Deep-water shipwrecks in the East Mediterranean: a microcosm of Late Roman exchange
Bibliographic record
Abstract
Deep-water shipwrecks provide an opportunity to investigate ships away from the destructive dynamics of coastlines and approaches to harbors where most ancient wrecks to date have been found. Such exploration expands the potential for finding wrecks of periods for which relatively few are known. One such period is the 6th and 7th c. in the E Mediterranean. Studies of cargo assemblages from the few known wrecks of the later Roman period reveal a partial picture of interlinked and overlapping trade networks that incorporated major and minor ports in the adjacent provinces.1 Various trading modes may be discerned, including cabotage, short-haul trade, inter-regional commerce, and private long-haul trade. Largely missing thus far are the wrecks of ships that participated in the annona transport, the “backbone of Late Roman shipping”.2 Each year, an enormous fleet of private ships under state contract hauled thousands of shiploads of Egyptian grain from Alexandria to Constantinople for public distribution,3 but no shipwrecks explicitly associated with these fleets have been found. Also largely invisible are the non-commercial transports associated with the annona militaris, the fiscal supply of foodstuffs destined for armies stationed on the empire‘s borders. The state supply-system became more formalized in 536 when Justinian created the quaestura exercitus, a prefecture that was granted administrative control and jurisdiction of Moesia Secunda, Scythia, Caria, the Aegean islands, and Cyprus.4 Evidence suggests that the quaestor‘s main task was to ensure the supply, by sea, of agricultural products from the Aegean and NE Mediterranean to troops on the Danube frontier.5 While no definitive grain ships have been found in the E Mediterranean — what M. McCormick has called the “annona paradox”6 —, shipwrecks with the larger cargoes expected of state supply have remained rather elusive.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".