Cybercrime is whose responsibility? A case study of an online behaviour system in crime
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Drawing on Sutherland’s theory of behaviour systems in crime, this study investigates social media fraud (SMF) facilitated by botnets to understand the onset and maturation of this new online offending behaviour. We find legitimate actors in the system – Internet of Things manufacturers, online social networks, hosting companies and law enforcement agencies – share a way of life that prioritises private gains and avoids implicit responsibility for security. They arrive at a Nash equilibrium that provides a weak and disorganised social response to crime. SMF providers, on the other hand, are cleverly organised and exploit weaknesses in security, adapting to change and developing working relationship with those who benefit from their activities and share their lenient behaviour towards fraudulent activities. We conclude that the rise in cybercrime is a result of the behaviours of all actors in the system, not just those who offend.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it