Bibliographic record
Abstract
The discourse around the bridging the gap debate is seen to a unique sub-set of the social sciences in the United States as applied to a unique American approach to security. This article looks beyond US National Security and the practices of the discipline of political science at US universities to address, and expand on, some specific ideas in Michael Desch’s volume The Cult of the Irrelevant. We offer that an integrative assessment of how scholarly work can best inform security policies and practices requires more critical examination in four domains: consideration of how different disciplines frame key issues and speak to each other; understanding the dynamics of the policy marketplace; assessments to alternate ways to frame security and national security; and requirements to critical challenge the privilege academics have awarded themselves as the purveyors (and gatekeepers) of ‘knowledge’ and the ‘truth’.
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 | 0.028 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.015 | 0.048 |
| Scholarly communication | 0.028 | 0.086 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.017 | 0.020 |
| Insufficient payload (model declined to judge) | 0.019 | 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".