The Impact of Coronavirus Pandemic on Bitcoin: A Literary Overview
Bibliographic record
Abstract
Bitcoin has several features that set it aside from traditional currencies. Digital convenience ensures the safety and convenience of Bitcoin users, while decentralization also poses as a primary benefit. Not only does this specific type of cryptocurrency portray many advantages, it also positions several disadvantages as well. Extreme volatility and the impact of negative externalities on the value of Bitcoin contribute to the assessment of Bitcoin trends in the market. The recent outbreak of the coronavirus (COVID-19) has shown evidence of influencing Bitcoin prices as the virus is spread across continents, leaving the global financial environment in turmoil. The classification of Bitcoin as either a portfolio diversifier, a hedge or a safe haven is dependent on various factors, including the global economic uncertainty. Analyzing the literature on the influence of the crisis on the Bitcoin movement will provide an explanation as to why COVID-19 has had such a significant impact on the global financial markets, especially that of cryptocurrencies.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".