Living on a flammable planet: interdisciplinary, cross-scalar and varied cultural lessons, prospects and challenges
Bibliographic record
Abstract
Living with fire is a challenge for human communities because they are influenced by socio-economic, political, ecological and climatic processes at various spatial and temporal scales. Over the course of 2 days, the authors discussed how communities could live with fire challenges at local, national and transnational scales. Exploiting our diverse, international and interdisciplinary expertise, we outline generalizable properties of fire-adaptive communities in varied settings where cultural knowledge of fire is rich and diverse. At the national scale, we discussed policy and management challenges for countries that have diminishing fire knowledge, but for whom global climate change will bring new fire problems. Finally, we assessed major fire challenges that transcend national political boundaries, including the health burden of smoke plumes and the climate consequences of wildfires. It is clear that to best address the broad range of fire problems, a holistic wildfire scholarship must develop common agreement in working terms and build across disciplines. We must also communicate our understanding of fire and its importance to the media, politicians and the general public.This article is part of the themed issue 'The interaction of fire and mankind'.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".