MétaCan
Menu
Back to cohort
Record W4396733252 · doi:10.3167/hrrh.2024.500209

The Americans and “Sleeper Cells” of Russian Intelligence in America

2024· article· en· W4396733252 on OpenAlexvenueaboutno aff
Sergei I. Zhuk

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Abstract In June of 2010, a Canadian couple, Donald Heathfield and Tracey Lee Ann Foley, was arrested in Cambridge, Massachusetts, as the KGB “sleeper agents.” These KGB agents (Andrei Bezrukov and Elena Vavilova) lived in Canada since 1992, and in the United States since 1999, working for the Russian intelligence as “a sleeper cell” of the Russian spies. This story became an inspiration for the American TV show The Americans (2013–2018). Using the reviews of this TV show from the United States and Russia, the interviews with the real participants of the events of 2010 and with the retired KGB officers, the KGB documents from the SBU Archive in Kyiv, Ukraine, this article is an attempt to study how the special KGB/FSB operations in the USA, portrayed in one American TV series became an object of fascination and “fictionalization” on the both—American and Russian—sides of the geo-political conflict.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.011
Scholarly communication0.0060.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.040
GPT teacher head0.365
Teacher spread0.325 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueHistorical Reflections/Réflexions HistoriquesSame topicIntelligence, Security, War StrategyFrench-language works237,207