R‑Shief: critical AI for public scholarship and Civil society.
R‑Shief is a humanities‑forward platform for building and sharing datasets, tracing citational politics, and making interpretive visualizations legible. It’s designed for researchers, classrooms, and communities who treat data as contested—structured by power, infrastructures, and histories.
What this project enables
Inspired by critical media scholarship: the point isn’t to “extract insights,” but to make the conditions of insight visible—what counts as evidence, how it travels, and who benefits.
Datasets as situated evidence
Bring public archives, platform traces, and research collections into a shared space—without pretending the data is neutral.
Explore datasetsInterpretability-first AI
Contrapuntal treats visualization as argument: the goal isn’t automation, it’s legibility—what is highlighted, what is erased, and why.
Learn the approachFrom analysis to public scholarship
Make data stories that can be taught, reviewed, cited, and contested. Publish with context and provenance, not just charts.
See storiesMethods for media, not just metrics
R‑Shief supports critical research workflows: collecting, curating, annotating, comparing, and narrating across platforms and archives.
Experimental toolsAn ideology sketch
R‑Shief is built for humanities research at the scale of platforms: it treats datasets as situated artifacts, pairs them with interpretive methods, and makes analysis legible—so public scholarship can be made, reviewed, and shared.
Start from a dataset, not a prompt
R‑Shief is designed so research begins with a bounded, explicit object: a dataset with provenance. From there you can map, compare, narrate, and publish—while keeping the interpretive frame visible.
Get started in 5 steps
1. Browse datasets2. Set up your profile3. Create a dataset (social / public / uploads)5. Visualize with Contrapuntal, publish, and invite critique
© 2026 R‑Shief · Humanities-forward AI + datasets