Evaluation policy and organizational evaluation capacity building: A study of international aid agency evaluation policies
Bibliographic record
Abstract
Abstract Research and theory on evaluation capacity building (ECB) and organizational evaluation capacity have been developing at a good pace over the past decade. On the other hand, there is a paucity of research on the nature and consequences of organizational evaluation policy. Evaluation policies are developed and implemented ultimately to inform and shape evaluation practice and its consequences. It is therefore natural to consider the interface between evaluation policy and ECB. The present exploratory descriptive study examines 52 evaluation policies from bilateral and multilateral aid agencies to explore connections between evaluation policy content and ECB principles and considerations. The results shed light on some interesting relationships; they are discussed in terms of evaluation use, evaluation purposes, and organizational leadership. The study also resulted in a revision of Trochim's (2009) definition of evaluation policy and a refinement and expansion of his eight‐category taxonomy. Implications for ongoing inquiry are considered and practical implications are offered to organization members and evaluation policy developers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.083 | 0.154 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".