Bibliographic record
Abstract
A major focus of cartographic research can be framed within two broad trends involving geovisual analytic and critical cartographic approaches. Understated in the development both of scientific and critical approaches to the field of cartography has been the role of cartographic inference. Making inferences from maps is fundamental to the visual analytical tradition and the thinking/communication continuum. Reasoning is also fundamental to critical cartography and the development of critiques relies on inference based on “evidence” encoded or inscribed in a map or set of maps. The social construction of a map and the map’s use have a significant impact on the types of inferences that are made, but conclusions must be carefully scrutinized with respect to these inferences. This study examines the Piercean notions of abductive, deductive, and inductive inference and their application to cartographic inquiry from both scientific and critical perspectives. A study of John Snow’s famous map of a cholera outbreak in London shows the evolution of this map from an instrument of scientific inquiry to one of historical discourse. This historical discourse also shows the continuous unfolding of “Snow’s map” as a mapping practice. By understanding how logical inferences change over time as the context of a map within society changes, this study shows biases inherent within cartographic expression integral to both scientific and critical lines of inquiry.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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".