Bibliographic record
Abstract
When we think of tackling climate change, we think about reducing CO2 emissions. Whilst this is essential, it is no longer enough. MacMartin and Ricke examine the failures of current carbon dioxide removal (CDR) strategies, all of which fail to satisfy three essential criteria: scalability, economic viability, and lack of detrimental local impacts. In the face of future uncertainty, there is another tactic – in addition to mitigation and carbon dioxide removal – that Macmartin and Ricke propose: ‘solar geoengineering’, an approach aiming to reduce global warming by decreasing the amount of incoming energy from the sun. Such ideas were first discussed in the 1960s, but remained mostly on the fringe until 2006. At its most basic level, geoengineering seeks to modify the radiation balance of Earth by increasing the amount of energy sent back into space, and this chapter discusses how it might be possible to accomplish this – from mimicking the cooling effect that occurs after large volcanic eruptions to enhancing the formation of reflective low clouds over the ocean. However, these approaches present both technical challenges and significant questions to be addressed – from physical effects to broader societal issues impacting ethics and international relations. If CO2 emissions continue unabated, there will be an increase in the amount of geoengineering required to compensate, and future generations would be committed to maintaining it indefinitely. In order for it to be effective, geoengineering must be considered as a supplement and not a substitute, used alongside CO2 reduction, and accompanied by a development in the capacity of international governance to make sound decisions.
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.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.193 | 0.101 |
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".