The Othering of Muslims: Discourses of Radicalization in the <i>New York Times</i>, 1969–2014
Bibliographic record
Abstract
In this article, I engage with Edward Said's Orientalism and various perspectives within the othering paradigm to analyze the emergence and transformation of radicalization discourses in the news media. Employing discourse analysis of 607 New York Times articles from 1969 to 2014, this article demonstrates that radicalization discourses are not new but are the result of complex sociolinguistic and historical developments that cannot be reduced to dominant contemporary understandings of the concept or to singular events or crises. The news articles were then compared to 850 government documents, speeches, and other official communications. The analysis of the data indicates that media conceptualizations of radicalization, which once denoted political and economic differences, have now shifted to overwhelmingly focus on Islam. As such, radicalization discourse now evokes the construct radicalization as symbolic marker of conflict between the West and the East. I also advanced the established notion that the news media employ strategic discursive strategies that contribute to conceptual distinctions that are used to construct Muslims as an “alien other” to the West.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.011 | 0.021 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| 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".