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Fall 2026
Federal Appeals Project
LAW 912: FEDERAL APPEALS PROJECT examines federal appellate procedure, criminal law, and advanced legal research and writing for JD students.
Recorded instructors · Fall 2026 Adam Stevenson
Summary
Lectures are small, with a median of 9 enrolled students in the recorded sections.
Grade history
↗ average GPA
letter grades
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Prerequisites
Course mapDeclared in Law JD
- Declared in Law JD
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- Declared in Law JD
Professors
Fall 2026Historical instructors & teaching patterns
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Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 9 / 15 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
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Student experience
the class
Examine federal appellate procedure, substantive and procedural federal criminal law, and advanced legal research and writing techniques. Emphasis is placed on the strategic and ethical skills required to represent a client in a federal direct criminal appeal, including issue selection, standards of review, record analysis, and persuasive brief writing. Navigate practice before the Seventh Circuit Court of Appeals and use analytical tools essential to effective client-centered appellate advocacy.
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Sources & history
UW–Madison
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Selected offering source records
Federal Appeals Project
Recorded 2026-09-07Raw records
[
{
"run_id": "20260907T155543-ce3781c4",
"semester": "1272",
"observed_at": "2026-09-07 15:55:43.033547+00:00",
"offering_id": "1272:528:027379",
"course_id": "LAW 912",
"course_uid": "course_70eb8a1e8bcd4e93e5f25e88",
"term_id": "1272",
"source_course_id": "027379",
"source_subject_id": "528",
"title": "Federal Appeals Project",
"credits_min": 2,
"credits_max": 2,
"typically_offered": "Not Applicable"
}
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Madgrades
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Explore recorded gradesModel outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "95bc218bfac65d8bcf060722131970e533215819bf0e6f371fe201a10720af33",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}