Climate policy beyond ideological trenches
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
The climate crisis demands urgent and effective policy interventions, yet the discourse remains mired in ideological polarization. On one side, some argue that reducing consumption is the primary solution to the climate crisis, while others emphasize that technological innovation is the only viable option. We argue that a convergence of perspectives is needed and propose using the ecological footprint metric as a framework for evaluating the environmental impacts of different policies. The metric, expressed as a fraction with consumption in the numerator and efficiency in resource use in the denominator, allows for an equitable evaluation of the outcomes of policies that focus on either reducing consumption or improving efficiency. Through simulations, we analyze the ecological footprint outcomes of various scenarios—Business-As-Usual, Tech World, Consumption Reduction, and Smart Sustainability. We show that trade-offs between consumption and efficiency are hardly avoidable, and policies that address both aspects—such as those outlined in the Smart Sustainability scenario—are more likely to reverse the growing trend of global ecological footprints. While sharp and unexpected disruptions—such as major epidemics causing abrupt declines in consumption or breakthrough innovations dramatically improving efficiency—could in theory shift these dynamics, bridging ideological divides remains the most prudent approach for crafting policies that can effectively address the climate crisis and ensure a sustainable future.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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