Report · Culture

Six-in-ten Americans are undecided whether Charlie Zhang is feminine

Reading

In a Verasight survey of 509 U.S. adults conducted in May 2026, 61% of Americans neither agreed nor disagreed that a person named Charlie Zhang is feminine.

About a third disagreed (34%), including 18% who strongly disagree and 17% who somewhat disagree. Another 5% agreed, with 4% who somewhat agree and 1% who strongly agree.

Topline

response scale

Topline scale

61% of Americans neither agree nor disagree that a person named Charlie Zhang is feminine.

A person named Charlie Zhang is feminine?

  • Neither agree or disagree 60.6%
  • Strongly disagree 17.5%
  • Somewhat disagree 16.9%
  • Somewhat agree 3.6%
  • Strongly agree 1.4%

2026 · base n 509 · +/- 4.6%

society

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Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Field dates
2026-05-11 → 2026-05-11
Base (unweighted)
509
Margin of error
+/- 4.6%
Module
society

Source

  • 01
    Six-in-ten Americans are undecided whether Charlie Zhang is femininereports.verasight.io/reports/spsp26

Citation

Verasight SPSP Omnibus Survey #2026-045, fielded May 11-11, 2026, N=509 US adults age 18+, +/- 4.6%.

https://reports.verasight.io/reports/spsp26#q-society-8_a

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. Each wave's specific field dates, sample sizes, and module breakdown are listed in that wave's report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
Every wave is published as a standalone report at verasight.io/reports with full instrument and methodology.
Transparency
AAPOR transparency standards.

Wave-specific methodology, full weighting variable lists, and verbatim instrument text live in each report at verasight.io/reports.