Shopping less with shopping lists: Planning individual expenses ahead of time affects purchasing behavior when online grocery shopping
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
Abstract How do shopping lists affect purchasing behavior? On the one hand, breaking down a shopping task into its subcomponents might increase predicted budget for the shopping trip and consequently increase the number of purchases made and dollars spent. On the other hand, a shopping list may function as a concrete action plan for the shopping task and decrease the number of purchases made and dollars spent. In two studies, participants were randomly assigned to make a shopping list for their next grocery trip or not make a list and then completed the shopping trip virtually without the shopping list (Study 1) or with the shopping list (Study 2), using a popular online grocery store website. Those who were induced to make a shopping list prior to shopping bought marginally (Study 1) or significantly fewer (Study 2) items in an online grocery trip and spent marginally less money (Study 1). Simply making an overall spending prediction did not have the same effect as writing an itemized shopping list (Study 2), and purchases in this condition did not differ from those in the control group. We also document descriptive information on frequency of use and beliefs about functionality of shopping lists.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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