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
For the past three decades Denis Wood has explored the \nnature and power of maps; how maps are designed, used, \nand understood, the role of maps in society; and \ncartographic theory more broadly. His collaboration \nwith John Fels, The Natures of Maps, furthers this project \nand seeks to detail both the nature of maps and the nature \nof maps. For Wood and Fels, ontological thinking \nabout cartography has been fixated on the nature of \nmaps. They illustrate this argument with reference to \nArthur Robinson and J.B. Harley, two cartographic \ntheorists with very different ideas about the ontology of \nmaps – maps as objective truths and maps as social \nconstructions. Wood and Fels argue that, despite their \ndifferences, Robinson and Harley both conceive of a map \nas having an inherent truth (they note that for Harley the \nmap itself remains ideologically neutral, with ideology \nbound to the subject of the map and not the map itself). \nWood and Fels reject this position to argue that the \nmap itself, its very make-up and construction – its selfpresentation \nand design, its symbol set and categorization, \nits attendant text and supporting discourse – is ideologically \nloaded to convey a particular message. In so doing, a \nmap does not simply represent the world, it produces the \nworld. To illustrate their argument, they use the example \nof the nature of a map – how the supposedly neutral, \nobjective natural world is produced by maps – \nto demonstrate how maps produce nature rather than \nreflect it.
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 | 0.003 | 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 | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 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 it