Mapping Evaluation Use: A Scoping Review of Extant Literature (2005–2022)
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
Factors influencing evaluation use has been a primary concern for evaluators. However, little is known about the current conceptualizations of evaluation use including what counts as use, what efforts encourage use, and how to measure use. This article identifies enablers and constraints to evaluation use based on a scoping review of literature published since 2009 ( n = 47). A fulsome examination to map factors influencing evaluation use identified in extant literature informs further study and captures its evolution over time. Five factors were identified that influence evaluation use: (1) resources; (2) stakeholder characteristics; (3) evaluation characteristics; (4) social and political environment; and (5) evaluators characteristics. Also examined is a synthesis of practical and theoretical implications as well as implications for future research. Importantly, our work builds upon two previous and impactful scoping reviews to provide a contemporary assessment of the factors influencing evaluation use and inform consequential evaluator practice.
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 | 0.082 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it