World Views: Cartographers, Artisanship and Epistemology in Early Modern Italy
Bibliographic record
Abstract
Scholars have long since demonstrated that no such occupation as “cartographer” existed in early modern Europe. Instead, the skills needed to produce maps often combined those of manuscript illuminators, scribes, mathematicians, letterpress operators, and engravers - to name only a few. Though it is common to speak of maps as offering insight into “world views,” we often assume these to be those of patrons and viewers rather than of the craftspeople who produced them. These artisans relied upon a host of tools, skills, and materials which varied tremendously from city to city even within discrete geographic regions. Moreover, though many early modern maps were only marginally related to the practical activity of way-Dinding, those who labored to create them were often themselves itinerant artisans moving across the Alps and beyond. In this essay, I chart the training, experiences, and know-how of the engineers, printers, painters, and woodworkers who made maps. I explore the ways in which the trans-national and often multilingual social-lives of these makers informed the material fabric of their maps and, in turn, shed light upon the sometimes unexpected interpenetration of biography, world view, and object that characterizes cartographic cultures between the Difteenth and seventeenth centuries. My approach thus seeks to bridge recent insights on the “artisanal epistemology” of makers with a critical approach to the agency of objects, informed both by anthropological theory and a renewed focus on materiality which has come to characterize studies of visual culture.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.009 | 0.044 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".