The Use of Terminology in Reporting Islam: A Comparative Analysis
Bibliographic record
Abstract
The use of terminology in reporting Islam has been one of the major concerns of many scholars and religious experts in recent years. Specifically, the media’s selection of words to describe Islam attracts attention of many righteous people. Words such as extremist, terrorist, militant, insurgent are mostly used to describe Muslims. This indicates the need to explore how the media particularly newspapers use terminology in reporting Islam, since people rely on the media for news and information. The present study focuses on content analysis of terminology used to describe Islam in selected Nigerian and Malaysian English newspapers. Two different divisions of sampling procedure were employed; sampling for the newspapers and sampling for related articles in the newspapers. The study used purposive sampling to gather data. Punch and Vanguard were chosen from Nigeria while The Star and New Straits Times were chosen from Malaysia based on their popularity and readership. Meanwhile, an internet-based search for news articles on Islam was performed. The aim was to locate the news articles relating to Islam in the selected newspapers. Articles between November 2015 and September 2016 were selected. Any article that focuses upon reporting Islam or Muslims fulfills the inclusion criteria. The content of each article was examined and read for relevance. The newspapers produced 599 different Islam-related articles within this period. The study found that 260 different Islam-related terms appeared in the selected newspapers. But Malaysian newspapers used more (200) of these terms than Nigerian newspapers, which used only 60. However, the most frequently used Islam-related term in the selected newspapers is “Islamist militants” which appeared 60 times, followed by “radical Islam” and “Islamist attacks”, which came second and third respectively. It was found that these words were used in negative context. It is therefore recommended that journalists should make an effort to understand clear connotation of the terminology they use, and use them properly. Newspapers should mind the use of terms in or order to avoid creating negative perception toward Islam.
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How this classification was reachedexpand
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 | 0.388 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".