Bibliographic record
Abstract
Between archives, as documentary by-products of human activity retained for their long-term value, and the archive, as a concept used outside of the discourse of professional archivists, there is a semantic, conceptual, and theoretical gap. However, this interval is particularly fertile. In this space, non-traditional archives users such as found-footage filmmakers find inspiration. Through the narratives of their work, they show what is not always visible in archives. Their artworks confront us with unarchived and unarchivable dimensions (what is not archived and what cannot be archived), constituent of how archives are created. In studying the archives that are part of found-footage works through an archival usage framework (exploitation), three main cat- egories of the unarchived and the unarchivable emerge: absence, which is linked to gaps, fragments, and incompleteness; the forbidden, which manifests in archives as material traces; and the invisible, which is not shown. These three categories have to do with an unconceived (impensé) state – a state of the archival field reflecting the intentional or unintentional inconceivability or omission of some of its theoretical or practical aspects. By investing in the unconceived – in other words, by studying archival science from practices on the margins – it is possible to renew ideas and discourses inside the discipline.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.030 |
| Scholarly communication | 0.027 | 0.040 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.024 | 0.008 |
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".