Toward a “Third Order” Archival Interface: Research Notes on Some Theoretical and Practical Implications of Visual Explorations in the Canadian Context of Financial Electronic Records
Bibliographic record
Abstract
Ce texte aborde les défis liés à l'abstraction et aux représentations des documents d'archives et participe au débat sur ce sujet qui existe dans la littérature scientifique par un certain nombre de ses contributions théoriques et pratiques.Présentant les résultats d'un projet de recherche multidisciplinaire visant la création d'un modèle de référence interactif de haut niveau portant sur le contexte canadien des documents d'archives financiers numériques, il avance un cadre théorique au sujet du contexte sociétal comme ontologie de domaine et il fournit une approche pour établir les frontières du contexte sociétal.Il s'inspire également de la théorie sur les systèmes d'information, en particulier sur la théorie des représentations, afin d'élaborer la théorie des documents d'archives comme représentations.Il poursuit en abordant des expériences visant à développer un prototype d'une représentation visuelle interactive d'une ontologie de domaine du contexte canadien des documents d'archives financiers numériques, suggérant que les représentations visuelles interactives qui combinent des caractéristiques des éditeurs et concepteurs d'ontologie avec des caractéristiques d'outils pour l'analyse visuelle peuvent fournir des bases solides pour des interfaces d'archives de « troisième ordre ».ABSTRACT This paper addresses challenges related to abstraction and representation of archival records and makes a number of theoretical and practical contributions to discussions in the archival literature on this topic.Reporting on an interdisciplinary research project aimed at creating a high-level interactive reference model of the Canadian context of financial electronic records, it contributes a framework for theorizing about societal context as a domain ontology and an approach to establishing the boundaries of societal context.It also draws upon information systems theory, in particular representation theory, to extend the theory of records as representations.It then moves on to discuss experiments in developing a prototype interactive visual representation of a domain ontology of the Canadian context of financial electronic
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.023 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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".