Exploring the Current State of North American Graduate Archival Education1
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 analyzes 65 North American graduate archival education programs' course listings against current professional standards as crystallized in the 2016 Guidelines for a Graduate Program in Archival Studies (GPAS). The study addresses the following research questions: 1) What types of programs list graduate archival education courses?, 2) What types of courses do these graduate archival programs currently list?, 3) To what extent do archival programs' courses conform to GPAS?, and 4) What are the implications of a program's conforming or not conforming to GPAS? The authors' findings indicate an overriding tendency for graduate archival education programs to be hosted by LIS programs, especially under the auspices of iSchools. They identified a great diversity of graduate archival education programs and course listing combinations. Most important, they analyzed the archival curriculum coverage of 65 graduate archival programs to discern conformance with GPAS curriculum requirements. Although their findings may be used by programs for self-study, they also call into question the overall utility of GPAS and suggest the need for a more flexible approach.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
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 | 0.000 | 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 | 0.001 | 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