Exploring equity implications of online grocery, online restaurant delivery and e-shopping service usage in a suburban context
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
By examining how different demographics engage with online services, researchers and policymakers can better understand patterns and disparities in their access, usability, and engagement. This study explores the factors driving the frequent usage of online services, particularly online grocery shopping, online restaurant delivery, and e-shopping. By utilizing a representative sample of Scarborough, Ontario, Canada, collected in 2022, this study followed a Generalized Joint Regression Modelling approach by simultaneously modelling three online service usage behaviours. The findings suggested that millennials are highly likely to be frequent users of all forms of online shopping, while baby boomers and the greatest generation are less likely to engage in these activities. Households with children demonstrate a strong inclination towards online service usage, highlighting household's need for convenience and time savings. Access to personal vehicles influences online service usage behaviour. The study also found that car users are more likely to prefer in-person grocery shopping. Health-related challenges, such as mobility difficulties, correlate with increased reliance on online services. Furthermore, neighbourhood satisfaction and the perceived ease of accessing services positively impact online service usage. The findings further implied a nuanced relationship between online service usage and its potential impact on equity-deserving groups and sustainable transportation behaviour of Scarborough residents. Although findings suggested that online service usage is prevalent among several sociodemographic groups, it may exacerbate disparities for lower-income and transport-disadvantaged populations due to costs and digital exclusion. This scenario highlights the need for balanced urban planning and policy interventions to support equity and community ties in the digital age.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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