Function, symbolism or society? Exploring Canadian consumer interest in electric and shared mobility
Bibliographic record
Abstract
Electric and shared mobility offer alternatives to the dominance of privately-owned, fossil fuel powered vehicles.I explore consumer perceptions and motivations regarding these innovations, using survey data from samples of Canadian adopters and non-adopters of electric vehicles, car-sharing and shared ride-hailing (n = 529).I apply a framework with four perception categories: private-functional (e.g., costs and convenience), privatesymbolic (e.g., making good impressions), societal-functional (e.g., protecting the environment) and societal-symbolic (e.g., spreading inspiration).Using a theory-based approach, I regressed the four perception categories noted above as predictors of adoption for each innovation.Results show that positive private-functional perceptions are consistent predictors across all three innovations, while private-symbolic perceptions are only associated with electric vehicle adoption.Societal-functional and societalsymbolic perceptions have no association with adoption.I also apply an exploratorybased approach using factor analysis to identify unique perception categories.Findings are largely consistent with the first method, with some nuanced insights.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".