Bibliographic record
Abstract
Unedited and raw time-based media—dailies, rushes, scratches, original or source footage, B-roll, and more—go by different names depending on the context of creation. This article examines the collecting, preservation, and access practices of raw, unedited, and auxiliary media through the lens of initial findings of a scoping review underway by the authors. Exploring the literature and incorporating post-custodial and media archeology frameworks expanded the authors’ research design to embrace the potential of access, reuse, and reactivation of materials as means of remediation. This paper discusses the potential raw, unedited, and auxiliary media pose for galleries, libraries, archives, and museums, as well as broader communities, and it encourages readers to embrace relationships with raw and unedited media, reuse, and resistance by way of community and artistic intervention. [This article is an expansion of a presentation given at the International Association of Sound and Audiovisual Archives (IASA) conference, held virtually in September 2021.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.026 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.002 | 0.002 |
| 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".