Suspended Equilibrium in Iran's Political System
Bibliographic record
Abstract
Two sets of power relationships have emerged in the political system of the Islamic Republic of Iran: official, institutional relationships outlined in the Constitution, and unofficial, informal ones existing between and within groups and clusters of powerful individuals and institutions. The juxtaposition of informal factional alliances with the formal institutions of power has resulted in the development of a precarious balance within the state, as ‘hardliners’ and ‘softliners’ vie for greater influence and the adoption of their agendas as official state policy. The ensuing results have been two‐fold. On the one hand, the emergence of multiple centers of power has enhanced the extent and reach of the state in relation to various social strata, thus bestowing it with considerable durability and staying power. On the other hand, the existence of multiple official and unofficial venues for competition has sharpened the tenor and substance of factional rivalries. For the most part, each of the factions has so far been able to balance out the influence and agendas of the other. At the same time, however, since the ‘softliners’ by and large advocate greater political liberalization, these very factional rivalries have had some modest consequences in opening up the Iranian polity. Ultimately, the pace and direction of political liberalization in Iran will depend on the outcome of the ongoing rivalry that is currently being played out within official state institutions and unofficial power‐cliques.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".