Random Utility Location, Production, and Exchange Choice; Additive Logit Model; and Spatial Choice Microsimulations
Bibliographic record
Abstract
A land use modeling system has been developed and applied on the basis of random utility theory. The system abstracts the decisions of the actors located in and traveling around a city or region as a series of logit models: (a) the choice of where to locate the home; (b) the choice of technology, lifestyle, or production option, being the choice of the quantities of “commodities” (consisting of goods, services, labor, and space categories) to consume or produce and hence what interactions will occur; and (c) the location of the “exchange” (transaction or interaction) for each commodity consumed or produced (i.e., for each interaction). These logit models can be combined in a nesting structure, but an additive logit formulation is required because the exchange choices are not mutually exclusive. The additive logit model, which is developed by combining the central limit theorem with random utility theory, can be applied to any choice situation in which several independent choices are conditional on a higher level choice. The resulting choice probabilities can be applied in an aggregate allocation system (as in software for the Production Exchange Consumption Allocation System, PECAS) and result in supply-and-demand equations for each commodity in each exchange that can be solved for a short-term equilibrium. In future research, microsimulation versions of the system could allow a fully integrated and dynamic representation of land use-transport interactions.
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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 | 0.009 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".