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
While conducting doctoral research on international undercover operations, the author attended undercover training courses in the United States (US) and in Canada. He also conducted interviews with undercover operatives and those that supervise undercover operations with several agencies in the US, Canada, United Kingdom (UK) and the Netherlands. During the course of this research the author was privy to sophisticated and contemporary undercover training and recruitment methodologies. While the author is available to provide advice to law enforcement agencies on undercover management and training, the author is cognisant of the detrimental effect of disclosing policing methodologies to those external to law enforcement who may hold less than desirable motives. As such, this article is focused upon shedding some light upon the legal ‘grey’ area that exists between the right to silence and police undercover investigations, from information available in the public domain. However, when researching material for this article, the author was both surprised and alarmed at the quantity and accuracy of publicly available information on undercover policing methodologies. 1
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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