Legalitas Ucapan Selamat Natal Bagi Umat Islam Studi Kritis Terhadap Pemikiran Quraish Shihab Dalam Tafsir Al-Misbah
Bibliographic record
Abstract
Legality Derived from the word "legal" which means legal, valid according to law. While legality itself is legitimacy, legality. So "Legality" can be interpreted as a legitimacy or validity of a law based on State Law or the ideological source of a group. M. Quraish Shihab's interpretation process in legalizing the "Merry Christmas" greeting using QS. Maryam 33 through several methods including, using "Dalalah Lafadz 'Am, Syaddud dzaraI', and the rules of Maqashidul Lafdzi fiqh 'Ala Niatil Lafidz". With the latter method he interprets who is allowed or not to say "Merry Christmas". Like other contemporary commentators in interpreting the Qur'an, he also considers harmony and harmony between religious communities. None of the classical and contemporary scholars have stated that it is permissible to say "Merry Christmas" by saying that it has been approved by Al-Qur'an. The Qur'an is even recommended using the QS argument. Maryam verse 33 as used by M. Quraish Shihab in legalizing the saying. Ulama' who allow it only consider this as a form of "Mujamalah and Muhasanah" only. Because it is seen from the interpretation of the verse that none of the scholars interprets that the verse is a verse that approves the greeting of Merry Christmas, and also by looking at the history of the "Christmas" celebration. Keywords: Legality, Merry Christmas, Muslim
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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".