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Record W4412373178 · doi:10.1080/09669582.2025.2529330

Why <i>Flying Less</i> remains difficult: a <i>theory of practice</i> perspective on transdisciplinary climate and sustainability conferencing

2025· article· en· W4412373178 on OpenAlexafffund
Ying-Syuan Huang, Blane Harvey

Bibliographic record

VenueJournal of Sustainable Tourism · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsMcGill University
FundersMitacsInternational Development Research Centre
KeywordsSustainabilityPerspective (graphical)Climate changeSociologyEnvironmental resource managementEnvironmental scienceComputer scienceGeology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.315
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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