Role of Spatial Configuration in Commuting Trade-Offs of Two-Worker Households: A Case Study in the Greater Toronto Area
Bibliographic record
Abstract
This research investigates the commuting trade-offs between individuals in two-worker households with home and work locations in the Greater Toronto Area (GTA). A commuting trade-off occurs when a home relocation results in one worker incurring a higher commute distance for the other worker to work closer to the home location. This research uses stated preference data and multilevel modeling to demonstrate that two-worker households adjust their home–work spatial configuration which results in commuting trade-offs between individuals. This research uses the angle between the two workplaces, measured at the home location, as a variable in its empirical model. This variable is a descriptor of the home–work spatial configuration and a predictor of total household commute distance. The modeling results indicate an inverse relationship between total household commute distance and the difference between individual commutes. This suggests that individuals in two-worker households trade off their individual commute distances and, in that process, reduce total household commute distance. A key policy implication arising from this research relates to the jobs–housing balance within a catchment area. Two-worker households have been regarded as a hindrance to achieving jobs–housing balance as the two work locations present a constraint in relocating the home near both work locations. However, as this research shows, workers will trade off their individual commute distances such that a home relocation results in a shorter commute distance for one worker and longer commute distance for the other.
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 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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".