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
A mismatch between largely absolute Newtonian models of space in GIScience and the relational spaces of critical human geography has contributed to mutual disinterest between the fields. Critical GIS has offered an intellectual critique of GIScience without substantially altering how particular key geographical concepts are expressed in data structures. Although keystone ideas in GIScience such as Tobler's "First Law" and the modifiable areal unit problem speak to enduring concerns of human geography, they have drawn little interest from that field. Here, we suggest one way to reformulate the computational approach to the region for relational space, so that regions emerge not through proximity in an absolute space or similarities in intensive properties, but according to their similarities in relations. We show how this might operate theoretically and empirically, working through three illustrative examples. Our approach gestures toward reformulating key terms in GIScience like distance, proximity, networks, and spatial building blocks such as the polygon. Re-engaging the challenges of representing geographical concepts computationally can yield new kinds of GIS and GIScience resonant with theoretical ideas in human geography, and also lead to critical human geographic practices less antagonistic to computation.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.017 | 0.006 |
| 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 it