Bibliographic record
Abstract
Archival research has been long recognized as a key method in geography, and such research continues to appeal to scholars excavating historical influences on contemporary places. At the same time, geographical literature on care is growing rapidly. However, while geographers have often implemented care into their archival research and practice, these literatures have remained largely distinct from each other. In this paper, I bring archives and care into closer conversation. Drawing on existing geographical literature on care and on archival methods, work in archival studies, and my own research and ethnographic experiences in archives, I show how the socio‐material practices of geographers in the archives help generate spaces of care, where ethical caring practices exist, and caring relationships flourish. I demonstrate how archival work in geography and beyond includes relationships of care between archivists, researchers, and archival records. I share some examples and strategies that geographers and other researchers can—and do—follow in maintaining, continuing, and repairing archival relationships, even in times of precarity and uncertainty.
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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 | 0.058 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.018 |
| Science and technology studies | 0.037 | 0.111 |
| Scholarly communication | 0.038 | 0.026 |
| Open science | 0.004 | 0.031 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".