Secrets, Lies and History: Experiences of a Canadian Archivist in Hungary and South Africa
Bibliographic record
Abstract
Cet article est à la fois un examen de l'interne de dépôts d'archives privés d'Europe de l'Est et d'Afrique du Sud ainsi qu'une analyse du rôle critique des dépôts d'archives et des musées comme gardiens de la mémoire collective.Les expériences de l'auteure comme archiviste en audio-visuel, d'abord à Budapest, où elle a travaillé à la Open Society Archives créée par George Soros, et au Mayibuye Centre du Cap, fournissent une fenêtre unique sur des collections archivistiques hautement subversives et qui documentent les activités de deux régimes parmi les plus répressifs du XX e siècle.Les contrastes et parallèles dans l'histoire récente de la Hongrie communiste et de l'Apartheid en Afrique du Sud offrent des exemples convaincants de la façon dont les histoires nationales sont modelées et contrôlées par les pouvoirs dominants.En vue de montrer leur nouvelle image de sociétés libérées, les historiens de ces deux pays doivent ré-examiner les documents du passé : parmi ceux-ci se trouvent des secrets bien gardés qui ont été soustraits à la connaissance du public ainsi que les mythes et mensonges qui ont été gravés dans la mémoire du public à coup de fréquentes répétitions.ABSTRACT "Secrets, Lies and History: Experiences of a Canadian Archivist in Hungary and South Africa" is both an inside view of privately funded archival repositories in Eastern Europe and South Africa and an analysis of the critical role of archives and museums as the keepers of public memory.The experiences of the author as an audiovisual archivist, first in Budapest, where she worked at the Open Society Archives founded by George Soros, and then at Cape Town's Mayibuye Centre, provide a unique window on formerly subversive archival collections documenting the activities of two of the most repressive regimes of the twentieth century.The contrasts and parallels in the recent histories of Communist Hungary and Apartheid South Africa offer striking examples of how national histories are shaped and controlled by dominant powers.In order to reflect their new image as liberated societies, historians in both countries are faced with the task of re-examining the records of the past: the well-kept secrets that were withheld from public knowledge and the myths and lies that were fixed in public memory through frequent repetition.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.056 | 0.018 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".