From Excess Commuting to Commuting Possibilities: More Extension to the Concept of Excess Commuting
Bibliographic record
Abstract
The excess-commuting literature provides a methodological framework in which the observed average commute ( C obs ) is compared with theoretical commuting values: the minimum ( C min ) and maximum ( C max ) average commute. In this paper, I argue that real spatial behavior is ill represented by the two assumptions of optimal (minimizing or maximizing) behavior. C min and C max are in fact extreme values of a much richer distribution of commuting possibilities. I argue that all those possibilities should be taken into account in the evaluation of C obs . In order to do this, I develop a probabilistic framework where any urban form is associated with a statistical distribution of commuting possibilities, with an average and a standard deviation, within which C min and C max represent extreme and very improbable outcomes. Applied to a sample of fifty metropolitan areas, this framework helps us understand the combined association of spatial behavior and urban form with commuting.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".