Translation versus Transliteration of Religious Terms in Contemporary Islamic Discourse in Western Communities
Bibliographic record
Abstract
The significance of the present research stems from the escalating yet unnecessary conflict between Islamic culture on the one hand and western civilization on the other hand. The researchers believe much of the growing and sometimes mutual distrust between the two sides may sometimes at least stem from mere linguistic behaviour. Hence, this research aspires to examine the use of translation versus transliteration of religious Islamic terms in two different types of Islamic discourse in the western countries, viz. the site of Imam Hendi (USA) and the Da'wah Internet site of Australia, as representative of tolerant versus intolerant Islamic discourse. The main objective is to investigate the researchers' hypothesis that the use of translation versus transliteration may be fairly regarded as a linguistic marker of the type of content advocated by the two kinds of Islamic discourse. The scope of the research is confined to Islamic discourse in English, notwithstanding that the author/s in both sites in question are native speakers of English, and, hence, differences in the use of transliteration and/or translation can hardly be attributed to problems with linguistic competence. In this respect, a couple of articles and/or texts have been examined with an eye on the use of such terms as God versus Allaah/Allah, prayer versus Salaah/Salat, alms giving versus Zakaah/Zakat, mosque versus masjid and even Islam (a traditionally accepted transliteration of????? ) versus Islaam. The researchers mainly depend on semantic analysis of religious terms in translation versus transliteration and, partly, try to make use of a questionnaire to test the impact of both techniques upon the possible addressees. The research ends with a couple of recommendations suggested by the researchers in the light of their discussions of the data and findings of the research.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".