El cuadro de clasificación integrado: normalización de la clasificación archivística
Bibliographic record
Abstract
La normalización de la descripción archivística se ha visto frenada por el enfoque que hasta ahora se había dado a los tres elementos de toda clasificación documental (orgánico, funcional y temático) como criterios contrapuestos entre sí para el diseño de estructuras clasificatorias. Frente a todo ello se propone un modelo integrador, que suma siempre los tres elementos: el temático o por materias, el orgánico como desvelador del principio de procedencia, y el funcional, que se define de nuevo tratando de sortear la desorientación semántica en la que estaba sumido, para evitar confundirlo con cualquierade los otros dos elementos. Se ofrece así un cuadro de clasificación flexible, de fácil uso y aplicable a cualquier fondo de Archivos centrales e intermedios.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.004 | 0.053 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 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".