online opt-in
YouGov
YouGov Survey: Transgender Issues · Jan 22–27, 2024 · US national
Methodology
- Pollster
- YouGov commercial
- Sponsor
- YouGov
- Fielded
- Jan 22–27, 2024
- Population
- adult citizens
- Sample size
- 2,000
- Sample frame
- online opt-in
- Panel
- YouGov Panel
- Mode
- Web-based interviews; YouGov online opt-in panel, sample matched to a stratified frame
- Margin of error
- ±3% (approximately, per the YouGov release; per-item split halves are wider)
- Weighting
- Weighted to U.S. adult citizen population targets (gender, age, race, education, region, 2020 presidential vote); see the YouGov methodology statement accompanying the release.
- Geography
- US national
- Base notes
- The 40-position policy grid is a randomized split-sample framing experiment: each respondent saw one of the two framings of each of 20 issues, so per-item n is roughly 1,000. Several other batteries (11x, 14x, 16-19) were also asked of split halves. Items 1-8 and 15 were asked of the full sample (n about 2,000).
Sources
Verification note. WORDING RECOVERY SWEEP. The database carried YouGov's short chart labels (e.g. 'Banning discrimination against transgender people in employment'). The crosstab shows the fielded items are longer and materially different, and that each issue was asked as a randomly assigned affirming-or-restrictive PAIR, which the chart labels did not convey. || Crosstab PDF downloaded and machine-parsed; Total and Party ID (Dem/Ind/Rep) columns read directly from the tables and checked to sum to 99-101%. Field dates taken from the crosstab header (January 22-27, 2024); the YouGov article also references a companion fielding of January 23-26, 2024, which is the second half of the split design. The weighting text is summarized rather than quoted verbatim because the crosstab PDF does not carry the full methodology statement.
Figures below are transcribed from these documents. Where they disagree with the source, the source governs.
Questions asked (16)
employment protection for trans workers
Would you support or oppose. . . ? Of each pair of items about the same issue, each respondent was asked one, selected randomly
Banning employers from firing employees on the basis of their transgender identity
Wording notes: paired split-sample design | affirming half of the pair | frames protection as a ban on employers
neutral — the policy is stated plainly; the paired restrictive version (13J, 'Allowing employers to fire employees on the basis of their transgender identity') is the designed counterweight
Subgroup figures (9)
hate-crime law coverage for trans people
Would you support or oppose. . . ? Of each pair of items about the same issue, each respondent was asked one, selected randomly
Including protections for transgender people in hate-crime laws
Wording notes: paired split-sample design | affirming half of the pair
neutral — plain statement; paired against 13AB, 'Excluding protections for transgender people from hate-crime laws'
Subgroup figures (9)
gender-neutral restrooms in new public buildings
Would you support or oppose. . . ? Of each pair of items about the same issue, each respondent was asked one, selected randomly
Requiring all new public buildings to include gender-neutral restrooms
Wording notes: paired split-sample design | applies only to NEW public buildings, a limit the database's short label ('Providing gender-neutral restrooms') dropped
neutral — plain statement; paired against 13AD, 'Requiring all new public buildings to include sex-segregated restrooms'
Subgroup figures (9)
statutory definition of gender
Would you support or oppose. . . ? Of each pair of items about the same issue, each respondent was asked one, selected randomly
Creating a law that defines gender as a person's sex assigned at birth, rather than their gender identity
Wording notes: paired split-sample design | restrictive half of the pair | explicitly a legislative definition
neutral — plain statement; paired against 13AK, 'Creating a law that defines gender as a person's gender identity, rather than their sex assigned at birth'
Subgroup figures (9)
bathroom use by gender identity
Views on Transgender Policies -- Allowing transgender people to use bathrooms that match their gender identity, rather than their sex assigned at birth
Would you support or oppose. . . ?
Wording notes: randomized split-sample framing pair; each respondent saw only one of the two framings (paired item: 13B) | policy framed in the permissive direction | no strength-of-opinion scale; only Support / Oppose / Not sure
neutral — Each half of the pair is worded plainly, but the pair as a whole is the finding: on several issues a plurality supports both the permissive and the restrictive framing (e.g. women's refuges, 34% support allowing vs 35% support banning), which is direct evidence of acquiescence and of soft, framing-dependent opinion rather than settled preference.
Subgroup figures (9)
whether gender incongruence is biological or social in origin
Some people say their gender identity does not match the sex that they were assigned at birth. Do you think this is the result of. . . ?
A mix of both
38%
Social factors
27%
Biological factors
16%
Not sure
19%
neutral — offers a genuine 'mix of both' middle rather than forcing a binary aetiology
Subgroup figures (12)
whether transgender identity is a new phenomenon
Do you think that people feeling as if they are a different gender than the one they were assigned at birth is. . . ?
Something that has occurred in various cultures and time periods
55%
A relatively new phenomenon
27%
Not sure
17%
Wording notes: the 'relatively new phenomenon' option maps onto the social-contagion claim used in restrictive advocacy
neutral — two substantive alternatives stated with an explicit Not sure
Subgroup figures (9)
perceived level of discrimination against transgender people
How much discrimination do you think there is against people who are transgender in the United States today?
A lot
50%
A little
29%
None
8%
Not sure
14%
neutral — same wording as the Economist/YouGov April 2023 item, so the two are directly comparable
Subgroup figures (12)
whether society has gone too far in accepting transgender people
Which of the following statements comes closer to your feelings?
Our society has gone too far in accepting people who are transgender
36%
Our society has not gone far enough in accepting people who are transgender
34%
Our society has been about right when it comes to accepting people who are transgender
15%
Not sure
15%
neutral — identical wording to the Economist/YouGov tracker, so it extends that series
Subgroup figures (12)
moral acceptability: Identifying with a gender different from the gender assigned at birth
Morally Acceptable or Wrong -- Identifying with a gender different from the gender assigned at birth
Do you believe that, in general, the following is...?
Morally acceptable 13%33% Morally wrong
Wording notes: offers 'Not a moral issue', which absorbs a large share and makes the 'morally acceptable' figure far lower than in Gallup-style two-option morality items
neutral — the third 'not a moral issue' option is the right design choice but makes this incomparable with Gallup's binary morality tracker
Subgroup figures (12)
factual belief: All transgender people want to undergo gender-affirming surgery
Beliefs about Transgender People -- All transgender people want to undergo gender-affirming surgery
Do you think the following statement is...?
Probably false
30%
Definitely false
21%
Probably true
15%
Definitely true
6%
Not sure
29%
Wording notes: knowledge/misinformation item (false claim) | large Not sure share | asked of a split half of the sample
neutral — asks respondents to rate a factual claim rather than a preference; the item text itself is the claim under test, so 'loaded' language in it is the object of measurement, not a flaw
Subgroup figures (15)
agreement that a transgender woman is a woman
Identity of Transgender Men/Women -- A transgender woman is a woman
Do you agree or disagree with the following statements?
Wording notes: bare agree/disagree with no strength scale | acquiescence-prone format
neutral — an unbalanced agree/disagree statement rather than a two-sided choice; agree/disagree items of this kind carry a known acquiescence pull, though here the disagree side wins
Subgroup figures (9)
whether Joe Biden cares about transgender people's needs
How much do you think Joe Biden cares about the needs and problems of transgender people?
Some
29%
Not much
20%
A lot
17%
Not at all
15%
Not sure
19%
neutral — standard empathy battery applied symmetrically to both 2024 candidates
Subgroup figures (15)
whether Donald Trump cares about transgender people's needs
How much do you think Donald Trump cares about the needs and problems of transgender people?
Not at all
43%
Not much
17%
Some
15%
A lot
5%
Not sure
19%
neutral — standard empathy battery applied symmetrically to both 2024 candidates
Subgroup figures (15)
approval of Joe Biden's handling of transgender issues
Do you approve or disapprove of the way Joe Biden has handled transgender issues as president?
Approve 33%35% Disapprove
Wording notes: about a third answer Not sure for both men, indicating low awareness of either record
neutral — symmetric approve/disapprove asked about both 2024 candidates
Subgroup figures (15)
approval of Donald Trump's handling of transgender issues
Do you approve or disapprove of the way Donald Trump handled transgender issues as president?
Approve 31%38% Disapprove
Wording notes: about a third answer Not sure for both men, indicating low awareness of either record
neutral — symmetric approve/disapprove asked about both 2024 candidates
Subgroup figures (15)