A Mathematical Borderscape in Eratosthenes’ Geographika: North-South Distances of the Oikoumene
Bibliographic record
Abstract
In the Hellenistic world, landscapes were often tied to the borders of kingship. This paper challenges the prevailing geopolitical framework by showing that Eratosthenes defined the oikoumene not by shifting imperial frontiers, but through a mathematical conception of its outermost edges. It examines how his Geographika constructs a borderscape shaped by intellectual inquiry and mathematical precision, drawing on geographical evidence through textual analysis, empirical observation, and scientific reasoning. His engagement with mathematics moved his research beyond the Library of Alexandria into the natural world. This interplay reveals an alternative mode of boundary-making: one rooted in scientific inquiry. To examine these borderscapes, this study employs GIS to reconstruct Eratosthenes’ spatial framework, focusing on the southern connections between the Near East and North Africa to show how boundaries and landscapes were theorised in the Hellenistic world.
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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 | 0.003 |
| 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 | 0.024 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".