Modelling activity generation: a utility-based model for activity-agenda formation
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Bibliographic record
Abstract
This article presents an econometric modelling framework for activity-agenda formation. The activity-agenda is referred to the collection of different types of activities that are to be scheduled within a specific time period (time budget). The concept of activity utility is used to model frequencies of all individual activity types under consideration within a specific time budget constraint. Contrary to univariate modelling approach for individual activity types separately, this approach deals with all activity types together in a unified econometric modelling framework. The specification of the model also ensures the scope for unplanned (or not defined a priori) activities within the time budget. Kuhn–Tucker optimality condition is used to ensure the probability of having zero frequency of any specific activity type. Each individual activity-specific utility has two components: baseline utility and additional utility. The logarithmic function of additional utility ensures the satiation effect with increasing frequency. The heterogeneity in activity behaviour is also considered by incorporating error correlation in baseline utility. Data from the 2002–2003 CHASE survey, collected in Toronto are used to test the model specifications. Application of this modelling framework in an activity-based travel demand model will greatly enhance behavioural validity as well as sensitivity to subtle transportation policies of travel demand models.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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