The Global Problem of the Third Millennium: Organized Transnational Cybercrime (Historiography)
Bibliographic record
Abstract
During the last decade issues connected with rapid development of phenomenon known all over the world as "computer crime" have been thoroughly studied. At present this concept (rather conditionally) includes all illegal actions when electronic processing of information was an object or means of committing them. Thus the problem now embraces not only crimes directly connected with computers but also such as fraud with credit magnet cards, crimes in the telecommunications sphere (fraud with international phone conversations payment), illegal usage of electronic payments bank network, illegal software, fraud in using play slot machines and many others. Crimes connected with using evidence of computer origin when investigating traditional crimes are also referred to this group of issues. Computer crime is an international phenomenon; its level is closely connected with economic level of society development in different countries and regions. Less developed technically counties due to the activity of international law enforcement organizations have an opportunity to use experience of more developed countries for preventing and detecting computer crimes. General tendencies, criminal means and preventive measures are similar in different countries in various time periods, they are based on united technical program and methodological base of these crimes. Thus "computer crime" notion together with development of computer, telephone technologies was gradually transformed into crimes in informational technologies' sphere concept.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 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".