La complexité de valeurs dans la politique étrangère de l'administration Reagan face à l'Iran
Bibliographic record
Abstract
The formulation of a policy that will satisfy several values and interests more or less compatible is a classic problem of political decision making. This phenomenon by which there can be, in a foreign policy issue for example, several divergent values and interests was named value-complexity by Alexander George. When facing a value complexity problem, a decision maker must choose some values and some interests over others. The choice he makes will not necessarily be the one made by other decision makers. This can result in a serious impediment to the decision making process. The American foreign policy towards the Middle East faced, for the major part of the Cold War era, a value-complexity problem because it looked to reconcile four hard-to reconcile values and interests. The Reagan government was confronted rather acutely with this problem in the making of its Iranian policies. The administration was split in at least two factions over Iran : one who thought primarily of containing the Soviet Union in the Middle East region and the other for whom the political stability of moderate regimes threatened by revolutionnary Iran should be the most important priority. The existence of these factions, consequence of value-complexity, produced the making and the implementation of two distinct Iranian policies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".