Two Perspectives on the Same Source: An Examination of Federal Deportation Case\t\t\t\tFiles
Bibliographic record
Abstract
This article investigates the appraisal and use of deportation case files from the perspective of an archivist as well as an historian. The author outlines her experiences in both capacities -- as an archivist with the Library and Archives Canada and later on as a Ph.D. student in history -- in order to demonstrate how her perception of this source changed dramatically after she switched from one role to the other. In addition to outlining the re-appraisal work she undertook with these records at the NAC as well as the research involved in her dissertation, the article suggests some possible solutions as to how the different priorities and needs associated with these two groups might be resolved in the future, without threatening the independence required by archivists when undertaking appraisal and re-appraisal initiatives.RÉSUMÉCet article examine l’évaluation et l’utilisation des dossiers individuels de déportation, du point de vue de l’archiviste aussi bien que de l’historien. L’auteure expose les grandes lignes de ses deux expériences, comme archiviste à la Bibliothèque et Archives Canada et plus tard comme étudiante de doctorat en histoire, afin de montrer comment sa perception de la source a changé énormément en passant d’un rôle à l’autre. En plus de décrire le travail de ré-évaluation de ces dossiers qu’elle a fait aux BAC, de même que la recherche entreprise au cours de son doctorat, l’auteure suggère quelques solutions pour résoudre les problèmes posés par les priorités et les besoins différents des archivistes et des chercheurs, sans pour autant menacer l’indépendance requise par les archivistes pour mener à bien leur travail d’évaluation et de ré-évaluation.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".