The carbon footprint cost of travel to Canadian Urological Association conferences
Bibliographic record
Abstract
Introduction: Canadian Urological Association (CUA) conferences are held annually across Canada. Guests from across the world attended, contributing to the overall carbon footprint of the conference with their travel and accommodations. This study identified the carbon footprint of each of the 2016 (Vancouver), 2018 (Halifax), and 2019 (Quebec City) CUA conferences to investigate their carbon footprint and help determine the most eco-friendly location to hold future conferences. Methods: Registrant home institution was used to estimate the distance and method of transportation of attendee travel. Carbon footprint was calculated using an online calculator in tons of CO2 equivalents (tCO2). Total attendees, number of attendees driving, number of attendees flying, mean distance travelled per attendee, total carbon footprint, and average carbon footprint per attendee were calculated for each conference. Mean carbon footprint, and mean distance travelled were compared using a Brown-Forsythe ANOVA test, with Dunnett’s T3 multiple comparisons test (α=0.05). Results: Vancouver had the largest number of attendees (n=473; 407 flying, 66 driving), followed by Halifax (n=382; 331 flying, 51 driving), and Quebec City (n=362; 265 flying, 97 driving). The mean distance attendees travelled was greatest for the Vancouver CUA (6041 km/roundtrip) compared to Quebec City (3096 km/roundtrip, p<0.0001) and Halifax (2985 km/roundtrip, p<0.0001). There was no difference in mean distance travelled between Halifax and Quebec City (p=0.95). The highest total carbon footprint was seen in Vancouver (tCO2=447.76), followed by Quebec City (tCO2=217.04) and Halifax (tCO2=182.22). The average footprint per attendee was significantly higher in Vancouver (mean tCO2=1.08) compared to both Quebec City (mean tCO2=0.62, p<0.0001) and Halifax (mean tCO2=0.52, p<0.0001). There was no difference in the average footprint between Halifax and Quebec City (p=0.63). Conclusions: The estimated emissions associated with the Vancouver CUA conference is greater than both the Halifax and Quebec City locations combined. In-person conferences provide several benefits to the urological community. Incorporating environmental considerations into conference planning, such as conference location, could reduce the CUA conference’s overall carbon footprint, mitigating the contribution to rising temperatures and negative health outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".