GIS and Geographic Governance: Reconstructing the Choropleth Map
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper takes up the challenge of "reconstructing gis" by examining gis and governmental rationality. As an aspect of government, mapping is a vital source of geographic knowledge that informs political decision-making. Of particular importance to geographic governance and management are population distributions such as health, wealth, education, density, or criminality. Yet how these distributions have been mapped has shifted and been contested historically. Whereas in the early nineteenth century populations merely filled in pre-existing political areas, by the early twentieth century populations were understood as themselves defining areas and boundaries. Today, gis has returned to the earlier unproblematic politics of space. I explain these shifts by identifying similar shifts between the choropleth and the dasymetric map. Although commonly used, the choropleth is inadequate and misleading. I discuss the possible reasons for these shifts by re-emphasizing mapping as an aspect of geographic governance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 it