The dual state : parapolitics, Carl Schmitt and the national security complex
Bibliographic record
Abstract
Contents: The concept of the parapolitical, Eric Wilson State-corporate globalization and the rise and demise of the new deal world order, Tom Reifer Capitalism, covert action and state terrorism: toward a political economy of the dual state, Nafeez Mossadeq Ahmed 'America is addicted to oil': US secret warfare and dwindling oil reserves in the context of peak oil and 9/11, Daniele Ganser Researching parapolitics: replication, qualitative research, and social science methodology, David N. Gibbs The unusual suspects: Africa, parapolitics, and the national security state complex, Enrico Carisch State hierarchy and governance: of shadows or equivalence in regulating global crisis, Mark Findlay Dual state: the case of Sweden, Ola Tunander Canadian stalking horse: 'a parallel power', David MacGregor A study in gray: the Affaire Moro and notes for a re-interpretation of the Cold War and the nature of terrorism, Guido Giacomo Preparata Schmitt, Ergenekon and the neocons, Len Bracken The spectacle and the partisan, Jeff Kinkle Targeting journalists and media in the new world order, Stig A. Nohrstedt and Rune Ottosen Afterword: dual Schmitt, deep Schmitt, William A. Rasch Index.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".