A roll down memory lane: Policy implications of nostalgic experiences in shared e-scooter consumption
Bibliographic record
Abstract
• Ethnographic study utilizing transit diaries, interviews, and participant observation to explore nostalgia's role in shared e-scooter use. • Nostalgia was found to be associated with consumer feelings of freedom and social connectedness. • New mobility norms and meanings ascribed to transport modes need to be considered in current e-scooter policy contexts. This ethnographic study leverages transit diaries, in-depth interviews, and participant observation to examine consumptive experiences of shared e-scooter use. Moving beyond functional and utilitarian motivations, this research draws on Consumer Culture Theory to uncover the affective dimensions that shape users’ experiences with e-scooters. Findings reveal nostalgia, underpinned by consumer feelings of freedom and social connectedness, are present in e-scooter experiences and implications for policy makers are discussed. By increasing awareness of consumptive experiences of e-scooters, this research contributes to an understudied area of transportation and mobility research, and holds potential to assist cities in understanding how to better implement first- and last-mile transit solutions as micromobility moves out of the periphery and into the core of transit systems.
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.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".