Learning to Think Archivally: Thesis Research in the Archival Studies Program at the University of Manitoba
Bibliographic record
Abstract
This article outlines the role of the thesis in the approach to archival education of the master’s program in archival studies at the University of Manitoba. The article discusses the role of the thesis in educating students to think archivally, or to enable them to identify significant work problems, conceptualize their issues, research the relevant sources, analyze and assemble the resulting information, and share it with others. The author maintains that this research ability is vital in the increasingly complex archival workplace of the twenty-first century.RÉSUMÉCet article décrit le rôle des thèses dans l’enseignement de l’archivistique au sein du programme de maîtrise en études archivistiques de l’Université du Manitoba. L’auteur soutient que les thèses jouent un rôle important en apprenant aux étudiants à penser de façon archivistique ou en leur permettant d’identifier les problèmes significatifs, à conceptualiser leurs questions, à faire des recherches dans les sources appropriées, à analyser et rassembler les informations pertinentes et à partager les résultats avec les autres. Il fait valoir que cette capacité de recherche est vitale dans le monde de travail de plus en plus complexe des archivistes en ce XXIe siècle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.022 | 0.008 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".