The Symbolic Review of the Concept of War in the Works of Iranian Artist: Ali Akbar Sadeghi
Bibliographic record
Abstract
<p>By examining the history of world art, it can be expressed that art was not conducted between different ethnic groups only through cultural exchanges. And sometimes common aspects can be found among the artworks which have been the same among all nations. This suggests that the human is a treasure of symbols and images in which the traces of all human races can be seen during different periods of time. Carl Gustav Jung called this belief as “archetype” which is manifested in various symbolic forms. According to this theory, we can cite the many artists not only to express their own ethnic and national values to create their work but also studied the human subjects which are at a collective unconscious. They moved beyond the boundaries of their land. Ali Akbar Sadeghi is an Iranian contemporary painter. He maintained the tradition of painting in his country and used universal symbols in his works. The most important of these symbols is the symbols of war. This article suggests the hypothesis that Ali Akbar Sadeghi knows the world as a place for interference and conflicts and used the tools and symbols of war in his works in order to express the permanent war in the world. The results of this paper states that these symbols have emerged during the periods of his art activities in different ways, shapes and forms in order to convey the concepts and individual contrast with the environment. The method of this study is descriptive- analytical and data collection method was performed through interviews with the artist and library studies.</p>
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".