Is bitcoin ESG‐compliant? A sober look
Bibliographic record
Abstract
Abstract Much of the media focus surrounding Bitcoin (BTC) has been on the ‘E’ (environmental) element of the ESG investing approach. Given the amount of electricity consumed by BTC mining, and the resulting large carbon emissions, BTC has faced substantial criticism of its overly negative environmental impact, which is critically reviewed in this article. This one‐sided discussion, however, ignores the ‘S’ (social) and ‘G’ (governance) elements entirely. To remedy that, we explore BTC's positive impact on the ‘S’ (user satisfaction, data protection and privacy, human rights, and criminal activity), and ‘G’ (accounting integrity and transparency, compensation, and principles of good governance) components.
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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 | 0.020 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.015 | 0.023 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".