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Record W4413097598 · doi:10.1016/j.fhj.2025.100453

Estimating CO2 emissions from international medical electives: a literature review and quantitative analysis

2025· review· en· W4413097598 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFuture Healthcare Journal · 2025
Typereview
Languageen
FieldMedicine
TopicTravel-related health issues
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental science

Abstract

fetched live from OpenAlex

• There is growing concern regarding the carbon footprint associated with face-to-face international electives. • Virtual electives are undertaken by students and instructors who are separated in space, where instructors can teach remotely via the internet using technology such as videoconferencing and virtual reality. These virtual electives have recently appeared as an attractive alternative with the potential to contribute to improving the sustainability of medical education and student satisfaction has so far been broadly positive based on available literature. • We performed calculations for direct round trips from the United Kingdom (UK) to the 10 most popular elective destinations for UK medical students. • Our CO2 emissions calculator produced similar emission estimates to other calculators used, and suggests that the carbon footprint of IMEs is substantial. • Future research should also evaluate alternative programmes, to assess whether or not virtual or local electives are considered to provide the same educational benefits as in-person electives. Electives are short placements during medical school lasting 2–8 weeks, serving as an opportunity to engage with different healthcare systems and cultures and to travel overseas. However, amid increasing alarm about climate change, interest in the sustainability of electives and alternative elective formats are gaining attention. A scoping review of MEDLINE, Embase, ERIC, Web of Science SCOPUS, WHO Globus Index Medicus and Scielo was conducted with double-blind screening to identify previous efforts to quantify carbon costs of electives. To quantify the carbon dioxide (CO 2 ) emissions of electives, we created an approach based on the fuel efficiency of aircraft used for long-haul travel, distances from the UK to popular elective destinations and the average occupancy rates of aeroplanes. These results were compared with results from seven existing resources: MyClimate, ICAO, Google Flights, C Level and EcoTree. The review did not identify any previous studies estimating the environmental costs of medical student electives. All of the 7,575 records revealed by the database search were excluded following full-text screening. Our estimates of the CO 2 emissions from round-trip flights from Heathrow Airport, London, UK to the 10 most popular elective destinations were: Australia: 2,995 kg/person, USA: 1,039 kg/person, New Zealand: 3,316 kg/person, Canada: 941 kg/person, India: 1,185 kg/person, South Africa: 1,705 kg/person, Malaysia: 1,867 kg/person, Tanzania: 1,322 kg/person, Ireland: 79 kg/person. This is the first study to quantify the carbon footprint of international medical electives. Our bespoke calculations, which generally agree with the results from established tools, reveal that CO 2 emissions from international travel for electives are substantial, compared to the average annual CO 2 emissions of 7,000 kg per person in the UK. This study provides evidence to motivate the design and delivery of alternative elective programmes.

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.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.794
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.007
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.470
Teacher spread0.432 · 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