Bibliographic record
Abstract
Bright Internet research was launched as a core project of the AIS Bright ICT Initiative, which aims to build an ICT-enabled Bright Society. To facilitate research on the Bright Internet, we explicitly define the goals and principles of the Bright Internet, and review the evolution of its principles. The three goals of the Bright Internet are: the realization of preventive security, the provision of the freedom of anonymous expression for innocent netizens, and protection from the risk of privacy infringement that may be caused by preventive security schemes. We respecify design principles to fulfill these seemingly conflicting goals: origin responsibility, deliverer responsibility, identifiable anonymity, global collaboration, and privacy protection. Research for the Bright Internet is characterized by two perspectives: first, the Bright Internet adopts a preventive security paradigm in contrast to the current self-centric defensive protective security paradigm. Second, the target of research is the development and deployment of the Bright Internet on a global scale, which requires the design of technologies and protocols, policies and legislation, and international collaboration and global governance. This research contrasts with behavioral research on individuals and organizations in terms of the protective security paradigm. This paper proposes validation research concerning the principles of the Bright Internet using prevention motivation theory and analogical social norm theory, and demonstrates the need for a holistic and prescriptive design for a global scale information infrastructure, encompassing the constructs of technologies, policies and global collaborations. An important design issue concerns the business model design, which is capable of promoting the propagation of the Bright Internet platform through applications such as Bright Cloud Extended Networks and Bright E-mail platforms. Our research creates opportunities for prescriptive experimental research, and the various design and behavioral studies of the Bright Internet open new horizons toward our common goal of a bright future.
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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 | 0.055 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".