On ‘Holding the Process’: Paying Attention to the Relations Side of Donor Relations
Bibliographic record
Abstract
This article reports on a series of interviews with archivists and recordkeepers conducted as part of a larger project exploring relationships between grief and recordkeeping. Though the interviews were not explicitly focused on donor relations, it emerged that the relationship between archivists and donors was a particularly emotionally charged one: interview participants described deep and complex relationships with donors, whom they often knew over a long period and through difficult or complicated times. Interview participants also reported feeling unprepared for this emotional work. This article responds to a perceived lack of attention paid to donor relations in archival theory and education by acknowledging the significance of donor stories, feelings and relationships. Aligned with the ever-growing emphasis in archival theory and praxis on person-centered approaches, the article suggests where such approaches are needed in relation to archival education and training, the collection and preservation of donor stories, relationship-building, and recognition of different kinds of archival labor.
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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 | 0.055 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.030 | 0.088 |
| Scholarly communication | 0.027 | 0.036 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.008 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 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".