Bibliographic record
Abstract
This article examines the characteristics of archives (records) susceptible to modification by changes in context. After briefly defining the notion of context, the author proposes a complex analytical model, taking into account what archives are, what they do, and what they represent for their creators. By applying such a model to a traditional definition of archives, the author can identify the physical, functional, andsymbolic characteristics of archives and explore how they have been conditioned by contexts of recording, communication, and memory making. Résumé Le présent article examine les effets que peuvent avoir divers contextes sur les caractéristiques des documents d’archives. Après avoir brièvement défini la notionde contexte, l’auteure propose un modèle d’analyse complexe tenant simultanément compte de ce que les archives sont, de ce qu’elles font et de ce qu’elles représentent pour leurs producteurs. L’application d’un tel modèle sur la définition traditionnelledes archives permet à l’auteure d’identifier des caractéristiques physiques, fonctionnelles et symboliques de la production documentaire et de voir comment ces dernières sont plus ou moins conditionnées par des contextes de consignation, de communicationet de mémoire.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.359 | 0.095 |
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".