Why <i>Flying Less</i> remains difficult: a <i>theory of practice</i> perspective on transdisciplinary climate and sustainability conferencing
Bibliographic record
Abstract
Air travel for academic and policy convening is a growing contributor to global carbon emissions. Researchers, policymakers, consultants, and practitioners working in the environment, climate, and sustainability (ECS) field are particularly implicated, as prevailing practices of frequent flying may jeopardise the long-term credibility of their work. This study applies Pierre Bourdieu’s theory of practice to better understand how air travel-intensive professional practices are perpetuated within the ECS community, and the factors that deter from a wider adoption of hybrid and virtual conferencing. Drawing on an international survey, the findings reveal that unequal access to digital capital and entrenched belief in the superiority of face-to-face interactions collectively sustain the illusio that air travel is indispensable. Furthermore, the habitus of conferencing as a means of accumulating symbolic capital reinforces a reward structure that continues to incentivise frequent flying. The findings further show how power dynamics sustain the dominance of frequent flying and reinforce the emergence of digital elites. Transforming air travel-intensive ECS practices thus requires those who shape success in the field to move beyond reliance on short-term technical fixes and foster collective responsibility for decarbonisation. It also calls for active engagement in developing new practices and incentive structures that encourage low-carbon alternatives.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.081 |
| Scholarly communication | 0.017 | 0.012 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".