Extending drift theory to cybercrime forum participation: the case of digital workers
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
This study extends Matza’s concept of drift to cybercrime forum participation, suggesting that participants exist in a liminal state where they are neither fully compliant with legal norms nor explicitly engaged in criminal activity. In this state, criminal involvement can only be confirmed when individuals openly disclose crimes on these forums. This nuance is valuable when studying those who are not fully committed to cybercrime, but remain active in these settings, such as digital workers. Through an analysis of 105 digital workers in cybercrime forums, this study reveals their limited and sporadic engagement, with many contributing benign or ambiguous content. This reflects the neutrality of IT, where criminal intent is often ambiguous. Only a small fraction displayed consistent criminal involvement. Moreover, the findings empirically support Goldsmith and Brewer’s (2015) notion of digital drift, underscoring the fleeting and episodic nature of, in this case, cybercrime forum participation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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