Bibliographic record
Abstract
Places of household residence and places of commuter destination are considered in a contiguous system of subareas constituting a region. An intrahousehold distribution of household members, by subarea of their commuting destination, is considered for each subarea of residence. A household composition matrix is constructed in reference to the average number of commuters to subareas of destination, per household at a subarea of residence, across all subareas. The matrix is a linear transformation from the spatial distribution of households onto the spatial distribution of daytime population, over all subareas of the region. Diurnal population change throughout the region is rendered by this transformation. A linear optimization model extending this transformation formalizes general conditions that relate the diurnal population system to household choice of residence and work. Further, the division of the region into subareas is assumed to be such that the average household in each subarea contains at least one person who remains in the subarea during day and night. Under these conditions, the diurnal system is shown to be analogous to the Leontief input‐output model. An example of eleven counties of North Wales, along with an exogenous area of northwestern England, drawn from the 1991 census of the United Kingdom, illustrates the formal relationships.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".