Football and climate change: what do we know, and what is needed for an evidence-informed response?
Bibliographic record
Abstract
Association football is popular and influential globally. Interest in how football relates to climate change, and the climate policy required for football, is growing. Clubs, players and fans increasingly call for action to reduce football’s impact on the climate, and for plans to adapt to climate impacts on football. However, well-intentioned actions must be underpinned by robust evidence. This synthesis reviews research at the interface of football and climate change. After summarizing the main climate actions identified for fans, players, clubs and organizing bodies, the review looks in-depth at four areas: impacts of football on climate; impacts of climate on football; football as a driver for pro-climate actions; and the relationship between football and carbon-intensive industries. The review then outlines research gaps for an evidence-driven response to climate change in football: adaptation across different geographical contexts; understanding what climate change means for community-level football; understanding how carbon-intensive industries relate to sense of place identity in football under a just transition; developing principles for phasing-out fossil fuel financing; and considering how climate change relates to women’s football.Key policy insights Football is a forum for galvanizing societal action in support of climate policy. However, football also contributes to, and is impacted by, climate change, and hence requires policy support under a changing climate;Reducing transportation emissions, especially flying, is a key climate policy requirement for football. Institutional policy, with government support, may enable more efficient scheduling and use of surface transport;Institutional policies, and public health policies, should develop standards and guidelines for football under extreme heat. Football also ought to be integrated within local, regional and national climate adaptation policy to ensure climate resilience;Clubs and players can lead by example on climate-positive actions, and energize wider action through fan bases. Alignment of initiatives with national or international climate policy may raise public awareness of climate polices and targets;Institutional policies for clubs, tournaments and associations should regulate fossil fuel financing. Football also offers an avenue to understand relations between local identity and carbon-intensive industries, and thus to identify socio-cultural factors for regional just transition policies.
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 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 | 0.047 | 0.176 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".