Conjuring a cooler world? Imaginaries of Improvement in Blockchain Climate Finance Experiments
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
Meeting on the second anniversary of the Paris Agreement signing, the United Nations Climate Change Secretariat founded the Climate Chain Coalition (CCC) in 2017. Backed by a number of multi-stakeholder groups like the Blockchain for Climate Foundation, the Ottawa-based CCC promotes the use of this emergent technology as a pathway to achieving the goals of the Paris Agreement. What kind of ‘cooler’ world are blockchain-based climate projects conjuring? This article scrutinizes the shared visions materializing in particular across climate finance experiments, locating them as extensions of existing imaginaries of how financial markets can address planetary concerns. The imaginaries identified underpin these ‘cool’ technological feats yet provide only incremental improvements to existing modes of market-led climate governance that are far from the scale required to actually conjure a cooler planet.
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