A Critical Corpus- Based Analysis of the Words Muslim and Islamic Vs. Christian in Contemporary American English
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The words Muslim and Islamic have recently become a recurrent theme in western media especially in the U.S. However, there is little research on how the words Muslim as opposed to Christian are represented in the US spoken and written media discourse. Utilizing the Corpus of Contemporary American English (COCA), the current study investigated how Muslims and Christians are portrayed in U.S media outlets through a quantitative and a qualitative analysis of the lexical collocations of the words Muslim, Islamic and Christian. A threshold of Mutual Information (MI) score of at least 3. and 2% frequency was set for the candidate collocates. The results showed that the former group was largely associated with fanaticism and ethnicity while the other group was largely associated with knowledge and theology. A fine-grained analysis of a common collocate i.e., fundamentalist revealed striking differences between the characteristics of Muslim fundamentalists and Christian fundamentalists in US media. The study highlights the value of corpus-based approaches in enhancing the objectivity of critical discourse analysis and pinpointing the lexical and grammatical patterns that contribute to biased mental construction of particular groups.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it