The demographics of decarbonizing transport: The influence of gender, education, occupation, age, and household size on electric mobility preferences in the Nordic region
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
Many researchers, policymakers and other stakeholders have explored and supported efforts to transition towards more sustainable forms of low-carbon mobility. Often, discussion will flow from a narrow view of consumer perceptions surrounding passenger vehicles—presuming that they act in rationalist, instrumental, and predictable patterns. In this paper, we hold that a better understanding of the social and demographic perceptions of electric vehicles (compared to other forms of mobility, including conventional cars) is needed. We provide a comparative and mixed methods assessment of the demographics of electric mobility and stated preferences for electric vehicles, drawing primarily on a survey distributed to more than 5,000 respondents across Denmark, Finland, Iceland, Norway and Sweden. We examine how gender influences preferences; how experience in the form of education and occupation shape preferences; and how aging and household size impact preferences. In doing so we hope to reveal the more complex social dynamics behind how potential adopters consider and calculate various aspects of conventional mobility, electric mobility, and vehicle-to-grid systems. In particular, our results suggest that predominantly men, those with higher levels of education in full time employment, especially with occupations in civil society or academia, and below middle age (30 to 45), are the most likely to buy them. However, our analysis also reveals other market segments where electric vehicles may take root, e.g. among higher income females and retirees/pensioners. Moreover, few respondents were orientated towards V2G, independent of their demographic attributes. Our empirical results can inform ongoing discussions about energy and transport policy, the drivers of environmental change, and deliberations over sustainability transitions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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