The dark side of impact measurement: complexities and drawbacks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this study is to contribute to the discussion surrounding impact measurement on social enterprises (SEs). The findings provide a more nuanced perspective on tensions that often emerge from SEs journeys by presenting the complexities which social entrepreneurs and investors should be attentive to. Design/methodology/approach This research used grounded theory as the means to explore how stakeholders accomplish the requirements for impact measurement, overcoming the challenges that arise in the process. Through 18 semi-structured interviews, the authors develop a conceptual model to better understand how a practice that is often taken for granted might compromise SEs achievements and sustainability in the long term. Findings The proposed model uncovered an unintended consequence of impact measurement: mission drift. The requirements to assess the social impact raise expectations on different actors and create challenges that affect the true purpose of SEs, the delivery of their social mission. Practical implications This study contributes to research and practice. First, the authors develop a theoretical model for social entrepreneurs and social investors to shed light on the hidden consequences of impact measurement. Second, the authors strengthen the knowledge in the field by conducting a study on SEs outside the mainstream Western-centric context. Originality/value The authors enrich the literature by exploring the tensions related to impact measurement in SEs in the Global South and unravel new perspectives on the subject.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it