They’re Happy, but Did They Make a Difference? Applying Kirkpatrick’s Framework to the Evaluation of a National Leadership Program
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
Abstract: This article examines the Kirkpatrick evaluation framework through a case study of a national leadership development program. The authors introduce the program and the Kirkpatrick framework, and then describe the research processes and instruments through which the framework was applied to evaluate the pilot cohort of the program. The article concludes with several frank and practical insights about using the Kirkpatrick framework to evaluate non-credit educational programs. In areas such as leadership development education, Kirkpatrick offers an appealing framework for organizing an evaluation process. The framework enabled a productive formative evaluation process, and the demonstration of participant satisfaction and learning with the program was sufficient to facilitate the approval of funding for a second cohort. However, despite the investment of considerable resources, the evaluation of this program was not able to conclusively demonstrate that behaviour changes and resulting impacts on organizations and communities took place as a result of the program.
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 | 0.017 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it