Une approche synoptique des théories de la décision, de la puissance et de la négociation
Bibliographic record
Abstract
Assuming that the synoptic reading of partial theories is of use in the building of cumulative theories, the author seeks to establish common points between theories of the decision-making process in foreign policy and theories of power and egotiation at the international level. This paper seeks as well to complement these latter two types of theory with the findings of decision theory. After having justified his undertaking by the relations existing between observed phenomena - that is, decision, power and negotiation - and by the absence of a theory taking these three phenomena into account, the' author sets out the plan of his reflection in function of the distinctions between the approaches and factors emphasized by the various decision theories. The text considers the defining elements of the most important contributions of the specialists on the question. To conclude, the author provides a synoptic table of the main observations of his analysis. This table, which in the author's opinion is able to account for specific situations that are not explicitly described therein, demonstrates that the paradigms of theories of power and negotiation may only be established by reference to the decision paradigm.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".