Records in contexts : vers un nouveau niveau dans la description archivistique ?
Bibliographic record
Abstract
Cet article se concentre sur les grands courants de pensée de la profession des archivistes qui ont amené le Conseil international des archives (ICA) à s’orienter vers une amélioration de ses quatre normes descriptives. L’auteur passe en revue les manifestations de la provenance, de l’ordre original et des approches basées sur le fonds, en indiquant de nombreuses positions exprimées dans la littérature professionnelle. La deuxième partie offre quelques aperçus du nouveau modèle conceptuel proposé par l’ICA pour la description archivistique, appeléRecords in Contexts(Note du traducteur : les travaux à ce sujet s’étant effectués en anglais et le projet étant encore en consultation auprès de la communauté archivistique, il n’y a pas de traduction officielle du concept « Records in Contexts ». On a maintenu le terme anglophone qui équivaut à « Documents en contextes »).
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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.008 | 0.055 |
| Scholarly communication | 0.021 | 0.031 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 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".