Keep Running Towards the Danger : The Transformative Potential of Archival Care
Bibliographic record
Abstract
This work is a lightly-edited transcript of a keynote presentation at the Archives Society of Alberta 2023 Biennial Conference, held in Edmonton, Alberta, May 25-27, 2023. The conference theme was Care for People in the Archives. The talk traces some of the development of discourses around care, trauma, grief and emotion in archives and archival work. It reflects on ten years of research on grief and recordkeeping and on changes to the reception of work of this type in the discipline and the profession. It also suggests ways that discourses of practicality alongside what Victoria Hoyle calls "authorized archival discourse" impede the potential for the kinds of transformative change many archival theorists and practitioners are calling for. Finally, it highlights the need for systemic change that is supported and enacted structurally and especially at leadership levels.
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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 | 0.026 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.033 | 0.102 |
| Scholarly communication | 0.036 | 0.019 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.010 | 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".