Bibliographic record
Abstract
ABSTRACT Helen Samuels sought to document institutions in society by adding to official archives counterweights of private records and archivist-created records such as oral histories. In this way, she recognized and sought to mitigate biases that arise from institution-centric application of archival functionalism. Samuels's thinking emerged from a late-twentieth-century consensus on the social license for archival appraisal, which formed around the work of West German archivist Hans Booms, who wrote, “If there is indeed anything or anyone qualified to lend legitimacy to archival appraisal, it is society itself.” Today, archivists require renewed social license in light of acknowledgment that North American governments and institutions sought to open lands for settlement and for exploitation of natural resources by removing or eliminating Indigenous peoples. Can a society be said to “lend legitimacy” to archival appraisal when it has grossly violated human, civil, and Indigenous rights? Starting from the question of how to create an adequate archives of Canada's Indigenous residential school system, the author locates Samuels's work amid other late-twentieth-century work on appraisal and asks how far her thinking can take us in pursuit of archival decolonization.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.035 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".