Bibliographic record
Abstract
In 502 the Iranian king of kings Kawad (488–96, 498–531) personally marched a major field army into Roman Anatolia, dramatically bringing to a close a century and a quarter in which co-operation rather than conflict had characterized Roman–Iranian relations.1 Kawad found the strategic cities of Theodosiopolis and Amida woefully under-defended, as neither the reigning emperor Anastasios I nor his immediate predecessors had envisaged the return of major Iranian armies to Roman territories that had remained largely peaceful since the campaigns of Shapur II. Once Amida fell to Kawad’s siege engines, the Romans only managed to dislodge Iranian forces from their territory through submitting payments of 1,000 pounds of gold in 504. But this was merely the beginning of emphatically hostile relations between the Roman and Iranian empires. Again in 530 and 540 the kings of kings Kawad and Husraw I (531–79) led major campaigns into Roman territory and departed only after the submission of payments in gold, amid unrelenting contestation of the frontier zones between the two empires that continued into the early seventh century. A century of almost continuous warfare followed immediately and suddenly upon an era of rarely interrupted peace. It is the goal of the present article to explain how Iranian campaigns against Rome facilitated the unprecedented expansion of the institutions of empire both within and beyond Iran’s frontiers that took place in the sixth century. Internally, fiscal and military reforms enabled the kings of kings more reliably to extract resources from the provinces, to supervise officials and to field armies.2 The provincial aristocracies of Iberia, Armenia and Albania as well as Iran’s Arab clients, the Lakhmid dynasty, were increasingly subject to imperial oversight and contributed to the extension of Iranian rule deeper into the Caucasus and the Arabian Peninsula.3 Externally, Kawad secured a stable relationship with the Hephthalite Hun kingdom that had hitherto humbled Iran, and his successor, Husraw I, in league with the Turk qaghan, finally reconquered Bactria in 560.4 And the campaigns against the Roman empire continued throughout the century, culminating in the ‘last great war of antiquity’ between 602 and 625, when the Iranians gained and lost the Roman Middle East and briefly extended their authority from the Nile to the Oxus.5
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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".