Taking Action on Climate Change--Inside and Outside Our Schools.
Bibliographic record
Abstract
ention climate change and some people’s first reaction is uncertainty about what it means. Others know what it means but wonder whether we need to be concerned about it or doubt that it is occurring at all. For many educators, the question is not whether climate change is occurring, as the scientific data is compelling enough to convince us that it is. Rather, the question is how to engage students in meaningful exploration of this global issue and in positive action within their own communities. Climate change is difficult to address tangibly, due in part to its relative invisibility. But it is the slow pace of climate change — the long period over which it manifests itself — that largely accounts for people’s natural reluctance to recognize and respond to it. “Natural” because, as ecologist Paul Erlich has pointed out, our vertebrate nervous system has evolved as a “fight or flight” mechanism: it is built to respond to sudden changes or threats in our environment but not to changes that develop slowly and incrementally. This makes it difficult for us to perceive climate change as a threat, since it is a slowly emerging phenomenon which began more than a generation before us and may not reach truly crisis proportions until at least a generation after us. For students, comprehending the time period over which climate change occurs is not the only challenge. They may also struggle to make sense of climate change in the absence of direct experience, and its global scale can prevent them from feeling that they have any ability Taking Action on Climate Change: Inside and Outside our Schools
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.014 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.008 | 0.019 |
| Insufficient payload (model declined to judge) | 0.028 | 0.015 |
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".