Blockchain technology in corporate governance and future potential solution for agency problems in Indonesia
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
The aim of this study is to determine stakeholder acceptance of the blockchain and to investigate a suitable model using a Technology Acceptance Model with specific reference to corporate governance through cryptography in solving decades of financial record-keeping problems. Stakeholders in corporate governance, namely customers, creditors, suppliers, communities, employees, owners, investors, trade unions and social activists, can benefit in different ways. Investors can benefit from buying equity at a lower price and selling it on a market with greater liquidity, but they will find it difficult to disguise their trades. This study argues that almost all aspects of corporate governance can be improved through the application of this technology, which results in greater transparency, increases liquidity, and lowers costs. Corporate governance will also be better because blockchain technology uses the concept of a distributed ledger which allows data to be distributed at every connected point in an efficient and accountable manner, so that all parties in the blockchain can exchange data in real time.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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