Stalin’s Daughter by Rosemary Sullivan. An Interview on Memory
Bibliographic record
Abstract
This article deals with Canadian biographer Rosemary Sullivan, one of the most important voices in Canadian literature. Stalin’s Daughter (2015) is a biography of the woman who tried to free herself from the terrible weight of being the daughter of a dictator. Memory is an essential element in Svetlana Stalin’s life, as in all those who knew her. In a sustained effort to understand Svetlana, Sullivan explored archives (including the KGB), travelled to the places where Svetlana had lived, asked questions of those who had met her. She reconstructed the life of Svetlana in a passionate and deeply researched biography. The article contains Sullivan’s answers to questions asked during a skype interview.Stalin’s Daughter di Rosemary Sullivan: un’intervista sulla memoriaL’articolo si riferisce alla canadese Rosemary Sullivan, una delle voci più importanti in Canada. La figlia di Stalin (2015) è la biografia di una donna che cercò di liberarsi da un peso terribile: essere la figlia del dittatore Stalin. La memoria è elemento fondamentale nella vita di Svetlana Stalin e nel libro. Sullivan, in un tentativo, riuscito, di capire la vera Svetlana, ha lavorato negli archivi (anche del KGB), è andata nei luoghi dove visse Svetlana, ha interrogato chi l’aveva conosciuta. Sullivan ha ricostruito la vita di Svetlana Stalin, una biografia appassionante e altamente documentata. L’articolo pubblica inoltre alcune risposte di Rosemary Sullivan a domande poste via skype.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".