Profit-seeking solar geoengineering exemplifies broader risks of market-based climate governance
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
Despite uncertainties about its feasibility and desirability, start-up companies seeking to profit from solar geoengineering have begun to emerge. One company is releasing balloons filled with sulfur dioxide to sell “cooling credits”, claiming that the cooling achieved when 1 g of SO 2 is released is equivalent to offsetting one ton of carbon dioxide for one year. Another aspires to deliver returns to investors from the development of a proprietary aerosol for dispersal in the stratosphere. Such for-profit solar geoengineering enterprises should not be understood merely as rogue opportunists. These proposals are not only scientifically questionable, and premature in the absence of effective governance, but they are a predictable consequence of neoliberal, market-driven climate governance. The structures and incentives of market-based climate policy - circumscribed by neoliberalism's emphasis on technological innovation, venture capital, and the marketization of environmental goods - have generated repeated efforts to profit from various forms of geoengineering. With a climate governance regime wherein private, for-profit actors significantly influence and weaken climate policy, de facto governance of solar geoengineering has emerged, dominated by actors linked to Silicon Valley funders and ideologies. Without more explicit efforts to curb the power of private sector actors, including commercial geoengineering bans and non-use provisions, pursuit of techno-market “solutions” could lead to both inadequate mitigation and increasingly risky reliance on geoengineering.
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 | 0.000 |
| 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 it