Rate-Splitting Multiple Access (RSMA) is a key enabling technique for sixth-generation (6G) wireless systems due to its powerful interference management, and Reconfigurable Intelligent Surface (RIS) improves communication performance by shaping wireless propagation. However, conventional RSMA--RIS architectures employ fixed antennas, limiting spatial degrees of freedom and system performance. To address this, we propose a movable-antenna (MA) assisted RSMA--RIS framework and formulate a sum-rate maximization problem that jointly optimizes the transmit beamforming matrix, RIS reflection matrix, common-rate partition, and MA positions. After yielding a closed-form solution for common rate splitting, the problem is transformed via fractional programming (FP). Using Karush--Kuhn--Tucker (KKT) conditions, we give iterative updates for Lagrange multipliers and beamforming matrix, obtain the RIS reflection matrix via the dual problem, and determine optimal antenna positions via gradient ascent. Numerical results show that with the existence of RIS, integrating MA yields additional gains of approximately 33.3\% for SDMA and 35.6\% for RSMA.