Between Desire and Routine: Assembling Environment and Finance in Carbon Markets
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
Abstract: This article contributes to emerging research on the social construction of carbon markets by focusing on the mobilisation of desire amongst carbon market actors, and on the routinisation of financial practices within such markets. We examine specifically the markets that have emerged around the Clean Development Mechanism. First, we look at the stories market actors tell each other in advertising and at Carbon Expo. Second, we look at the routinisation of carbon finance through the borrowing of ideas and tools from traditional financial markets. We suggest that the former animates the markets while the latter enables the markets to become “normalised” for financiers. We also suggest that the two aspects however also work in tension with each other, and that the character of this tension is one way of understanding the distinctiveness of carbon markets.
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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