Cousins, J. B., & Chouinard, J. A. (Eds.). (2012). Participatory evaluation up close: An integration of research-based knowledge. IAP. Available in paperback (ISBN 978-1617358012)
Bibliographic record
Abstract
Th e past few decades have seen strong evidence of participatory approaches improving the relevance and use of program evaluations. In tandem, a plethora of participatory approaches, rationales, methods, and resources have emerged. Evaluators and novice theorists must weed through a sea of information that may be diverse, ambiguous, or contradicting. In this comprehensive review, editors Cousins and Chouinard take on the daunting task of presenting and synthesizing existing research about participatory evaluation. Th e result is Participatory Evaluation Up Close, an important contribution to practice and scholarship. In the fi rst section of the book, the authors lay out the foundations of participatory evaluation. Th ey outline the many types of collaborative inquiry and possible justifi cations for those approaches, and they defi ne the two primary streams of participatory evaluation (practical and transformative). Further, they elucidate several conceptual frameworks that are used to situate diff erent approaches and purposes of participatory evaluation, including the dimensions of form in collaborative inquiry (Cousins, 2003; Cousins & Whitmore, 1998) and a comprehensive framework of the nature, contextual conditions, and consequences of participatory evaluation. For the reader, this section borders on overwhelming; decades of important texts are synthesized in fewer than 35 pages. However, upon reading it a second time, the reader realizes how benefi cial this introduction is to the rest of their reading experience. Th e second section is where Cousins and Chouinard compile their impressive and all-inclusive summary table: a review and thematic analysis of 121 studies published about participatory evaluation from 1996 to 2011. Most studies originate in the United States or Canada, but span many sectors including education, health care, community development, and international development. Th e authors analyze the studies by the dimensions of form, by the types of consequences, and by theme. For me, the thematic analysis is the strongest part of the book. Th e authors discuss seven main themes: training leading to meaningful participation; relational processes and dimensions of voice; dealing with multidimensional contexts; evolution of evaluator identity, role, and “positionality”; stakeholder selection and consequences of participation; learning as a basis for practice and change; and
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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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.011 |
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".