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University of California-Los Angeles

University of California-Los Angeles's course descriptions average 67.7 on the 100-to-0 ruler: clearly left of center. Across all 100 schools, the average is 67.5, so University of California-Los Angeles reads 0.1 points further left.

Liberal (100)center (50)Conservative (0)
University of California-Los Angeles: 67.7 (likely range 66.6 to 68.8) All 100 schools: 67.5 each other school in the comparison

Where its courses fall

<1%Far left92–100
16%Left75–91
80%Center-left59–74
4%Center42–58
0%Center-right26–41
0%Right9–25
0%Far right0–8
140 plotted courses (the ones with a political framing). 100 = far left, 50 = the average American, 0 = far right.

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Underlined: words the model quoted from the description when we asked it, after scoring, to explain its score.

Furthest left

Asian American Studies 126 · Comparative Race and Indigeneity92

Ethnic & African American Studies

Seminar, three hours. Preparation: one ethnic studies course. Analysis of race and indigeneity within comparative ethnic studies framework. Examination of how Asian, Pacific Islander, Black, indigenous, and Latinx identifiers are formed in…

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African American Studies 140 · Radical Black Imaginaries: Politics, Identity, and Struggle86

Ethnic & African American Studies

Lecture, four hours. Exploration of some more powerful visions for freedom, liberation, and racial justice in African diasporic world, with focus on political struggles, intellectual movements, and creative expressions that formed part of…

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Asian American Studies 109 · Gender Violence, Policing, and Law85

Ethnic & African American Studies

Seminar, three hours. Examination of race, gender, and sexuality in modern American legal punishment, policing, and borders. Draws from feminist of color and indigenous feminist antiviolence theories to trace relationship between…

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Furthest right

None. University of California-Los Angeles has 140 left-framed courses and not one right-framed course.

Why this number, in plain words

Political lean of course descriptions. Average Framing score (0 = far right, 50 = center, 100 = far left) of the scored courses in the group.

50 is the survey-anchored center of US adults on each issue (the "moderate" place of the ANES/GSS/PRRI seven-label ruler), not the cohort midpoint; scores above 50 read leftward, below 50 rightward.

Counted: courses with a Framing score (categories L/R/B/C). The likely range (95% interval) is 66.6 to 68.8; a comparison whose range overlaps this one is not a reliable difference.

  • Most course descriptions carry no political lean at all and are not in this average; the "share described from the left" view counts them.
  • Readings are of catalog description text, not of teaching, syllabi or individual professors.
University of California-Los Angeles by department (share of courses described from the left)
DepartmentLeft-framed shareCourses
Women's & Gender Studies19.8%121view
Ethnic & African American Studies17.4%414view
Sociology7.7%155view
Anthropology3.9%152view
History3.8%320view
Political Science2.8%144view
Religious Studies2%50view
Psychology1.8%166view
English & Comparative Literature1.6%258view
Philosophy0.8%131view
Art & Art History0.5%203view
Economics0%155view

Lean (mean Framing score) is not published per department within a school; only the left-framed share is. Department rows carry no interval.

Details: exact rows, definitions and method
NameMetricValue95% intervalnscored
University of California-Los Angelesmean_bias_score67.766.6 – 68.82,269140
All 100 schoolsmean_bias_score67.567.4 – 67.7124,29010,124
Formula
SUM(bias_score) / COUNT(bias_score)
Interval
normal approximation: mean +/- 1.96 * sd / sqrt(n), sample sd (n-1); undefined when n < 2
Model / prompt / snapshot
gpt-5.6-sol · r12 (2026-10-16-le49-r12) · 6df50b10
Metric caveats
Scored courses only (L/R/B/C); N and I carry no score and are excluded, so n here is smaller than the group's course count. Scores are model readings of catalog description text against a fixed anchored definition, not teaching or syllabi. The interval covers sampling noise in the mean only; it does not represent model reading error. Every value carries a `method` label: exact_rows or histogram_midpoint.

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