“Always Follow the Money”: A Call to Investigate Financial Records
Bibliographic record
Abstract
Cet article fait un survol de la littrature sur les documents financiers et conclut qu'on a trs peu crit ce sujet.Remarquant qu'il y a au moins vingt ans l'Association of Canadian Archivists recommandait que des cours soient donns aux archivistes pour les sensibiliser ce genre de documents, l'auteure rclame que de la recherche soit faite sur les documents financiers et les documents d'institutions financires.L'article dcrit comment le nouveau UBC Centre for the Investigation of Financial Electronic Records (CiFER) vise mener de la recherche sur les docu ments financiers et les documents d'institutions financires.L'article soutient que de nouvelles tudes sur ce genre de documents permettront aux archivistes de mieux les prserver, tout en favorisant la mise en pratique de la thorie archivistique.De plus, ces tudes offriront aux archivistes une meilleure comprhension des facteurs qui contribuent la stabilit conomique et la stabilit des institutions financires, ce qui montrera comment les tudes en archivistique peuvent contribuer de faon pratique et pertinente au dveloppement de la socit.L'article prsente un nombre de projets de recherche du CiFER et montre comment ceux-ci contribueront notre connaissance, tout en mettant l'preuve la thorie.L'article termine en invitant les archivistes int resss participer au rseau de recherche du CiFER.ABSTRACT This article surveys the literature on financial records and finds that very little has been written on the subject.Noting that as much as twenty years ago the Association of Canadian Archivists called for course content that would increase archivists' awareness of these records, the author calls for research into financial records and the records of financial institutions.The article describes how the newly formed UBC Centre for the Investigation of Financial Electronic Records (CiFER) aims to conduct research on financial records and the records of financial institutions.The article argues that new studies on financial records and the records of financial institutions will both better prepare archivists to preserve these types of records and
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".