Frozen-Ground Cartoons: An international collaboration between artists and permafrost scientists
Bibliographic record
Abstract
Communicating science about a phenomenon found under ground and defined by its thermal properties in an easy, fun, and engaging way, can be a challenge. Two years ago, a group of young researchers from Canada and Europe united to tackle this problem by combining arts and science to produce a series of outreach comic strips about permafrost (frozen ground). Because this concerns us all. As the climate warms, permafrost thaws and becomes unstable for houses, roads and airports.The thawing also disrupts ecosystems, impacts water quality, and releases greenhouse gases into the atmosphere, making climate change even stronger. The Frozen Ground Cartoon project aims to present and explain permafrost research, placing emphasis on field work and the rapidly changing northern environment. The target audience is kids, youth, parents and teachers, with the general goal of making permafrost science more fun and accessible to the public. The project has so far produced 22 pages of comics through an iterative process of exchanging ideas between two artists and thirteen scientists. The project artists were selected through an application call that received 49 applications from artists in 16 countries. With input from scientists, artists Noémie Ross (Canada) and Heta Nääs (Finland) have created a set of beautiful, artistic, humoristic, and pedagogic comics.. The comics are available for free download through the project web page (in English and Swedish), and printed copies have so far been handed out to school kids and general public in Europe. Prints in North America are planned for the fall of 2017. The next steps of the project are (1) to distribute the comics as wide as possible, (2) work towards translations into more languages, and (3) to evaluate the effectiveness of the science communication through the comics, in collaboration with schools and pedagogic experts.
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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.016 | 0.008 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.041 | 0.004 |
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".