The Natures of Maps: Cartographic Constructions of the Natural World
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
Editor's Note We are pleased to introduce a new section in Cartographica devoted to a series of invited critiques and commentary on a target article. For the inaugural contribution, we have chosen to examine chapter 1 of a new book by Denis Wood and John Fels, The Natures of Maps (University of Chicago Press, 2008). Responses to this piece have been provided by Chris Perkins (University of Manchester, UK), Gwilym Eades (McGill University, Montreal, Canada), and Rob Kitchin (National University of Ireland, Maynooth). Wood and Fels then offer a short reply. Note that, for reasons of space and of clarity, some notes have been modified in the version provided here, and the colour figures that appear in the book have been omitted. Except in quoted material, US spellings have been replaced by Canadian spellings. (Jeremy W. Crampton)
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it