Memorandum of Understanding for the implementation of the COST Action "Building on scientific literacy in evolution towards scientifically responsible Europeans" (EuroScitizen) CA17127
Bibliographic record
Abstract
Memorandum of Understanding for the implementation of the COST Action “Building on scientific literacy in evolution towards scientifically responsible Europeans” (EuroScitizen) CA17127 As citizens, we are confronted with a deluge of information and misinformation from the internet and the mass media. Scientific literacy, i.e. the ability to critically evaluate, apply and understand scientific knowledge and how it is produced, is therefore vital for responsible citizenship. It is a prerequisite for generating a knowledge-based society and for allowing citizens to make informed decisions. One of the most important fields of science is evolution, the foundation of modern biology. Evolutionary biology has great societal relevance and its findings have far-reaching implications for how we respond to climate change, drug resistance, issues of food security and controversies in modern medicine. However, it is frequently misunderstood or even rejected outright. This makes scientific literacy in evolution an ideal model to research approaches to improve the state of European scientific literacy. This Action will, for the first time, leverage the strengths of diverse stakeholders (evolutionary biologists, education researchers, educators, museum professionals and the media) to generate and analyse approaches used to improve public scientific literacy. Bridging differences in culture and education systems including participants from a wide range of countries and backgrounds is a source of innovation in itself. The expected result is to identify targeted strategies to raise levels of scientific literacy in Europe, thereby maximising Europe’s innovation potential. The Action will contribute to a culture of responsible, research and innovation (RRI) and will result in a more scientifically literate European citizenship, instrumental to implementing Europe 2020’s smart, sustainable and inclusive goals.
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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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.025 | 0.022 |
| Insufficient payload (model declined to judge) | 0.150 | 0.078 |
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".