“Humans and records are entangled”: empathic engagement and emotional response in archivists
Bibliographic record
Abstract
There is growing awareness in archival communities that working with records that contain evidence of human pain and suffering can result in unsettling emotions for archivists. One important finding of this work, however, is the considerable variability in not only the nature of responses, but also the nature of records that provoke emotional responses. Using in-depth qualitative interviews with 20 archivists from across Canada and one from the United States, and employing grounded theory methodology, this study sought to better understand the nature of emotional responses and factors associated with distress. Archivists described a wide range of reactions including shock, intrusive thoughts, profound senses of anger, sadness and despair, and ultimately at times disrupted functioning in personal and occupational spheres. One factor that has been associated with increasing vulnerability to distress in other occupational groups is empathic engagement, which is understood to have two elements: a vicarious emotional process and a cognitive process. This article explores the impact of personal connections and the nature of empathic engagement between archivists, donors, community researchers, and the records themselves on emotional response.
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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 | 0.024 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.025 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".