Trustless Technology within Trust-Based Systems; A Comparative Study of the Big Four’s Approach to Blockchain Adoption and its Future Prospects
Bibliographic record
Abstract
Technological developments and industrial adaptations are leading to a fundamental change in how industries and strategy function in the world today. Disruptive technologies are forcing us to reconsider the way we make decisions, and the models that were previously in place for delivering products and services. Blockchain in particular has demonstrated its ability to completely upend industry as we know it. Its main strengths lie in the fact that it is decentralized, unchangeable, anonymous and auditable. In this paper, we present a comparative study on the Big Four accounting firms’ approach to Blockchain development and adoption. We first give an overview of the blockchain technology and key characteristics of the blockchain and its applications. Furthermore, we discuss some existing approaches for blockchain development and application in the Big Four accounting firms and highlight the opportunities and future prospects of blockchain technology that can be utilized by the four professional services conglomerates.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".