Why we need to think beyond NATO’s 2 per cent benchmark: suggestions for amending the research programme
Bibliographic record
Abstract
The research programme on NATO burden sharing is heavily influenced by quantitative political economists who are interested in testing theories with statistical inferences and regression analysis. It uses predominantly rationalist, deductive reasonings and is informed by methodological individualism. However, there are significant theoretical and methodological limitations with such an approach, above all in understanding burden sharing as a social practice rather than a static outcome. This contribution offers suggestions for a post-positivist turn of NATO’s burden sharing research programme, especially those that highlight the importance of intersubjective meanings and the role of social forces, norms, beliefs, and values in burden sharing decisions that are not derived from material interests and reflexively inform behaviour. Such a post-positivist turn, we charge, would help us to explain how collective burdens are constructed and perceived by the member states. We also offer suggestions on how to operationalize this turn in the research programme.
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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 | 0.135 | 0.305 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.017 | 0.041 |
| Open science | 0.013 | 0.009 |
| Research integrity | 0.021 | 0.022 |
| Insufficient payload (model declined to judge) | 0.030 | 0.010 |
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".