Fantastic Beasts: Blockchain Based Banking
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
Blockchain is one of the primary digital technologies utilised in the finance industry with huge future potential. This study conducts a systematic literature review of a final sample of 407 prior literature from an initial set of 1979 records for the sample period of 2013–2020 with regard to blockchain adoption in banking. This review is further supplemented by a machine learning based textual analysis that identifies key themes, trends, divergences and gaps between academic and practitioner led industry literature. Moreover, the study highlights present, future use cases, adoption barriers and misconceptions of blockchains in banking, especially given COVID-19. Furthermore, this study identifies behavioural, social, economic, regulatory and managerial implications of blockchain based banking. In addition, our study identifies the cross-industry potential of blockchains via banking, thus, linking much disconnected prior literature. Finally, we develop a blockchain adoption framework and an adoption life cycle for banking. This study would be of interest to academics, bankers, regulators, investors, auditors and other stakeholders in financial markets.
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