Computational scaffolding for multiplicity: Systematic management of multiple perspectives in qualitative research

Contemporary qualitative psychology increasingly embraces multiplicity, yet methodological frameworks remain designed for single-perspective analysis. Current approaches typically pursue integration, flattening rather than leveraging multiplicity. This commentary argues for computational scaffolding as infrastructure for coordinating multiple perspectives without reducing complexity to algorithmic simplicity. Computational scaffolding involves using computational tools to support, organise, and coordinate interpretive work across multiple perspectives, data sources, and time, whilst maintaining human interpretive control. Rather than replacing human interpretation, computational tools can help manage disagreement, temporal complexity, and multi-source data, reframing multiplicity as a fundamental feature of psychological phenomena requiring methodological support to leverage its explanatory potential.