Dissociation and Loss: a Challenge for Sustainable and Inclusive Conservation
Bibliographic record
Abstract
The agents of deterioration (AoD) offer a structured categorization of hazards to collections: they are a basis for risk-informed preservation management. In drawing up the AoD their creators were not ignorant of wider societal issues of concern to conservators, but they envisaged them to be part of a broader institutional activity located beyond the scope of preventive conservation. Within conservation, there have been discussions about additional agents: social, cultural, or political causes of loss. Their continued exclusion from the AoD may mistakenly be interpreted as a lack of consideration of such concerns. There are reasons to limit the scope of an institution’s preventive conservation system but not everyone agrees that those reasons are sufficient to justify this limitation. This paper is a discussion and disagreement by two authors. Henderson argues that dissociation should capture any loss of meaning resulting from any aspect of conservation practice, including cleaning, documentation, failure to respect beliefs, etc. She argues that dissociation from context may stop preventive conservators from identifying and respecting optimal traditional sustainable methods and techniques. Waller argues that the threat of losing context information about collection items should be managed as part of the wider cultural heritage institution’s role and resolved through its engagement with the community. He acknowledges that preventive conservation can contribute to understanding and mitigating this form of loss, but advocates that primary responsibility must be situated at a higher level than the preventive conservation remit.
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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 | 0.037 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.190 |
| Scholarly communication | 0.034 | 0.050 |
| Open science | 0.006 | 0.051 |
| Research integrity | 0.010 | 0.025 |
| Insufficient payload (model declined to judge) | 0.007 | 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".