Methodological Perspectives on Smuggling: The GDL-Prussia Borderlands in the Late Eighteenth Century
Bibliographic record
Abstract
In this article we explore the customs system of the Grand Duchy of Lithuania (GDL) along its border with Prussia in the late eighteenth century, using as primary sources four inspection reports submitted to the GDL’s Treasury Commission between 1788 and 1792. We focus primarily on the extent of smuggling practices, the state of the customs administration, and the amount of revenues collected from cross-border trade. Our research is an example of a spatial humanities project, and for this reason we are primarily interested in methodological questions. More specifically, we employ a mixed methods analytical framework that includes GIS mapping, qualitative spatial reasoning (QSR), and corpus linguistics to explore the borderlands of the GDL at multiple scales of analysis. We do so to illustrate how a mix of methods and tools can shed new light on the degree of control exerted by the GDL along its border with Prussia.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".