Skip to main content

GPT-4o-mini

3 runs · 3 datasets · 1 model

slug: gpt-4o-mini

0.813
Best SPS · opinionsqa

Disaggregated subgroup scorecard. Each card below is one published run for this vendor; expand the question-type and demographic-subgroup sections to see the matrix beneath the headline SPS. Where coverage permits, 95% CI bands accompany the point estimate.

What each cell measures

Each cell compares this vendor's synthetic responses against real human respondents in that demographic subgroup — published survey ground truth, not a model's guess about the subgroup. Higher = closer to how that real subgroup actually answered.

Demographic conditioning here is not stereotyping: every conditioned score is checked against what real subgroup members said, not against assumptions about them — and where the vendor's output diverges from the real subgroup, the score drops.

  • globalopinionqa — ground truth: Durmus et al. 2023, Anthropic — llm_global_opinions
  • opinionsqa — ground truth: Santurkar et al., ICML 2023 — Whose Opinions Do LLMs Reflect? (derived from Pew American Trends Panel)
  • subpop — ground truth: Suh et al., ACL 2025 — SubPOP: Subpopulation-Level Opinion Prediction

Low-n cells: cells with n < 30 are shown muted and tagged low n — suggestive only instead of color-graded; they are reported for transparency, not as findings.

CIs: "no CI — single run" marks point estimates from a single run with no confidence interval yet; treat the uncertainty as unknown, never zero.

Columns: Score = distributional parity (p_dist) restricted to the subgroup · p_cond = conditioning strength vs the unconditioned baseline · N = questions answered under that conditioning · Cov. = coverage dot derived from N (green = high, ≥100 · amber = medium, 50–99 · red = low, <50). Topic tables: SPS = Survey Parity Score for the topic · p_dist = 1 − mean(JSD) · p_rank = (1 + mean(τ)) / 2 · p_refuse = 1 − mean(|R_model − R_human|).

Multiple comparisons: with this many subgroup cells, a few extreme cells are expected by chance alone — read patterns across a dimension, not single cells.

globalopinionqa raw

raw--gpt-4o-mini--tdefault--tplcurrent--a75c2c4a

0.749 ± 0.034
SPS · 95% CI [0.713, 0.782] · n = 100
Question-type breakdown (7 topics)
Topic SPS p_dist p_rank p_refuse N
Health & Science low n — suggestive only 0.859 0.791 0.927 1.000 2
Technology & Digital Life low n — suggestive only 0.793 0.725 0.860 0.968 3
General Attitudes 0.670 0.696 0.644 0.952 11
International Relations & Security 0.656 0.655 0.657 0.964 50
Politics & Governance 0.630 0.606 0.653 0.972 22
Economy & Work low n — suggestive only 0.620 0.667 0.573 0.967 5
Trust & Wellbeing low n — suggestive only 0.407 0.356 0.458 0.980 7

Topics with N < 10 are muted and tagged "low n — suggestive only": too few questions for a stable 3-decimal score.

Not yet measured

This vendor has no demographic-conditioned runs for age, geography, education, or any other subgroup dimension on globalopinionqa. No cells are fabricated — scores appear here only when a conditioned run actually measured them.

How to submit a demographic-conditioned run →

opinionsqa raw

raw--gpt-4o-mini--tdefault--tplcurrent--ede40dcf

0.813 ± 0.008
SPS · 95% CI [0.805, 0.820] · n = 684
Question-type breakdown (10 topics)
Topic SPS p_dist p_rank p_refuse N
Health & Science 0.777 0.731 0.823 0.987 47
Media & Information 0.760 0.728 0.792 0.993 63
Trust & Wellbeing 0.752 0.726 0.779 0.995 25
Politics & Governance 0.751 0.694 0.809 0.989 40
Economy & Work 0.738 0.701 0.775 0.991 68
Social Values & Religion 0.713 0.662 0.763 0.990 37
Identity & Demographics 0.712 0.669 0.754 0.985 39
General Attitudes 0.708 0.685 0.731 0.989 190
Technology & Digital Life 0.705 0.659 0.752 0.993 26
International Relations & Security 0.703 0.655 0.751 0.988 149

Not yet measured

This vendor has no demographic-conditioned runs for age, geography, education, or any other subgroup dimension on opinionsqa. No cells are fabricated — scores appear here only when a conditioned run actually measured them.

How to submit a demographic-conditioned run →

subpop raw

raw--gpt-4o-mini--tdefault--tplcurrent--4dba4f5c

0.770 ± 0.026
SPS · 95% CI [0.743, 0.795] · n = 100
Question-type breakdown (8 topics)
Topic SPS p_dist p_rank p_refuse N
Politics & Governance low n — suggestive only 0.751 0.728 0.775 0.981 4
Health & Science low n — suggestive only 0.751 0.783 0.719 0.994 5
International Relations & Security 0.740 0.699 0.780 0.989 10
Social Values & Religion 0.671 0.606 0.737 0.985 28
General Attitudes 0.650 0.637 0.664 0.938 18
Economy & Work low n — suggestive only 0.638 0.611 0.665 0.991 9
Technology & Digital Life 0.625 0.588 0.662 0.994 25
Identity & Demographics low n — suggestive only 0.506 0.394 0.618 0.995 1

Topics with N < 10 are muted and tagged "low n — suggestive only": too few questions for a stable 3-decimal score.

Demographic subgroup scorecard (10 cells · 5 dimensions)
Dimension Subgroup Score 95% CI p_cond N Cov.
Geography (US Census region) Northeast 0.598 no CI — single run 0.038 100
South 0.601 no CI — single run 0.052 100
Education College graduate/some postgrad 0.633 no CI — single run 0.018 100
Less than high school 0.622 no CI — single run 0.078 100
Income $100,000 or more 0.616 no CI — single run 0.017 100
Less than $30,000 0.612 no CI — single run 0.071 100
Political party Democrat 0.625 no CI — single run 0.040 100
Republican 0.650 no CI — single run 0.130 100
Sex Female 0.585 no CI — single run 0.039 100
Male 0.605 no CI — single run 0.018 100
Not yet measured: this vendor has no demographic-conditioned runs for Age. Submit a conditioned run to fill in the missing dimension.
← Back to leaderboard