Future Studies of Virtual State Formation in Iran and Its Effect on the Promotion of Global Peace Index (the Outlook of 1404)
Bibliographic record
Abstract
In this study, it has been attempted to investigate the feasible and desirable futures regarding the possibility of virtualization of Islamic Republic of Iran’s state and its effect on the promotion of Global Peace Index (GPI) using trend analysis technique, Delphi surveys and scenario building .Therefore, according to the documents such as perspective and development documents, the outlook of 1404 SH has been considered as a time period of desirable future formation. The writer believes that the formation of virtual state in Iran through decreasing structural violence in society leads to the promotion of GPI. In fact, the dynamics of new global arrangements that have been derived from the technological innovations and socioeconomic adjustments of international relations actors with agencies and global markets, have led to the formation of a new pattern for the conceptualization of states’s evolving nature, that in turn, can increase the possibility of positive peace elements through decreasing the level of structural violence in society. In order to confirm this assumption, seven key deriving forces of virtual states have been chosen referring the systematic theory of virtual state by Richard rosecranace and combining it with Galtung’s positive peace theory and their evolution has been investigated since writing the outlook documents. On the next step, four main scenarios were formed in response to the probability of virtual state formation around two axes of states’ commitments to pursue open economic policies and sanctions lifting as two independent variables. Finally, all four scenarios were evaluated using Delphi surveys of elites and one scenario was chosen as the probable future.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".