Counter-Mapping Maroon Cartographies
Bibliographic record
Abstract
Formal spatial modeling and analytical approaches to maroon settlement, fugitivity, and warfare in the colonial-era Caribbean have tended to mine historical cartographic sources instrumentally to analyze the distributions and simulate processes driving marronage in St. Croix (Dunnavant 2021b; Ejstrud 2008; Norton and Espenshade, 2007). Through close-in analysis, we compare two Danish maps of St. Croix produced in 1750 and 1799 in relation to modern cartographic sources, to explore how cartographic forms and cartesian conventions (attempt to) elide blind spots in the colonial gaze. By modeling possible subject-oriented maroon movement on georeferenced colonial maps and contemporary LiDAR, we demonstrate how GIS can recover anti-colonial agency. Additionally, the practice of georeferencing itself is a critical site of analysis, revealing distortions suggestive of social and environmental conditions that limited colonial cartographers’ ability to map certain wilderness and contested landscapes that lay outside of their control.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".