Learning to be consumers of “smart” retail channels: The baby boomer experience
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
A global shift in aging populations points to greying consumers as an important market for retailers and an underserved segment for researchers. The COVID-19 pandemic has accelerated digital expansion in the marketplace, innovated new industries, and encouraged new participants. This acceleration provides significant implications for the greying population whereby the adoption of smart-enabled platforms and channels becomes essential. Most of the digital and smart-consumer socialization research has focused exclusively on younger generations because of their digital nativity. This study aims to expand our understanding of baby boomer consumers’ attitudes and behaviors in the smart retail context using a consumer socialization framework. Findings suggest that perceived usefulness, ease of use, reliability, and fun were significant influences on global attitudes toward shopping in smart retail channels. Global attitudes toward shopping in smart retail channels significantly influenced behavioral intention and digital mass media exposure significantly influenced all dimensions of attitudes toward shopping in smart retail channels suggesting interest and engagement in smart retail channel participation among older adults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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