Investigating the Role of Social Networks in Start Time and Duration of Activities
Bibliographic record
Abstract
In the context of improving understanding and modeling the capabilities of activity-scheduling processes in travel behavior, this paper explores the role of social networks in the start time and the duration of social activities. The study was performed with a trivariate joint econometric model that was capable of capturing the correlation between unobserved influential factors causing the endogeneity of these three key decisions. The model captures the relevance not only of sociodemographic variables but also of the social network dimension for travelers, or the with whom variable, that is, individuals with whom travelers perform social activities. A particularly relevant case is the role of travel time to social activities, which has a positive effect on longer durations and late start times and which acts as a link between these two basic dimensions (start time and duration) of activity scheduling. The results confirm the relevance of the social context in an episode's temporal characteristics and illustrate aspects that future activity-based travel demand models should incorporate to be able to capture the socializing side of mobility decisions.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".