Comparison of the environmental impacts of online and classical conferences: the case of LCE 2020 and perspectives regarding the planetary boundaries
Bibliographic record
Abstract
International conferences such as CIRP LCE usually imply that their attendees travel around the world to reach the venue. Several online conferences have already been organised, but the year 2020 was particular because of the COVID-19 pandemics which obliged to cancel or modify dramatically all the events planned from the second quarter of that year. The CIRP Life Cycle Engineering conference was no exception and all arrangements made before March were cancelled or modified in order to host the conference online. This article presents the environmental impact assessment of the online conference and its comparison to the estimation of the impacts if the event had taken place in Grenoble (France), as initially planned. This study confirms that an online conference has lower environmental impacts than a classical conference, except for freshwater quality. The main contributors are the country energy mix of the audience for the online conference and the travel by plane for the classical one. This article also shows that online conferences might contribute to stay within the planetary boundaries. These results encourages to improve the study of the environmental impacts of online conferences and to highlight the hotspots to be improved.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".