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Record W4386396592 · doi:10.1111/eufm.12451

Is bitcoin ESG‐compliant? A sober look

2023· article· en· W4386396592 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEuropean Financial Management · 2023
Typearticle
Languageen
FieldComputer Science
TopicBlockchain Technology Applications and Security
Canadian institutionsConcordia University
Fundersnot available
KeywordsTransparency (behavior)Corporate governanceCriticismElement (criminal law)Compensation (psychology)BusinessAccountingFocus (optics)Environmental economicsEconomicsComputer securityPolitical sciencePsychologyFinanceLawSocial psychologyComputer science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.941
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.006

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.

Opus teacher head0.017
GPT teacher head0.231
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it