Nonlinear tracing of conceptual lineages by reading texts, theories, events, and artifacts through one another to map how differences, inheritances, and exclusions take shape and matter over time, and how ideas co‑compose one another through crossings rather than through singular origins.
Diffractive Genealogies trace the lineage of ideas through intersecting, non-hierarchical networks. They adapt the critical craft of genealogy to diffractive method. Genealogy, following Foucault, examines how concepts and practices emerge from contingent histories rather than from linear progress or fixed origins. Diffraction, after Haraway and Barad, reads phenomena through one another to make patterns of interference perceptible. Woven together, diffractive genealogies follow how concepts take form across entangled lineages, showing where ideas intensify, split, or are cut away in the making of what later appears as coherent theory or practice. Rather than building a single family tree, a diffractive genealogy composes a set of situated encounters across sources and moments—feminist technoscience, new materialisms, affect theory, disability studies, decolonial critique, media and platform studies—attending to the effects of those encounters on what becomes thinkable and doable. In this mode, the historian’s archive and the researcher’s apparatus are participants in the story. The method foregrounds which strands get amplified as “canonical,” which are backgrounded or erased, and how those patterned cuts continue to shape present possibilities for pedagogy, authorship, and agency.
In Haraway’s terms, diffractive genealogies are ways of “staying with the trouble” by following inheritances as knots rather than lines. They are partial and accountable mappings that track how material arrangements, such as laboratories, classrooms, platforms, and policies, co-constitute ideas, and how ideas travel with attachments and exclusions. With Barad’s agential realism, the work of genealogy is not only descriptive but also performative: assembling archives, composing reading encounters, and choosing analytical lenses are agential cuts that reconfigure the phenomenon under study. Diffractive genealogies therefore make visible how power, affect, and apparatus shape the very histories that ground research, while also offering a method to reconfigure those histories toward more just and generative futures.
Diffractive genealogies align with postqualitative commitments to inquiry as world-making and with posthumanist attention to distributed agency. They treat histories as material-discursive practices rather than as background context, and they operationalize new materialist sensibilities by tracking how concepts condense through bodies, tools, infrastructures, and texts. Methodologically, this approach privileges composing over coding, tracing relations over isolating variables, and crafting situated reading encounters that surface how exclusions and inheritances continue to do work in the present. It clarifies ethical stakes by making the researcher’s apparatus—curation of sources, theoretical lenses, analytic moves—explicit and accountable.
Diffractive genealogies help surface how current debates about AI and writing inherit older anxieties about authorship, originality, and mechanical assistance, from the typewriter and word processor to spell-check, grammar checkers, and search engines. Reading policy memos through classroom practices, media narratives through instructors’ reflective journals, and platform affordances through assessment rubrics can reveal how particular framings of “cheating,” “creativity,” and “voice” crystallize from intersecting histories of assessment regimes, intellectual property discourse, labor expectations, and platform design. This approach also illuminates how affect travels across genealogies: for example, how earlier moral panics about plagiarism inflect today’s fear or excitement around model-generated prose, and how those affective inheritances shape classroom atmospheres and feedback practices. Practically, diffractive genealogies support the design of assignments and assessment that acknowledge these patterned inheritances, making room for more responsive, situated definitions of collaboration, attribution, and learning in AI-entangled writing courses.