Custodians of creativity: ethical archiving of artists’ digital records
Bibliographic record
Abstract
The digital age has dramatically reshaped archival practices, requiring novel approaches to preserve and provide access to born digital materials. The opportunities and challenges of the digital age are not only technical, but also ethical. This thesis explores the ethical archiving of artists’ digital records through a case study of the records of Scott Leroux, whose digital archive was entrusted to the University of Manitoba Archives and Special Collections (UMASC). Leroux’s extensive digital footprint, spanning many devices and social media platforms, presented distinct challenges and opportunities in archival work. Ethical considerations in digital preservation are paramount, particularly regarding the management of sensitive content and intellectual property rights. By implementing technical strategies alongside participatory appraisal and arrangement strategies, within a larger feminist ethics of care framework, the integrity and relevance of Leroux’s records are maintained. My study underscores the pivotal role of metadata in making digital records discoverable and usable. Comprehensive metadata was crucial in offering context and ensuring appropriate access to Scott Leroux’s artistic legacy. This thesis promotes the adoption of feminist and decolonial approaches to digital archiving, highlighting the importance of community engagement and radical empathy in archival work.
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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 | 0.034 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.038 | 0.062 |
| Scholarly communication | 0.023 | 0.011 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".