Understanding Evaluation Policy and Organizational Capacity for Evaluation: An Interview Study
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
Evaluation policy has been identified as an important means of shaping and influencing organizational evaluation practice, yet, to date, little empirical research has been conducted to deepen our understanding of this relationship. The purpose of this study was to illuminate evaluation policy’s role in leveraging organizational capacity to do and use evaluation. We interviewed 18 published evaluation scholars and practitioners from North America and Europe about this topic. A thematic analysis of findings underscores the importance of context, policy attributes, enablers, and organizational benefits. Based on the findings, we developed an ecological conceptual framework to guide thinking about the role of evaluation policy in capacity building. We discuss these findings in terms of practical implications of understanding context, redressing the imbalance between learning and accountability purposes of evaluation, and organizational leadership, and we conclude with some implications for research.
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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 | 0.071 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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