Developing the Program Evaluation Utility Standards: Scholarly Foundations and Collaborative Processes
Bibliographic record
Abstract
Abstract: Developing the third edition of the program evaluation utility standards required multilevel collaborations among task force members, members of the Joint Committee on Standards for Educational Evaluation, sponsoring organizations, and hundreds of involved stakeholders. The scholarship on evaluation use, influence, and collaboration was foundational for the utility standards and materials accompanying them and equally important for informing the processes guiding utility standards development. This article emphasizes the foundational role of this recent scholarship and the roles played by all who collaborated in planning and implementing the utility standards development processes.
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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 | 0.377 | 0.401 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.012 | 0.025 |
| Scholarly communication | 0.027 | 0.013 |
| Open science | 0.006 | 0.018 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".