Bibliographic record
Abstract
The relationship between historians and archives is generally taken for granted. But this impression is misleading. Across the world, the building of archival collections involves a complicated process of selection and destruction. Traditionally, historians do not really know how this process is being conducted and very often a good proportion of them believe that all documents should be kept. The evolution of history and the questioning of the archives by philosophers cannot be ignored and these have changed the relationship between historians and archives. However, the construction of tomorrow’s archives is happening right now, and historians should be prepared to find a way to participate in this operation. The role of archivists is central in the whole process. In the past, archivists generally received a basic training as historians, but since the 1950s, they have been more and more involved with other disciplines like library or information sciences. They became professionals in a new discipline. Historians should take notice of this reality and be prepared to work with archivists on an equal footing. They must learn what archivists are doing and join them to help create archival collections for the future. The last part of the paper takes a quick looks at the evolution of the Internet as an addition, or rather than as an extension, of archival holdings.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".