Where States Lie: A Historical Sociological Investigation into the Art of Cover Storying in a Secret Cold War Intelligence Operation
Bibliographic record
Abstract
Secrecy and deception are integral components of ruling, yet remain under-researched and under-theorized sociologically.This thesis draws on two complimentary literatures with the goal of advancing a conceptual framework and agenda for the study of secrecy and deception in government: governmentality studies and dramaturgy.The usefulness of this framework is demonstrated by analyzing the cover storying practices of military officials in Cobra Mist, a secret radar intelligence station built in England in the late 1960s.Based on a theoretical understanding of cover storying, six interrelated themes are developed and substantiated empirically: i) scripting and rehearsing a suitable cover narrative; ii) going public via press release; iii) backstage struggles over cover storying and information leaks; iv) strategies for managing information leakage; v) secret site closure; and vi) the production of mystery.In conclusion this thesis reflects on the methodological limitations of research on government secrecy and offers four possible avenues for future research on cover storying.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.038 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".