Military Spending and Economic Growth: A 2025 Update
Bibliographic record
Abstract
The start of the second millennium brought a growing sense that capitalism was becoming more ‘authoritarian’ and ‘illiberal’, with various indicators suggesting that ‘democracy’ is waning around the globe, that the protection of human and civil rights is in retreat and that the number and intensity of military conflicts is on the rise. This angst is now greatly amplified by the domestic and foreign policies of the new Trump administration. Having returned to office in early 2025, Trump promptly launched a highly publicized crusade against his country’s ‘deep state’, with blasé disregard for its laws and con-stitution; announced his intentions to retreat from his country’s traditional postwar role as leader and protector of the Western world; and embarked on seemingly unhinged acts against friends (Canada, Mexico, Denmark, Panama and, primarily, Ukraine) while cozying up to long-term foes (Russia). One possible consequence of this growing angst is a global ‘arms race’.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.013 |
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".