Hannah Arendt and the Art of Secrecy; Or, the Fog of Cobra Mist
Bibliographic record
Abstract
Using Hannah Arendt as our guide, we examine the imperfect and at times curious mechanisms through which state projects enact an aura of secrecy and deception. To date, International Political Sociology (IPS) has paid strikingly little attention to the workings of secrecy and deception in politics. Arendt’s contributions to international political sociologies of state secrecy are threefold. First, Arendt’s reflections on lying and secrecy occur across a wide historico-philosophical field, generating insights that a focus on liberal democracy alone cannot. Second, Arendt draws our attention to important variations in the arts of secrecy and deception, and their ethico-political implications. Third, Arendt highlights the limits of traditional scholarly methods for research on lying and secrecy and offers an important tool that we conceptualize as a twist. We demonstrate these three contributions through a case study of a foggy Anglo-American intelligence project called Cobra Mist.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.041 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".