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Record W4399333855 · doi:10.1108/ijshe-03-2023-0102

Reporting of and policy on greenhouse gas emissions from air travel at Canadian universities

2024· article· en· W4399333855 on OpenAlexaboutno aff
Derek Hall

Bibliographic record

VenueInternational Journal of Sustainability in Higher Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicConferences and Exhibitions Management
Canadian institutionsnot available
Fundersnot available
KeywordsGreenhouse gasSustainabilityNatural resource economicsEnvironmental scienceBusinessEnvironmental economicsEconomics

Abstract

fetched live from OpenAlex

Purpose This paper aims to explore the extent and characteristics of Canadian university reporting of and policy regarding greenhouse gas emissions from air travel. It identifies current approaches’ details and limits and recommends improvements. Design/methodology/approach The study developed questions and considerations for analysing reporting and policy, reviewed university documents and webpages and contacted university staff. Findings Roughly 20% of Canadian universities report flight emissions. Figures vary by factors of over 100 even when normalized or expressed as a percentage of institutional emissions. Inter-university differences in data collection and emissions calculation practices shape reporting. Canadian university air travel emissions cannot be meaningfully compared. Few universities have flight emissions reduction policies; those that do leave relevant decisions to individuals. These approaches do not respond adequately to the emissions reduction challenge. Originality/value This study is the first comprehensive survey of university flight emissions reporting for any country. Its original framework highlights calculation’s complexities. It recommends standardizing reporting process information disclosure, reporting flight emissions as a range and faculty leadership of emissions reduction efforts.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.653
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.033
GPT teacher head0.370
Teacher spread0.337 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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