Teaching climate change in mathematics classrooms: An ethical responsibility
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
Climate change is one of the most urgent human concerns. Mathematics, in various degrees of complexity, is used to communicate climate change to scientists, politicians, policy makers, the general public and children. Drawing on ideas from critical citizenship and critical mathematics education, we ask how incorporating issues of climate change into the teaching and learning of mathematics can be understood as a moral and ethical act? We consider the possible ethical and moral role of mathematics education at large, as well as the role and challenges of individual teachers who consider addressing climate change in mathematics classrooms. We illustrate our discussion with analysis of Canadian and Norwegian mathematics teachers’ explanations of their thinking about climate change in their teaching. We conclude that although including climate change in mathematics classrooms can be (and is) viewed as an ethical responsibility of mathematics teachers, in their day-to-day practice their decisions about this issue are complex.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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