Socio-Legal Issues Affecting the Use of Digital Signatures for Secure E-commerce Transactions: A Caribbean Perspective
Bibliographic record
Abstract
This article examines the socio-legal issues surrounding the role of digital signatures as an internet technology for secure e-commerce transactions in Caribbean developing countries. It highlights the view that as internet technologies become more affordable in developing countries, the societal changes surrounding digital signatures will be even greater than that of developed countries. Further, the increasing use of internet technology in electronic transactions raises the issue of the legality of these transactions. As in similar developing countries, socio-legal issues in the Caribbean Region will include perception, privacy and authentication, trust and confidence, psychology and culture, internet access and cost, and increased security. Given the absence of adequate legislation on digital signatures in Caribbean countries, the article concludes that for this technology to meet the need for user confidence in secure e-commerce transactions, an information infrastructure must first be put in place before users in Caribbean developing countries can actively engage in secure e-commerce.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".