Ācāra () is a concept used in the context of Classical Hindu law that refers to the customary laws or community norms of a particular social group. These community norms are delineated and put into practice by people who have earned the respect of those within each individual group, such as a community leader or elder. Although in Dharmaśāstra the ideal person who defines the ācāra of a particular place is dictated as one who knows the Vedas or is “learned”, in actual practice this role is often deferred to group leaders along with Vedic scholars. Ācāra is theologically important in Hindu law
Ācāra () is a concept used in the context of Classical Hindu law that refers to the customary laws or community norms of a particular social group. These community norms are delineated and put into practice by people who have earned the respect of those within each individual group, such as a community leader or elder. Although in Dharmaśāstra the ideal person who defines the ācāra of a particular place is dictated as one who knows the Vedas or is “learned”, in actual practice this role is often deferred to group leaders along with Vedic scholars. Ācāra is theologically important in Hindu law because it is considered, along with the Vedas (Śruti), and Smriti (traditional texts such as the Dharmaśāstra literature), to be one of the sources of dharma. Particular regional ācāra is believed to be canonized in Dharmaśāstra texts; however scholars differ on the source for the actual accounts found within these texts.
==Ācāra as customary law== Customary law within the context of Hindu law is defined as akin to the community norm of a particular region. This form of law encompasses laws that are actually applied to daily life, as opposed to theological laws canonized in texts which are accessible for only a small proportion of the population. In this sense, customary law represents the actual practice of law in classical Hinduism, while laws found in the Vedas, , and śruti literature represent the theoretical practice.
Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).