Perceptions of Evaluation Capacity Building in the United States: A Descriptive Study of American Evaluation Association Members
Bibliographic record
Abstract
Abstract: This article offers a descriptive picture of American Evaluation Association (AEA) members’ attitudes and perceptions related to evaluation capacity building (ECB). For this study, we analyzed data that were originally collected in the spring of 2006 from 1,140 AEA members in the United States on evaluation use. The current study is an attempt to add to the ECB knowledge base by describing respondents’ views concerning (a) the importance of ECB as an evaluation approach, (b) the role of evaluators in undertaking ECB-related activities, (c) ECB-related factors that influence use, and (d) the extent to which evaluation activities foster organizational learning and change outcomes. Respondents are largely familiar with ECB and agree that building evaluation capacity is a role of the evaluator. Linkages between organizational learning and ECB were supported. Learning-focused organizational outcomes were rated more favourably than change-focused organizational outcomes.
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How this classification was reachedexpand
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 | 0.082 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".