Status identification on the road: requisitioning of travel resources by senators, equestrians, and centurions without diplomata. A note on the Sagalassus inscription (SEG XXVI, 1392)
Bibliographic record
Abstract
This article seeks to answer the question posed in a study which I\nundertook with Altay Coşkun (forthcoming in Latomus 2013) how high-ranking\nusers (senators, knights, and centurions) of the imperial information and\ntransportation system (most commonly known by its late antique name, cursus\npublicus) would prove their social class, military rank, and official nature of\ntheir journey in order to qualify for requisitioning at stations (mansiones,\nmutationes) without permits (diplomata). Using the results of this study as\nbasis, I offer a survey over the susceptibility of each of the classes of\nhigh-ranking users for status usurpation. This section is followed up by a discussion\nof the various ways in which identification was possible, including status\nsymbols (ornamenta), travel permissions (legatio libera, commeatus) as well as\nother written documentation (mandata, codicilli, army records). It will thus be\nshown that there were acceptably reliable mechanisms in place to prove one's\nsocial status. This result will further corroborate the findings of our\nprevious study that permits, in accordance with the edict of Sotidius Strabo\n(SEG XXVI, 1392 [20/37]), were not obligatory for certain status groups.\nPermits became a requirement for all users only in the reign of Claudius.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".