unintended Consequences Knowability Classification Schema addresses the need for a field-ready framework that distinguishes among anticipated, foreseeable and unforeseeable unintended consequences. It offers conceptual clarity and practical utility across the programme cycle, from design to evaluation, helping practitioners surface blind spots, guide proportionate responses and support adaptive management. The schema complements complexity-aware approaches by integrating contextual insight and actor-dependent foresight without presuming linear causality. Application examples, including in fragile and conflict-affected situations, demonstrate how the Unintended Consequences Knowability Classification Schema supports reflexivity, ethical accountability and inclusive learning. While inherently subjective judgements remain, the schema strengthens transparency and evaluative reasoning around what could or should have been known, and by whom. Further field testing is encouraged to refine its use in diverse contexts.
Source: Evaluation
Authors: Angus Alexander Davidson, John Leake, Patrick O’Connor
Institution: The University of Adelaide
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,650
OpenAlex ID: W7115013239