Addressing the Challenges Encountered During a Developmental Evaluation: Implications for Evaluation Practice
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 describes three challenges encountered during a developmental evaluation and explains how these were addressed from the evaluators’ perspective. The evaluation was conducted to support the implementation of a three-year educational technology leadership project funded by the Alberta provincial government. The developmental evaluation responded to two purposes identified by the evaluation client: inform ongoing programmatic decisions and measure change in practice. The implications for evaluation practice related to the challenges of introducing a new evaluation approach, defining the boundaries of evaluator roles, and integrating technological resources are discussed and related to the Canadian Evaluator Competencies (Canadian Evaluation Society, 2010) and the Program Evaluation Standards (Yarborough, Shulha, Hopson, & Carruthers, 2011).
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 | 0.061 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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