Trust and Confidence and the Digital Economy:Issues and Challenges
Bibliographic record
Abstract
Globalization and technological change continue to profoundly affect economic growth and wealth creation. Information and Communications Technologies (ICTs) have been a key enabler and driver of globalization, which is likely to continue as trade and investment barriers continue to fall and communications become ever cheaper, easier and more functional. National economies, created by the Industrial Revolution in the 19th century, will continue to blend into a 21st century integrated, digital world economy, with an increasingly global division of labour. Every economy requires a physical, institutional and legal infrastructure, as well as understandable and enforceable marketplace rules, in order to function smoothly. In this paper the authors maintain that such an infrastructure must be developed for the new digital economy and society, one which provides trust and confidence for all those who operate in or are affected by it. An infrastructure that is an amalgam based on hardware, software, networks and a way of doing business which offers predictability, dispute resolution, legal recourse, policing powers against fraud,authentication, etc. The building of such an infrastructure is a necessary condition for the development and efficient functioning of a global, digital economy.
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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 | 0.014 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.007 | 0.046 |
| Scholarly communication | 0.026 | 0.037 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.014 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".