Bibliographic record
Abstract
Abstract There can be few historical figures who have made such a powerful impact on the popular imagination as the Roman emperor Caligula (died ad 41). Yet an accurate reconstruction of his life and reign largely eludes us. The problem lies not so much in the quantity of evidence available, but in its quality. For our information we are obliged to draw on ancient accounts that can be colourful and wonderfully entertaining but have a flexible notion of historical truth and often seem to border on fiction. The consequence is that there is hardly a detail that the modern historian can present without deep reservations about its reliability. This book approaches Caligula by presenting the reader with the raw material of the ancient sources. It provides over three hundred translated passages of texts, taken mainly from ancient writers, but also from coins and inscriptions. The translations are accompanied by extensive introductions and notes. These are tailored to the non-specialist, and intended to help such readers navigate material that is often contradictory, often downright incredible, and also place events and institutions in their historical contexts. The colourful and exotic incidents are still there, but presented in a context that will help the reader gain a more sophisticated understanding of how we try to reconstruct events of the past. This approach allows the reader to tackle head on the stark reality that what we read in our sources is not necessarily the truth.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".