Metaphors of resistance in the counter-discourse of Spanish, English and Dutch cycling activists
Bibliographic record
Abstract
There is a current need for exploring new mobility systems - and related narratives - that could help in addressing the challenges caused by climate change. As such, this paper aims to unveil the counter-discourses that promote cycling as a sustainable means of transport and an ecological solution to the current climate crisis. It identifies the main conceptual metaphors of contemporary emerging mobility as framed by Spanish, English and Dutch-speaking cycling advocates. The data, which includes 95 metaphors, were retrieved from X (Twitter), and analyzed qualitatively. Expanding upon the established strategies for challenging dominant metaphors (Gibbs Siman 2021, Van Poppel Pilgram 2023), we investigated the workings of resistance metaphors in the discourse of cycling activists. The study showed that partial resistance metaphors elaborate on the source domains of institutionalized mappings (city is a body, traffic is a circulatory system). They profile motorized mobility as an agent of disease (e.g., blood clot, drug, virus), which negatively affects the city as a whole; alternatively, they also foreground cycling as a potential healer (e.g., cycling infrastructure as band-aids or surgery). Additionally, complete resistance metaphors expose the drawbacks of motorized mobility and envisage alternative urban mobility designs through the introduction of new source domains (cities are ecosystems, cities are houses). The contribution of these metaphors to the current discourse on urban mobility ranges from an opposition to motonormativity to emphasizing cycling as a solution and promoting new kinds of urban co-existence. The underlying reconceptualization of the city from its perception as a (mechanized) body to that of a house or ecosystem also reveals a shift in its function from being a space for moving to being a space for living.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 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".