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Record W2489631024 · doi:10.1177/0038038516657949

Deception Declassified: The Social Organisation of Cover Storying in a Secret Intelligence Operation

2016· article· en· W2489631024 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSociology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicIntelligence, Security, War Strategy
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSecrecyDeceptionSociologyNarrativeCover (algebra)State (computer science)PoliticsEpistemologyLawAestheticsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

This article asks why and how governments keep secrets from publics, journalists and politicians using the strategy of ‘cover storying’. To develop a theory of cover storying, insights are drawn from political sociologies of state secrecy and from recent sociological examinations of secrecy and deception in organisations. This theory is illustrated by analysing Cobra Mist, a secretive and deceptive Anglo-American Cold War intelligence operation. Examining recently declassified documents, this article develops a framework for the analysis of five interrelated narrative conditions that shape social processes of cover storying: correspondence; plausibility; accountability; constraint; and durability. In conclusion this article reflects on the broader implications of this analysis for contemporary state and organisational theories and understandings of secrecy.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.158
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.062
GPT teacher head0.365
Teacher spread0.302 · 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