Bibliographic record
Abstract
Introduction: Security Meta-Framing: A Cultural Logic of an Ordering Practice Vida Bajc Public Spaces and Collective Activities 1. No Joking! Mark Salter 2. Security Meta-framing of Collective Activity in Public Spaces: The Pope John Paul II in the Holy City Vida Bajc Struggle and Resistance 3. When the Israeli State of Exception Meets the Exception: The Case of Tali Fahima Liora Sion 4. Rethinking National Security Policies and Practices in Transnational Contexts: Border Resistance Kathleen Staudt Law, Citizenship, and the State 5. A Note on Security Modulation Willem de Lint 6. Before the Law: Creeping Lawlessness in Canadian National Security Reem Bahdi 7. The Pre-Emptive Mode of Regulation: Terrorism, Law, and Security Gabe Mythen Global Agendas, Local Transformations 8. Re/Building the E.U.: Governing through Counterterrorism Sirpa Virta 9. Transnational Media Corporations (TNMCs) and National Culture as a Security Concern in China Jiang Fei and Huang Kuo 10. Security Metamorphosis in Latin America Nelson Arteaga Botello Conclusion: Security and Everyday Life Willem de Lint
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.005 |
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".