
This article analyses the contribution of ‘Abd Allah ibn Bayyah’s approach in the development of minority fiqh, particularly within the context of reconstructing Islamic law for Muslim minorities in Western countries. Ibn Bayyah is recognised as a neo-traditionalist striving to reconstruct Islamic law with an innovative approach to meet the needs of these minority groups. This research adopts a descriptive- analytical approach to comprehend the concepts introduced by Ibn Bayyah. In his efforts, Ibn Bayyah employs several new approaches, including the utilisation of verification of the hinge (taḥqīq al-manāṭ) to understand reality, weighing weaker opinions (al-qawl al-ḍa’īf) while considering communal welfare (maṣlaḥa), connecting the objective of Sharia (maqāṣid al-sharī’a) with legal theory (uṣūl al-fiqh), and optimising the Islamic legal maxims (al-qawā’id al-fiqhiyya). The article delineates the significance of the new approaches introduced by Ibn Bayyah in the context of minority fiqh development and their impact on Islamic legal thought for Muslim minorities in Western countries. It is anticipated this analysis will provide profound insights into the new paradigm in addressing legal challenges faced by Muslim minorities within the social and legal context of the West.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
