The Impact of Blockchain-Based Shareholder Voting System on Corporate Governance
Bibliographic record
Abstract
The development of blockchain technology in modern business and finance is of great importance.The study delves into the blockchain-based shareholder voting system and the role of blockchain on corporate governance.On this basis, relevant research hypotheses are formulated.After completing the definition of research variables, the research model is constructed to empirically investigate the impact of blockchain-based shareholder voting system on corporate governance.The research hypotheses are tested through regression analysis and the robustness test is utilized to ensure the reliability of the research findings.The minimum value of blockchain-based shareholder voting and corporate governance level are both 0, the maximum value is 4.954, 0.624, and the average value is 0.821, 0.089, respectively.There is variability in shareholder voting and corporate governance level across companies.Before and after the control variables, the coefficients of blockchain-based shareholder voting system are 0.225 and 0.247 respectively, and both are significantly positive at 1% level.Blockchain-based shareholder voting system can improve corporate governance.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".