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
In this third report, I focus on cognitive cartography in order to examine how the historical division between empiricist and critical approaches in cartography has shifted recently. I do so by building on Kitchin and Dodge’s argument (2007) that parts of the apparent disjuncture within cartography might be resolved through a greater focus on emergent approaches to mapping as a process, which is the core idea of post-representational cartography. By looking at cognitive cartography from a post-representational perspective I emphasize two major trends. On the one hand, the processual positioning of post-representational cartography simply shifts the historical line of divide, since it inherently disqualifies any cognitive studies that artificially dissociate the map from its context of use and production. On the other hand, by enabling the combination of critical positioning with empiricist practices, post-representational cartography offers opportunities to revisit in practical terms the tensions between these two approaches. It provides an original framework to envision our mental, emotional and embodied relationships with maps and with places through maps, and has the potential to bring cartography into a new arena in which the empiricist/critical divide could be transcended.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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