Graham Allison et le paradigme bureaucratique : vingt-cinq ans plus tard est-il encore utile ?
Bibliographic record
Abstract
Twenty-five years ago, Graham T. Allison brought to the political scientists community a new tool to help us to understand questions in the domain of Foreign Policy : the Bureaucratic Politics Model. Since then, his Essence of Decision has been one of the most read books in Universities and one of the texts most referred to in scholar works. However, it is of interest to analyze if, beyond the framework's reputation and despite the numerous criticisms addressed to it, the bureaucratic politics is still useful for someone who wishes to do analysis based on Us elements. How bureaucratic politics can still help us to better understand the decision-making processes ? Are there avenues, questions or problems that still can be better explained by referring to this scheme ? The answer we offer to these questions refers to the model's components, to an update of the evaluation several scholars made of it, and, finally, to a dynamic orientation that puts forward the paradigmatic dimension of the theory and an application to a specific question.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".