Worked sample · printable PDF
HUM-04 · Mechanical reasoning, historically
Connect a historical calculating/logic machine to a modern LLM claim; separate continuity from marketing.
Specialty centers · Machines & Meaning
Two printable humanities-and-AI briefs you can assign this term
Free humanities briefs about what a language model reveals — and does not reveal — about language. Students connect a historical calculating machine to a modern marketing claim without Whig history, and they measure something falsifiable about voice under AI assist. HUM-04 and HUM-01 have single-brief PDFs; every brief is in the bank PDF; the other ten are full on the page. No account. No student data leaves your school.
Non-claims about mind and meaning
Every major artifact ends with an explicit non-claim list about mind, meaning, consciousness, or authorship as essence. Measure something falsifiable when you study voice or style — or admit you are doing interpretive work without a metric. Corpus ethics: only texts you have rights to use.
How to run one
- Students choose the brief. You approve the research question, corpus rights, and measure (or interpretive frame) in writing first.
- Two scheduled checkpoints. Score with the six questions below.
- Mentor is advisory — school-supervised, never one-to-one unsupervised.
Featured packets
Featured · printable PDF
HUM-01 · Authorship after autocomplete
Design a study of voice change with AI assist; measure something falsifiable about style or revision.
Catalog (10 briefs on the page)
- HUM-02 · Corpus you can defend
Build a small, documented corpus; justify inclusion/exclusion like a digital humanist.
- HUM-03 · What tokenization erases
Show a meaning-bearing distinction that breaks under BPE/WordPiece — and why it matters for a text you care about.
- HUM-05 · Translation and loss
Compare human and machine translation on a short literary or historical passage; annotate what is lost.
- HUM-06 · Citation theater
Audit an LLM's citations on a humanities query; design a verification protocol students must follow.
- HUM-07 · Close reading vs. distant reading
Run a simple distant-reading pass, then return to close reading — show what each method cannot see.
- HUM-08 · Language ideology in prompts
Analyze how prompt wording encodes norms about "proper" language; propose ethical prompt practice for classwork.
- HUM-09 · Multilingual center brief
Study model performance across languages relevant to your program; refuse English-only conclusions.
- HUM-10 · IB / AP Research scope lock
Write the research question and method section that fits the official rubric without scope inflation.
- HUM-11 · Public humanities deliverable
Adapt the essay into a public-facing explainer (talk, exhibit text, or podcast script) that stays honest.
- HUM-12 · The claim you will not make
End with an explicit non-claim list — what your computational result does not prove about mind, meaning, or authorship.
Six-dimension rubric
- R1 — Is one text set, one question, and one claim type (empirical vs interpretive) named?
- R2 — Could another student rebuild the corpus step and method from the appendix?
- R3 — What does close reading show that the computational pass cannot?
- R4 — Are tokenization artifacts, sampling bias, and prompt effects recorded?
- R5 — Does the essay keep computational limits visible to a humanities reader?
- R6 — What does the student explicitly refuse to claim about mind, meaning, or authorship?
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