Theory-Practice Connections in Collaborative Approaches to Evaluation: A Systematic Review of Practice
Bibliographic record
Abstract
Collaborative approaches to evaluation (CAE) are evaluations where evaluators engage with program community members to coproduce evaluation knowledge. There has been much written about CAE theory and a plethora of empirical studies have been published. Yet little is known about the extent to which CAE practice corresponds with theory. This study is a systematic review of a set of 46 peer-reviewed studies of CAE practice published over the past 25 years. We draw from Cousins and Whitmore's descriptive theory of participatory evaluation to explore the extent to which and how the case examples reflect practical and transformative streams and how they map onto three fundamental process dimensions: control, diversity, and depth of participation. Results provide support for these descriptive theoretical propositions. We discuss their implications for the value and use of CAE evidence-based principles; ongoing research; CAE in government and international development sectors; and appreciation of reciprocal benefits.
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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 | 0.267 | 0.570 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.040 | 0.033 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.005 | 0.005 |
| 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 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".