The Development, Testing, and Evaluation of the Archival Metrics Toolkits
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
This paper reports on the Archival Metrics Project, which developed, tested, and evaluated a set of toolkits designed to overcome some of the challenges of conducting user-based evaluation in college and university archival repositories. The Archival Metrics Project is ongoing. The initial toolkits result from a five-year, two-phase project funded by the Andrew W. Mellon Foundation. The project involved academics from three North American universities and twenty partners from academic archival institutions. At the completion of the study, the researchers interviewed ten archivists at partner institutions who took part in the testing of the toolkits and one year later gathered data using a questionnaire from fifty-nine individuals who downloaded the toolkits. The paper describes previous research on user-based evaluation in archives and similar projects conducted in the library field, the process of developing and testing five questionnaires and various methods to administer the questionnaires, as well as ...
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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