jasoncorkill/would-you-rather-kissing-vs-sauce

Would You Rather: Kissing vs Sauce 💋🍝

The analysis in this README was written by an AI (Claude, working as Rapidata's engineering assistant), and every number was computed by a script from the data in this repo. The data itself is real: 10,000 human responses collected through Rapidata. Treat the interpretation as exploratory, not peer-reviewed.

We asked 10,000 people in 127 countries one question:

Would you rather never kiss someone on the mouth again, or never eat anything with sauce again?

Result: 53.1% would give up kissing to keep sauce (95% CI ± 1.0 pp). Globally it is close to a coin flip, but the answer depends a lot on where people live: it ranges from 35% in PT to 71% in EG.

Key findings

1. Country and culture explain far more than anything else (χ² p = 1.9e-55). The Arab world (68%) would give up kissing; Iberia (38%) would give up sauce.
2. This isn't caused by translation. In Arab countries, people who saw the task in English or French still chose "give up kissing" far more often than the global average.
3. Women give up kissing more often than men: after controlling for country, men have an odds ratio of 0.73 vs women (p = 4e-07).
4. Age has no real effect. The raw dip among 50–64 year olds comes from who is in that age group: 44% of them are European, vs 15% of 18–29 year olds. After controlling for country, no age group differs significantly.
5. Reliability score doesn't change the answer: weighted by user_score the result is 53.1%, vs 53.1% unweighted.

How the data was collected

Platform	Rapidata: responses from people using apps in Rapidata's network
Audience	Rapidata global audience, no country, language or demographic filter
Task type	Single-choice classification, two options
Responses	10,000
Localisation	The question and both answers were machine-translated into each person's app language; a neutral "?" image stood in as the task asset so no untranslated text was shown
Answer order	Randomised per person
Rapidata job	job_1VyZzsnpmgyphz
Collected	September 2026

Dataset structure

One row per response. No user identifiers are included.

Column	Type	Description
response_id	int	Row index, 0…9999
choice	string	"Never kiss someone on the mouth again" or "Never eat anything with sauce again"
gives_up_kissing	bool	True if choice is the kissing option
country	string	ISO-3166 alpha-2 country of the respondent
language	string	ISO-639-1 language the task was shown in
age_group	string / null	18-29, 30-39, 40-49, 50-64, 65+ (49% missing)
gender	string / null	Female, Male, Other (38% missing)
occupation	string / null	Self-reported occupation or education (35% missing)
user_score	float	Rapidata's global reliability score for the respondent, in [0, 1). It comes from their accuracy on known-answer tasks
region	string	Grouping used in this README: Arab world, Iberia, Other Europe, Rest of world

from datasets import load_dataset
ds = load_dataset("jasoncorkill/would-you-rather-kissing-vs-sauce", split="train")
df = ds.to_pandas()
df.groupby("country").gives_up_kissing.mean().sort_values()

A CSV copy is at data/responses.csv.

Analysis

Every percentage below is the share who would give up kissing (and keep sauce). Confidence intervals use the normal approximation. Groups with fewer than 50 respondents are left out of the tables.

Overall

Measure	Value
Gives up kissing (unweighted)	53.1% ± 1.0 pp
Gives up kissing (weighted by user_score)	53.1%
Gives up sauce	46.9%
Countries / languages represented	127 / 52

By region

Region	n	Gives up kissing	95% CI
Arab world	1,651	68.1%	± 2.2 pp
Rest of world	5,877	54.1%	± 1.3 pp
Other Europe	1,144	44.8%	± 2.9 pp
Iberia	1,328	37.6%	± 2.6 pp

χ² test of independence: p = 1.8e-67.

By country

Country	n	Gives up kissing	95% CI
EG	839	71.3%	± 3.1 pp
IQ	298	67.4%	± 5.3 pp
TH	75	64.0%	± 10.9 pp
JO	99	62.6%	± 9.5 pp
BD	230	60.9%	± 6.3 pp
DZ	230	58.7%	± 6.4 pp
PH	1,023	58.7%	± 3.0 pp
KR	133	57.9%	± 8.4 pp
CI	83	57.8%	± 10.6 pp
TR	166	57.2%	± 7.5 pp
ZA	231	55.8%	± 6.4 pp
JP	723	55.5%	± 3.6 pp
PK	494	54.7%	± 4.4 pp
VE	51	52.9%	± 13.7 pp
US	57	52.6%	± 13.0 pp
CL	59	52.5%	± 12.7 pp
PE	128	51.6%	± 8.7 pp
BR	149	51.0%	± 8.0 pp
IN	1,648	50.2%	± 2.4 pp
DE	80	48.8%	± 11.0 pp
FR	250	45.6%	± 6.2 pp
GB	192	44.3%	± 7.0 pp
BY	123	43.9%	± 8.8 pp
AT	92	42.4%	± 10.1 pp
PL	160	41.2%	± 7.6 pp
ES	1,098	38.2%	± 2.9 pp
PT	230	34.8%	± 6.2 pp

χ² p = 1.9e-55. The spread between EG and PT is 36 percentage points, far larger than either confidence interval.

By task language

Language	n	Gives up kissing	95% CI
ar	1,229	71.4%	± 2.5 pp
th	70	64.3%	± 11.2 pp
ko	136	56.6%	± 8.3 pp
tr	151	55.6%	± 7.9 pp
ja	722	55.4%	± 3.6 pp
en	4,419	53.6%	± 1.5 pp
fr	542	51.1%	± 4.2 pp
de	160	47.5%	± 7.7 pp
ru	225	44.9%	± 6.5 pp
pl	142	42.3%	± 8.1 pp
es	1,524	42.1%	± 2.5 pp
pt	370	40.3%	± 5.0 pp

χ² p = 1.3e-54. The language ranking closely follows the country ranking. Arabic is at the top, and Spanish and Portuguese are at the bottom.

Is it the translation or the culture?

If the Arabic translation were driving the effect, people in Arab countries who saw the task in another language would look like the global average. They don't:

Task language (Arab countries only)	n	Gives up kissing	95% CI
ar	1,215	71.4%	± 2.5 pp
en	281	60.5%	± 5.7 pp
fr	148	57.4%	± 8.0 pp

Arabic-language respondents lean further toward giving up kissing (χ² p = 2.1e-05), but English- and French-language respondents in the same countries still sit well above the global 53.1%. The translation may add to the effect, but it doesn't create it.

By gender

Gender	n	Gives up kissing	95% CI
Female	2,872	55.8%	± 1.8 pp
Other	1,450	52.1%	± 2.6 pp
Male	1,852	48.5%	± 2.3 pp

χ² p = 4e-06. A logistic regression that controls for country (the top 15 countries plus "other") gives men an odds ratio of 0.73 vs women (p = 4e-07), so the gap isn't explained by gender mix across countries.

Country	Female	Male	Gap (F − M)
FR	56.3% (n=103)	34.8% (n=46)	+21.5 pp
GB	47.7% (n=65)	29.8% (n=47)	+17.9 pp
PK	61.6% (n=159)	44.0% (n=75)	+17.6 pp
JP	63.2% (n=209)	49.1% (n=291)	+14.0 pp
PH	61.2% (n=294)	49.0% (n=157)	+12.2 pp
EG	75.8% (n=293)	67.8% (n=143)	+7.9 pp
IN	55.3% (n=293)	48.0% (n=394)	+7.3 pp
PT	30.7% (n=101)	27.5% (n=40)	+3.2 pp
IQ	64.6% (n=82)	65.9% (n=41)	-1.2 pp
ES	37.8% (n=328)	41.2% (n=165)	-3.4 pp

In most countries women are more willing to give up kissing than men. Where a country breaks that pattern, the table shows it.

By age

Age group	n	Gives up kissing	95% CI
18-29	1,515	54.4%	± 2.5 pp
30-39	940	55.4%	± 3.2 pp
40-49	848	54.0%	± 3.4 pp
50-64	1,057	48.0%	± 3.0 pp
65+	734	52.0%	± 3.6 pp

The raw χ² is p = 0.005, but this effect largely comes from who is in each age group. Older respondents are far more often European:

Age	Share from Iberia + Other Europe
18-29	15%
30-39	16%
40-49	25%
50-64	44%
65+	49%

After controlling for country, no age group differs significantly from 18–29:

Age group (vs 18–29)	Odds ratio	p
30-39	1.02	0.838
40-49	1.03	0.763
50-64	0.91	0.258
65+	1.10	0.320

Within each region the share is mostly flat across ages. The one outlier is Other Europe 65+ (55%, n = 168); that is a small cell, so treat it with caution:

Age	Arab world	Iberia	Other Europe	Rest of world
18-29	68%	40%	49%	53%
30-39	71%	32%	42%	54%
40-49	73%	39%	41%	53%
50-64	72%	34%	42%	52%
65+	66%	39%	55%	55%

By occupation

Occupation	n	Gives up kissing	95% CI
Unable to Work (health / disability)	89	60.7%	± 10.1 pp
Homemaker / Caregiver	167	60.5%	± 7.4 pp
Prefer not to say	304	58.9%	± 5.5 pp
Technology, Engineering & Math	52	57.7%	± 13.4 pp
Middle School	182	56.6%	± 7.2 pp
Not currently working	1,072	54.9%	± 3.0 pp
Student	1,162	53.4%	± 2.9 pp
Seeking Employment	252	52.8%	± 6.2 pp
None of these	99	52.5%	± 9.8 pp
Master's Degree	58	51.7%	± 12.9 pp
High School	304	51.0%	± 5.6 pp
Bachelor's Degree	120	50.8%	± 8.9 pp
Retired	973	49.6%	± 3.1 pp
Working	1,033	49.1%	± 3.0 pp
Skilled Trades & Industry	60	46.7%	± 12.6 pp
Services & Public Sector	105	45.7%	± 9.5 pp

χ² p = 0.026. The occupation list mixes jobs, education level and employment status, and the differences are small next to the country effect. Read it as descriptive only.

By reliability score

user_score quintiles:

user_score range	n	Gives up kissing
0.29–0.54	2,002	53.4%
0.54–0.60	2,002	54.4%
0.60–0.66	1,998	52.9%
0.66–0.73	1,998	51.3%
0.73–0.99	2,000	53.8%

χ² p = 0.337. There is no meaningful trend: careful and less careful respondents answer the same way.

Limitations

• The sample is not representative. Respondents are people using apps in Rapidata's network, not a probability sample. IN, ES, PH, EG alone make up 46% of responses. The global 53.1% is not a population-weighted world estimate. Several large countries have very few respondents: US 57, CN 11, ID 25, NG 7, MX 45, RU 0.
• Many respondents have no demographic data: 49% have no age and 38% have no gender. The age and gender analyses cover only those who reported them, who may differ from those who didn't.
• Machine translation: the wording is not identical across languages ("sauce" covers different foods in different cuisines, and "kiss on the mouth" carries different cultural weight).
• This is a hypothetical question. People answered quickly in an app, so treat the results as a gut reaction.
• No multiple-comparison correction was applied across the many breakdowns; focus on the large effects (country, region, gender) rather than individual small cells.

Citation

@misc{rapidata_kiss_vs_sauce_2026,
  title  = {Would You Rather: Kissing vs Sauce},
  author = {jasoncorkill},
  year   = {2026},
  url    = {https://huggingface.co/datasets/jasoncorkill/would-you-rather-kissing-vs-sauce}
}

Responses collected with Rapidata.