Bibliographic record
Abstract
Purpose This is a theme editorial written exclusively by the guest editor for this special issue. This opinion piece demonstrates the impact of technology convergence on the internal control mechanism of an enterprise. It is important for an auditor to be aware of the security hazards faced by financial or the entire organizational information system. Author attempts to bring security systems design and the organizational vulnerabilities in the context of the convergence of communication and networking technologies with the complex information technology in business processes. Design/methodology/approach This editorial is mostly conceptual analysis of the current state of affairs. Findings Being an editorial, there are no specific findings presented in this piece. Research limitations/implications Theme editorials, being conceptual expositions of a particular current issue generally lack support of data analysis. However, advantage can be obtained by the future researchers by designing a study around the theme propounded in it here. Practical implications Its conceptual contribution is mostly knowledge enhancement and skill building for the professional external, internal or information systems auditor and budding researchers in the field of internal controls, new technologies and security. Originality/value It is an original piece written with a purpose of presenting the importance of convergence of technology vis‐à‐vis its impact on the internal controls in an organization and the matters of security.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".