Bibliographic record
Abstract
Terrorism is the talk of the world. It also occupies a larger part in the media and Islam receives relatively high attention compared to other religions. Islam, Muslims, particularly Arabs, in the eyes of the West, become the source of terrorism that gives the West an opportunity to launch a war against the countries which are accused of terrorism. It is, in fact, a war against radical Islam as they claimed. How do the western politicians, reporters, journalists and writers address terrorism in their official speech or literary works that reflect their vision and understanding of terror/terrorism? The present article addresses Amy Waldman’s The Submission, 2011, John Updike’s Terrorist, 2006, Joel Rosenberg’s The Last Jihad, 2002, and their vision of terrorism, its reasons and the people behind. The article concluded that the western narratives written during the controversial period of the post 9/11. 2001 came deeply influenced by the western media reports and the official statements about 9/11. Such narratives also created, but enrooted Islamophobia and anti- Muslim attitudes in the hearts of the westerners while the western narratives written lately showed more sympathy and rationality towards Muslim characters because the hidden facts of terrorism become exposed. The narratives showed that the western countries exaggerate in their reactions against terrorists/terrorism and the present research concluded that the West has taken precautionary steps to protect its interests and its allies in such countries accused of terrorism. The westerners make use of their domination upon the media to create negative and aggressive attitudes towards Islam/Muslims to blackmail the Islamic countries in the name of war on terrorism, and to secularize/westernize the different aspects of life in such Islamic countries. The narratives showed that war on terrorism is a war on Islam, particularly, radical Islam as claimed.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".