Modeling Individuals' Frequency and Time Allocation Behavior for Shopping Activities Considering Household-Level Random Effects
Why this work is in the frame
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Bibliographic record
Abstract
A comprehensive frequency and time allocation modeling system for shopping activities is described. The modeling system is person-based but explicitly considers fixed and random household effects. It has three components: a weekly shopping frequency model, a daily shopping frequency model, and a time allocation model for individual shopping episodes. The frequency models consider activity generation as a latent response—the propensity to participate in shopping activities. This latent response is modeled by using an ordinal response model. Both the weekly and daily frequency models are multilevel ordinal logit models, in which the household is the highest level and the individual is the lowest level. The multilevel ordinal logit models incorporate household-level influences on an individual's shopping behavior in terms of fixed effects and a random intercept. The time allocation models are hazard duration models that consider household-level random heterogeneity. The entire modeling system is sequential from the weekly frequency component to the time allocation component. The outputs of the earlier components enter as inputs to the later components: weekly frequency is the input to the daily frequency model; weekly and daily frequencies are input to the time allocation model.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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 it