Alain Blum, Marta Craveri, and Valérie Nivelon, eds. Déportés en URSS: Récits d’Européens au goulag. Paris: Éditions Autrement, 2012
Bibliographic record
Abstract
This collection brings together the accounts of Europeans deported to the Soviet Gulag, understood both as labor camps and forced relocation settlements. It is the result of a wonderful multimedia project that draws on the expertise of a dozen scholars from eight countries. Thanks to their work, we have the testimony of more than 160 individuals who were victims of the Soviet practice of forced deportation from 1939 to 1950. The project is multimedia in that it stems from a Radio France Internationale series that presented the interviews of deportees and an outstanding website. The latter allows the general public to trace the experience of deportees with the help of excerpts from filmed interviews, personal papers like photographs and diaries, as well as maps and official documents. This allows viewers to appreciate the individual experiences of deportees in their wider historical context. The volume under review is a companion to the radio series.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.006 |
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".