Bibliographic record
Abstract
This research discusses Iran's response to the political thriller movie Argo and how the movie represents Iranians. Argo movie was launch in October 2012 focusing on an exfiltration mission in Iran by the CIA, which is based on true events in 1979 when the Islamic Revolution broke in Iran. Iranian in 2012 was shocked by Argo's Iranian depiction that was deem by president Mahmoud Ahmadinejad ‘anti Iranian' and American propaganda. Iran further their accusation when Argo receive the prestigious Oscar award handed by first lady Michelle Obama at Febuary 24th 2013. This research will explain the Iran Hostage Crisis and Canadian Caper history in 1979, how Iran respond to the movie Argo in 2013, the scenes that was protested by the Iranian government, what kind negotiations are being done, and how the movie Argo influences Iran's and United States International relations. Perspective that used in this research is Realism perspective. The theory used in this research is the mass media concept. The theory used as a framework for analyzing the factors and cause the movie Argo and its consequences for Iran'spolitical situation.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 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".