A spatially aware method for mapping movement‐based and place‐based regions from spatial flow networks
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Community detection (CD) is a frequent method for analysing flow networks in geography. It allows us to partition the network into a set of densely interconnected regions, called communities. We introduce a new technique for including geographical weighting in existing methods for detecting spatially coherent communities. We take a link‐based CD algorithm and adjust it to incorporate geographical weighting. We call this approach geographically weighted community detection (GWCD). Our method is demonstrated on two case studies of commonly encountered flow networks: commuter flows and taxi pick‐up/drop‐off flows. Further, we test different measures of distance for geographic weighting and compare our results with the unmodified CD algorithm. Our results show that GWCD can capture the geographical nature of flow regions, generating spatially smaller and more compact areas than if geography is omitted, and that it can be used to distinguish between different types of movement‐type communities.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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