‘A tongue in every wound of Caesar’: Performing Julius Caesar behind Barbed Wire during the Second World War
Bibliographic record
Abstract
In a moving short story entitled ‘Internee Julius Caesar’, the Austrian journalist Carl Weiselberger writes about the impact of internment on detainees held in a Canadian prison camp during the Second World War. To counter the monotony of camp life — which includes the choice between attending yet another lecture about the history of the homing pigeon in the recreation lounge, or the use of the compress in natural healing in the dining room — the internees decide to play a theatrical guessing game which, with a veiled allusion to Franz Kafka, they call ‘Changing Identities’ ( Sichverwandeln ). 1 Two internees leave the room, while the rest assign well-known personae to them; on their return, each of the two internees is secretly told about the other’s identity, and the point of the exercise is that each has to try to uncover their own identity by interrogating the other, who also drops hints. The story recounts how the men, once they have all had their turn, draw into the game the inconspicuous and reluctant New Age internee No. 801, a man who believes in metempsychosis and is convinced that in an earlier life he was both a priest of the Astarte cult, and Julius Caesar. The men have deliberately decided to make No. 801 guess that he is indeed Julius Caesar. After several mistaken attempts — the Roman greeting of the raised arm, provided as a hint, does not mean that he is Mussolini — internee No. 801 finally guesses that he must be Julius Caesar. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.020 | 0.009 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".