Exploring the Causes of Social Exclusion Related to Mobility for Non-Motorized Households
Bibliographic record
Abstract
Using a lexicometric and qualitative data analysis of 57 semi-directed interviews with members of non-motorized households in the urban areas of Quebec City (Canada) and Strasbourg (France), this paper attempts to show whether living in a carless household in a car-dependent environment fosters feelings of social exclusion and if so, what the contributing factors are. Overall, a majority of respondents said they experienced feelings of social exclusion. Several factors were identified. The lack of consideration of non-motorized households in transportation planning processes and mobility policymaking appear to be important factors. In addition, many respondents perceived that they were not on an equal footing with drivers when it came to policy decisions. Motorized individuals with whom they interacted with, for example, in the workplace, also sometimes negatively judged and misunderstood their carless colleagues. Some also felt excluded from the job market, whereas others perceived exclusion from late evening social functions because of limited public transit schedules. Finally, not being able to get to certain places was often cited as a negative factor.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".