Grocery shopping and related access trips by mode in Canadian time use surveys
Bibliographic record
Abstract
• Many travel and time use surveys group grocery shopping with all other shopping. • We explore characteristics of grocery shopping and compare with all other shopping. • Grocery shopping sequences are shorter, more car-based, in home to home sequences or returning home. • Nearly half of full grocery shopping activity time is spent traveling to/from. • Grocery shoppers are distinct from shoppers for all other purposes. Grocery shopping episodes are often grouped with other shopping in travel surveys, making it difficult to study these activities. This paper explores grocery shopping trips, shopping episode characteristics and participants, and assesses the potential loss of information stemming from the grouping of all shopping activities. A sample of metropolitan area respondent data from the Canadian General Social Surveys’ 2010 and 2015 (cycles 24 and 29) time use modules is used. In the 2010 survey, grocery shopping and other shopping is surveyed separately, while the 2015 survey merges all shopping activities. This provides an opportunity to compare these approaches. The characteristics of shopping activities (2010 and 2015) with respect to participation, timing, in-store episode time and trip duration, activity sequences (in-store episodes with access/egress trips), and respondents’ demographics are compared using bivariate tests, and logistic regressions. Activity sequences are assessed using two locations before and two locations after shopping episodes. Grocery shopping activity sequences are shorter in duration than other shopping activity sequences. No difference in episode duration is found between gender or income for groceries, while significant differences are found for other shopping. “Home-store-home” by car is the most frequent sequence for all shopping types. Nearly half of the grocery shopping activity sequence is spent on the access and egress trips. In logistic regressions, age, gender, employment, and the most frequent travel mode are associated with having performed shopping episodes, regardless of shopping types. Compared to other shopping episodes, grocery shopping is more strongly associated with being 75 or older, being married, from visible minority groups, and with higher education. Grocery shopping activities differ from other shopping in terms of participant, timing, duration, and activity sequence. Combining grocery shopping and other shopping in future time use surveys (and in travel surveys) may mask the distinctiveness of grocery shopping episodes, trips and overall sequences.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.021 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".