A joint model of residential mobility and location choice decisions
Bibliographic record
Abstract
Residential relocation is a process involving the interdependent decisions of mobility (i.e. the decision to move) and location choice. Location choice is a discrete choice decision, whereas mobility has a continuous time dimension. Since households relocate along their life course for different reasons such as the birth of a child, these reasons could influence the duration of stay as competing events. This paper develops a joint model for mobility and location choice decisions. Data come from a retrospective survey conducted in the Central Okanagan of British Columbia, Canada. A reason-based competing hazard model is developed for the mobility component of the joint model. For the location choice component, a latent segmentation-based logit model is developed to capture unobserved heterogeneity. The influence of location utility on mobility is addressed through log sum parameters. The model confirms the effects of life-cycle events, parcel, socio-demographic, land use, transportation, neighbourhood and accessibility characteristics. The findings reveal that households relocating for the occurrence of life-cycle events are active in the housing market following the birth of a child, marriage and vehicle purchase. Relocation to live in a desirable neighbourhood is found to delay the move for the reason of living closer to activity points. Results also indicate that duration is likely to be shorter with the increase in expected utility from the following location. Regarding the location choice, preferences for dwellings closer to schools are evident. In the case of heterogeneity, it is observed that urban dwellers are more likely to prefer locations closer to the workplace with the addition of jobs in the household. In contrast, suburban dwellers are more likely to prefer residing far from the workplace. The developed joint model has been included in an integrated urban model, currently under development at the University of British Columbia.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".