Development of GreenDealz: A public engagement toolkit addressing critical raw materials and the EU Green Deal at informal education settings
Bibliographic record
Abstract
Abstract. One of the most important challenges Europe faces to date is the need for a drastic increase in the extraction, production, and recycling of critical raw materials to meet the demands of renewable energy technologies, as specified in the European Union's climate targets. However, this topic is not widely discussed amongst publics and is underrepresented within the field of informal education and public engagement. This pilot study describes the development of a public engagement toolkit called “GreenDealz” that aims to address this gap. We focus specifically on the festival environment as an informal education setting. GreenDealz was created via an iterative process informed by in-situ data collection across six cultural/arts and science festivals in Ireland. GreenDealz engages informal audiences through a supermarket experience, where participants must choose key critical raw materials to build essential renewable energy technologies and achieve EU climate goals. Evaluation is integrated into the tactile experience of GreenDealz. Embedded assessment measures yield quantitative data that show GreenDealz may significantly enhance audience knowledge of the topic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".