Le numérique et la ruine de l'authenticité archivistique : des données au document numérique composite, l'impensé quant à la préservation de l'écrit numérique
Bibliographic record
Abstract
Alors même que la fixité informationnelle se voit menacée par le présentisme informatique, l’abandon et la confusion des registres au profit des bases de données opérationnelles ainsi que le désintérêt des archivistes dans la gestion documentaire des organisations au profit d’un regard sur la valeur secondaire des archives constitue un frein à l’adaptation inévitable du concept de fixité à l’aune de la matérialité numérique de l’écrit, vers un retour à l’acte d’enregistrement. Nous donnons à voir dans cet article le bouleversement critique opéré par le numérique sur l'authenticité des archives et offrons des pistes pour redonner à l’archive son rôle supposé d’outil de décontextualisation de la confiance.
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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 | 0.014 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.025 | 0.025 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".