Understanding Dimensions of Organizational Evaluation Capacity
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
Organizational evaluation capacity building has been a topic of increasing interest in recent years. However, the actual dimensions of evaluation capacity have not been clearly articulated through empirical research. This study sought to address this gap by identifying the key dimensions of evaluation capacity in Canadian federal government organizations. The methodology used, based on Leithwood and Montgomery’s Innovation Profile approach, featured semistructured interviews with evaluation experts and a validating exercise conducted in four government organizations. The framework developed as a result of the study identifies six main dimensions of evaluation capacity (human resources, organizational resources, evaluation planning and activities, evaluation literacy, organizational decision making, and learning benefits), each one broken down into further subdimensions. The evaluation capacity of organizations on each of these dimensions and subdimensions can be described using four levels: low, developing, intermediate, and exemplary. The study found that government organizations vary in terms of their capacity from one dimension to the next, and indeed, from one subdimension to the next.
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 | 0.019 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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