Dan Healey <i>The Gulag Doctors: Life, Death, and Medicine in Stalin’s Labour Camps</i>
Bibliographic record
Abstract
Dan Healey's well-researched Gulag Doctors is a crucially important contribution to the history of the Gulag and to the history of medicine within coercive institutions. Healey situates his discussion as a counterpoint to Aleksandr Solzhenitsyn's generalization that Gulag medicine was part of the dehumanizing process leading to mass death. Instead, Healey focuses on individual personnel to highlight Gulag medicine as a “grey zone” (p. 33) in which some doctors and medical staff did their best to help prisoners, others sought to advance their careers, and still others tried just to do their jobs and maintain a low profile. As he notes in his conclusion, “The Gulag hospital could be a place of healing, compassion, and learning, while often simultaneously a portal to death after penal malnutrition, exhaustion, and systemic neglect” (p. 256). In sum, Healey examines the very human responses to working (sometimes by choice, sometimes not) within a very inhumane system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".