Measuring Stakeholder Participation in Evaluation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Stakeholder participation is an important trend in the field of program evaluation. Although a few measurement instruments have been proposed, they either have not been empirically validated or do not cover the full content of the concept. OBJECTIVES: This study consists of a first empirical validation of a measurement instrument that fully covers the content of participation, namely the Participatory Evaluation Measurement Instrument (PEMI). It specifically examines (1) the intercoder reliability of scores derived by two research assistants on published evaluation cases; (2) the convergence between the scores of coders and those of key respondents (i.e., authors); and (3) the convergence between the authors' scores on the PEMI and the Evaluation Involvement Scale (EIS). SAMPLE: A purposive sample of 40 cases drawn from the evaluation literature was used to assess reliability. One author per case in this sample was then invited to participate in a survey; 25 fully usable questionnaires were received. MEASURES: Stakeholder participation was measured on nominal and ordinal scales. Cohen's κ, the intraclass correlation coefficient, and Spearman's ρ were used to assess reliability and convergence. RESULTS: Reliability results ranged from fair to excellent. Convergence between coders' and authors' scores ranged from poor to good. Scores derived from the PEMI and the EIS were moderately associated. CONCLUSIONS: Evidence from this study is strong in the case of intercoder reliability and ranges from weak to strong in the case of convergent validation. Globally, this suggests that the PEMI can produce scores that are both reliable and valid.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.104 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 0.003 |
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 it