Fall 2026

Researching the City: Qualitative Strategies

Explores and applies qualitative methods in urban geography, including data analysis and a required field course.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Fall 2010: 3.38 GPA, 61.5% A/AB (n=13 letter grades); Spring 2018: 4.00 GPA, 100.0% A/AB (n=16 letter grades); Spring 2020: 4.00 GPA, 100.0% A/AB (n=16 letter grades).

Grade history

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average GPA
letter grades
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AB
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Prerequisites

Course map

Junior standing

  • Junior standing
GEOG/URBRPL 503

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Prerequisite text tree
  • Junior standing

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Fall 2026

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Meeting source records

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Student experience

the class

Recent recorded grades — Fall 2010: 3.38 GPA, 61.5% A/AB (n=13 letter grades); Spring 2018: 4.00 GPA, 100.0% A/AB (n=16 letter grades); Spring 2020: 4.00 GPA, 100.0% A/AB (n=16 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Debates in qualitative data analysis and interpretation
  • Concrete urban research applications

Skills

  • Applying qualitative methods in urban geography
  • Analyzing and interpreting qualitative data

Grades

Latest available · Spring 2020— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2020

More grade details Grade mix, volume & source data

Not enough comparable courses for Fall 2026 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

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Student reviews

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Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

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Dataset & model

Recorded 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "9cb868c6609064bc5ef35cee03fc02af0daa84c113fdcaa8095215031b95b99f",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}