Review of the Book: Ch.J. Halperin. Ivan the Terrible: Free to Reward and Free to Punish
Bibliographic record
Abstract
In Ivan the Terrible: Free to Reward and Free to Punish, Charles Halperin brings together his many years of research, study, and reflection on Ivan IV, a ruler who presided over important and lasting reforms in Russia in the mid-sixteenth century and led the conquest of the Volga khanates of Kazan and Astrakhan. Ivan is known for much more, however, as his reign also involved large-scale, often savage attacks on his own subjects, carried out through the mechanism of the variously defined and understood oprichnina. Historians have been prolific in their work on this most (in)famous of Russian tsars. This book is an important addition to the voluminous and still growing historiography on Ivan. As much a study of Muscovite society, economy, politics, and culture in Ivan's time as of the tsar himself, it situates him firmly in the Muscovy that had evolved in the century leading to his accession to the throne, a century of expansion and profound change affecting all segments and aspects of society. For Halperin, the attendant and deepening social tensions and malaise provide the context for understanding Ivan as a complex ruler and human being who was challenged by his times and responsibilities. They also, as Halperin persuasively argues, help explain the complicity of so many Muscovites alongside the ruler in the unleashing of "mass terror", which, in this book, is seen not as the product of Ivan's sick mind or thirst for unlimited power, but as an expression of "social pathology" run rampant, beyond the intentions of a tsar whose actions prepared the soil for such violence.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".