Distinctive Visual and Toponymic Characteristics of Adriatic Sea Island Representations in Early Modern Cartography
Bibliographic record
Abstract
The research addresses the representation of selected Adriatic islands, subcategorised with respect to their size, on early modern nautical charts and geographical maps employing two concurrent approaches. The first approach inspects their positioning relative to one another and in absolute terms, and their visual appearance. Particular emphasis was placed on their dimensions in relation to a modern map, which were quantified utilising the Local Map Scale Index (LMSI). The second approach focuses on the toponymical content, and examines their distribution and varieties, including some notable aspects of naming certain islands. The findings indicate that small remote islands such as Palagruža and Pianosa were rendered as the most exaggerated, presumably due to their significance for terrestrial navigation, and that early modern geographical maps depicted islands larger than contemporary printed nautical charts. Research has established that most of the islands on old maps were designated by Venetian names rather than by the names used by their inhabitants, reflecting the influence of Venice as the dominant political and economic power in the Adriatic. In this process, greater emphasis was placed on naming the more important islands of the outer chain and the offshore islands relevant to maritime navigation, regardless of their size. Although the nature of these phenomenologically distinct map elements hinders the establishment of a convincing quantitative correlation and causal relationship between their manifestation and distribution, they are complementary as they collectively improve spatial orientation and reflect historical geographical understanding during the examined period. Consequently, the study aims to introduce a novel cartometric and analytical methodology to enhance the present understanding of island representations on early modern charts and maps overall.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".