Who and what are carbon markets for? Politics and the development of climate policy
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
Why have carbon markets been rapidly adopted as policy solutions to climate change in the last decade? Perhaps surprisingly, this question has attracted virtually no attention in the large literature on such markets. The standard arguments given for why carbon markets are good ways to respond to climate change do not explain why such markets have flourished as governance mechanisms in relation to climate. Carbon markets have spread and become taken-for-granted because of the potential they give to certain powerful actors (financiers, specifically) to create new cycles of investment, profits and growth. As a consequence, they make possible a political coalition combining financiers with environmentalists. This coalition has considerable potential to legitimize substantial cuts in carbon emissions in the face of continued opposition from other interests. It is the combination of these two elements - the promotion of specific growth sectors and the construction of a political coalition - that constitutes the principal political virtue of carbon markets. In order to demonstrate this claim, the history of emissions trading is traced and the implication of this analysis is explored for the further building of climate governance centred on carbon markets.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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