Flying Less for Work and Leisure? Co-Designing a City-Wide Change Initiative in Geneva
Bibliographic record
Abstract
Geneva prides itself on being an international city, home to the United Nations and international organizations. The airport plays an important role in this image, tied to a quest for hypermobility in an increasingly globalized society. Yet, mobility accounts for close to one quarter of the territory’s carbon emissions, with flights responsible for 70% of these emissions. With recent legislation that includes ambitious targets for net zero carbon emissions by 2050, the role of air travel can no longer be ignored. In 2020, a partnership was formed between the City, the University of Geneva, and a community energy association to explore the possibility of co-designing a city-wide change initiative, focused on reducing flights through voluntary measures. The team consulted with a variety of actors, from citizens who fly for leisure, to those who fly for professional reasons, with a spotlight on academic travel. A review of the scientific and grey literature revealed what initiatives already exist, leading to a typology of change initiatives. Inspired by this process, we then co-designed a series of workshops on opportunities for flying less in Geneva. We demonstrate the value of going beyond an ‘individual behaviour change’ approach towards understanding change as embedded in socio-material arrangements, as well as identifying interventions that seek to address both negative and positive anticipated outcomes. We conclude with insights on how a social practice approach to understanding mobility reveals both material and immaterial challenges and opportunities, involving infrastructures and technologies, but also social norms and shared meanings.
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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 | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".