An econometric investigation on the relationship between modal accessibility and the home–work spatial configuration of two-commuter households
Bibliographic record
Abstract
This paper investigates the relationship between modal accessibility and the home–work spatial configuration of two-commuter households in an urban area. The home–work spatial configuration is captured by: (a) total commuting distance of the two commuters (from home to work) and (b) the angle between the two work locations (as measured from the common home location). The household travel survey data of 2011 of the National Capital Region is used for the empirical investigation. The empirical investigation reveals that higher modal accessibility increases the angle and reduces the total commuting distance. This investigation also reveals that certain two-commuter households are not able to optimise their home location in terms of widening the angles and reducing total distances. A correlation between total commuting distance and angle between work locations is observed such that angle decreases as the distance between home location and the Central Business District (CBD) increases. We infer that two-commuter households located far from the CBD live in predominantly residential areas that lack employment centres. As such, land use policies should guide development in areas far from the CBD towards mixed land uses. These findings are useful for urban transportation and land use planning since the proportion of two-commuter households is increasing in many urban areas.
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.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".