Mulheres, Get on your Bikes!: Critical Consciousness Building and Women’s Cycling Mobility Spaces in Brazil
Bibliographic record
Abstract
Over the past decade, cycling groups, collectives, and social projects specifically dedicated to improving the everyday cycling mobility experiences of women have emerged across Brazil. My research categorizes these cycling groups, collectives, and social projects as women’s Cycling Mobility Spaces (CMSs). Women’s CMSs use collective practices to address the gender, race, and class relations that have contributed to the underrepresentation of women cyclists in Brazil. For example, in Niterói, the Brazilian city with the highest share of women cyclists, women only represent 12 per cent of the cyclists (Franco 2014). My research draws from interview data with women across 10 different cities and 14 different CMSs to answer the following question: why and how do women use cycling as a method for social transformation? I argue that the collective practices of women’s CMSs reflect the process of critical consciousness-building. The critical consciousness-building activities of women’s CMSs in Brazil highlight the significance of non-physical cycling infrastructure in mobilizing cycling mobility justice in the Latin American context.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".