Climate Change in School: Where Does It Fit and How Ready Are We?.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research indicates that teachers place a high priority on climate change as a topic their students should know, but report their own knowledge as inadequate for teaching it. Students (and some teachers) seem unable to distinguish among related environmental issues, and treat general “environmentally friendly” behavior as affecting all issues. The curricular fit of global climate change is best in Earth systems oriented classrooms but opportunities exist across the curriculum; instructional materials are available, though these may not address misconceptions. Some interest groups oppose human-mediated climate change as a curriculum topic, for the same reasons they oppose public action on the problem. Resume D’apres la recherche, les enseignants estiment qu’il est important pour leurs eleves d’etre au courant du changement climatique, mais que leur propre connaissance du phenomene n’est pas a la hauteur. Les eleves et certains enseignants semblent incapables de distinguer les enjeux environnementaux connexes et considerent que le comportement ecologique en general affecte tous les enjeux. L’adequation du changement climatique planetaire avec le programme d’etudes est plus reussie dans les cours axes sur les systemes terrestres, mais il existe aussi d’autres possibilites. Des documents d’instruction sont aussi disponibles, quoiqu’ils n’abordent peut-etre pas les interpretations errones. Certains groupes d’interet refusent que le programme d’etudes aborde le sujet du changement climatique cause par les humains pour les memes raisons qu’ils s’opposent a l’action du public face au probleme.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it