Landscapes of (dis)connection: Modelling connectivity in west Samos with least cost path analysis
Bibliographic record
Abstract
• Least cost path analysis suggests most efficient terrestrial routes in west Samos. • LCP results are calibrated against ethnographic and archaeological data. • Rivers and seasonal waterways are the key connection points in west Samos. • Anisotropic modelling estimates travel times along the least cost paths. • Results emphasise terrestrial routes’ role in supplementing maritime connectivity. This study explores connectivity in west Samos, an island whose landscape was defined by steep topography and which was largely inaccessibly by sea in the winter months. The first part of this paper reviews bibliographic, cartographic, ethnographic and archaeological evidence for terrestrial connectivity, while the second applies least cost path analysis to investigate possible routes between five key sites in southwest Samos to five key sites in the northwest. The GIS-rendered routes are compared to the field data to further explore the finer details of pathfinding and environment. All data types indicate the importance of route-making along two major river courses, the Megalo Rema and the Fourniotiko. Early Modern travelogues, ethnographic interviews, and maps all highlight the importance of seasonal waterways for cutting through areas of steep slope gradient. Both in exploratory hikes taken by the author and in GIS modelling, the Megalo Rema is deemed to be the more effective waterway for connecting south to north, while the construction of the island’s modern road network largely deviates from the calculated least cost routes. Anisotropic modelling is also employed to estimate travel times along the least cost paths. It is suggested that a return journey by foot or donkey is possible between the two sides of the island in one day, but that travel by loaded cart would have been impractical in most situations. These findings contribute to broader debates on island connectivity in the Aegean, emphasising the role of terrestrial pathways in supplementing maritime networks.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".