Moral Panic and Electric Micromobilities: Seeking Space for Mobility Justice
Bibliographic record
Abstract
This article makes the case that electric micromobilities (EMMs) are the site of a moral panic and employs the lens of mobility justice to explain it. Through analysis of scholarly and media discourse, interviews with, and social media content produced by, EMM riders (eriders), and the auto ethnographic experiences of the lead author as an electric unicycle rider in daily life, as a participant in online and offline "erider" communities, and as a food delivery worker, we reinforce the conclusion that alternate mobilities face an uphill battle in gaining legitimacy and inclusion in transportation policy and infrastructure. While this is not a new finding-alternate mobilities have a long history of being demonized and excluded-this article offers insight into how individuals who find themselves unwitting scapegoats in conflicts over public space consciously engage in deliberate actions to resist EMM panic and achieve greater mobility justice.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.053 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".