L'abandon du fonds comme premier niveau de classification et de classement pour les documents du gouvernement ontarien: une solution moderne à un problème complexe
Bibliographic record
Abstract
Dans ce texte de Bob Krawczyk, traduit par Helene Bernier, l'auteur fait etat des reflexions qui ont amene les Archives publiques de l'Ontario a aborder d'une facon toute particuliere la classification et le classement des archives gouvernementales. Il demontre a l'aide d'exemples concrets et de nombreux tableaux que la constitution de fonds d'archives distincts pour les documents des administrations a structure organisationnelle complexe ne serait pas le meilleur moyen d'assurer le respect du principe de provenance. En raison des difficultes d'appliquer les criteres generalement reconnus permettant l'identification des organismes producteurs de fonds, les Archives publiques de l'Ontario ont mis en place un systeme dans lequel la serie est utilisee comme premier niveau de classification et de classement. Inspire du systeme en usage aux Archives nationales d'Australie, cette methode est fondee sur le principe que l'information concernant les documents et l'information relative aux createurs doivent etre maintenues separement et reunies au besoin pour fournir le contexte de creation des documents.
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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 | 0.016 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".