Do Evaluator and Program Practitioner Perspectives Converge in Collaborative Evaluation?
Bibliographic record
Abstract
Abstract: Interest in collaborative and participatory forms of evaluation — evaluation that involves evaluators working directly with nonevaluator program practitioners or stakeholders — has increased substantially in recent years. Yet research-based knowledge about such approaches remains limited. Moreover, empirical studies have focused almost exclusively on the perspectives of evaluators or, to a lesser extent, non-evaluator stakeholders associated with the program. This study examines in a direct comparative way the convergence of evaluator and non-evaluator perspectives about collaborative evaluation. Sixtyseven pairs of evaluators and program practitioners, members of which participated on a common collaborative evaluation project, completed a questionnaire about the evaluation and their opinions concerning collaborative evaluation. Relative to their evaluator counterparts, program practitioners indicated they were more involved in technical evaluation activities, were more conservative in their views about evaluation consequences, and tended to feel more positively about the collaborative experience. They agreed, however, about evaluator involvement and the range of stakeholder groups participating in the program. In general, program practitioner and evaluator views and opinions about collaborative evaluation converged, although some differences regarding who should participate and the power and potential of collaborative evaluation were noted. Typically, program practitioners were more conservative in their opinions. The results are discussed in terms of their support for the integration of evaluation into program planning and development.
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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 | 0.260 | 0.410 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.019 | 0.017 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.005 | 0.005 |
| 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".