Joint Model of Weekend Discretionary Activity Participation and Episode Duration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research on travel demand modeling has primarily focused on weekday activity–travel patterns. However, weekend activities and travel constitute a major component of individuals’ overall weekly activity–travel participation. This paper describes a modeling effort that focuses on weekend activity–travel demand for discretionary events. This study bridges the gap in the literature by modeling participation in discretionary types of events, the duration of participation, and accompaniment type jointly in a simultaneous equations model system. A joint discrete–continuous modeling framework is formulated for analysis of these dimensions as a choice bundle. Specifically, the combination of event type and accompaniment type constitutes the discrete component, whereas the duration of participation constitutes the continuous component. The model uses a copula-based sample selection approach that ties the discrete choice error component with the duration error component in a flexible manner. The data used in the paper are drawn from the 2008–2009 National Household Travel Survey sample of the greater Phoenix metropolitan area in Arizona. The results from the estimation process highlight the presence of sample selection in the joint modeling context. Furthermore, the results also highlight the flexibility of copula models in capturing such sample selection. The best copula model results are used to generate hazard profiles for various alternative related duration intervals. The generated profiles highlight the inaccurate predictions obtained by the use of approaches that ignore the presence of sample selection.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 it