Survey: Nevada and Thailand Are Most Promiscuous
Last week we talked about promiscuity and I gave you a chance to take a test to measure what psychologists call “sociosexuality”—which I referred to as promiscuity. When you took the test you didn’t get a score but instead found out the country where you would be most at home—based on your sexual proclivities. A week has gone by, and almost 10,000 people have taken the test from 110 different countries, and I have to tell you… I sure hope Finland’s immigration policies are as liberal as their views about sexuality. It turns out that a 54% of Dollars and Sex readers had a score greater than the average measure of promiscuity in Finland of 50.5. In fact, the average score on the test was a 70; exactly double the world average found by the International Sexuality Description Project.*
Promiscuity Index by State
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google.setOnLoadCallback(drawMap);
function drawMap() {
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data.addColumn('string', 'State');
data.addColumn('number', 'Promiscuity Index');
data.setValue(0, 0, 'US-AK'); data.setValue(0, 1, 64.275);
data.setValue(1, 0, 'US-AL'); data.setValue(1, 1, 73.0945);
data.setValue(2, 0, 'US-AR'); data.setValue(2, 1, 90.3958);
data.setValue(3, 0, 'US-AZ'); data.setValue(3, 1, 77.9567);
data.setValue(4, 0, 'US-CA'); data.setValue(4, 1, 76.9408);
data.setValue(5, 0, 'US-CO'); data.setValue(5, 1, 77.6149);
data.setValue(6, 0, 'US-CT'); data.setValue(6, 1, 65.9353);
data.setValue(7, 0, 'US-DC'); data.setValue(7, 1, 74.2622);
data.setValue(8, 0, 'US-DE'); data.setValue(8, 1, 62.4582);
data.setValue(9, 0, 'US-FL'); data.setValue(9, 1, 77.5803);
data.setValue(10, 0, 'US-GA'); data.setValue(10, 1, 77.4359);
data.setValue(11, 0, 'US-HI'); data.setValue(11, 1, 82.9623);
data.setValue(12, 0, 'US-IA'); data.setValue(12, 1, 61.967);
data.setValue(13, 0, 'US-ID'); data.setValue(13, 1, 52.7687);
data.setValue(14, 0, 'US-IL'); data.setValue(14, 1, 65.6537);
data.setValue(15, 0, 'US-IN'); data.setValue(15, 1, 57.1595);
data.setValue(16, 0, 'US-KS'); data.setValue(16, 1, 75.1548);
data.setValue(17, 0, 'US-KY'); data.setValue(17, 1, 71.0885);
data.setValue(18, 0, 'US-LA'); data.setValue(18, 1, 76.6356);
data.setValue(19, 0, 'US-MA'); data.setValue(19, 1, 62.9629);
data.setValue(20, 0, 'US-MD'); data.setValue(20, 1, 63.5905);
data.setValue(21, 0, 'US-ME'); data.setValue(21, 1, 75.8784);
data.setValue(22, 0, 'US-MI'); data.setValue(22, 1, 65.6881);
data.setValue(23, 0, 'US-MN'); data.setValue(23, 1, 63.464);
data.setValue(24, 0, 'US-MO'); data.setValue(24, 1, 74.9219);
data.setValue(25, 0, 'US-MS'); data.setValue(25, 1, 76.8713);
data.setValue(26, 0, 'US-MT'); data.setValue(26, 1, 74.6692);
data.setValue(27, 0, 'US-NC'); data.setValue(27, 1, 62.7666);
data.setValue(28, 0, 'US-ND'); data.setValue(28, 1, 66.1171);
data.setValue(29, 0, 'US-NE'); data.setValue(29, 1, 80.9836);
data.setValue(30, 0, 'US-NH'); data.setValue(30, 1, 63.1642);
data.setValue(31, 0, 'US-NJ'); data.setValue(31, 1, 69.2261);
data.setValue(32, 0, 'US-NM'); data.setValue(32, 1, 77.6144);
data.setValue(33, 0, 'US-NV'); data.setValue(33, 1, 93.9232);
data.setValue(34, 0, 'US-NY'); data.setValue(34, 1, 77.5622);
data.setValue(35, 0, 'US-OH'); data.setValue(35, 1, 66.442);
data.setValue(36, 0, 'US-OK'); data.setValue(36, 1, 66.6);
data.setValue(37, 0, 'US-OR'); data.setValue(37, 1, 79.8837);
data.setValue(38, 0, 'US-PA'); data.setValue(38, 1, 69.3607);
data.setValue(39, 0, 'US-RI'); data.setValue(39, 1, 90.2691);
data.setValue(40, 0, 'US-SC'); data.setValue(40, 1, 77.5954);
data.setValue(41, 0, 'US-SD'); data.setValue(41, 1, 52.2467);
data.setValue(42, 0, 'US-TN'); data.setValue(42, 1, 70.5072);
data.setValue(43, 0, 'US-TX'); data.setValue(43, 1, 73.0539);
data.setValue(44, 0, 'US-UT'); data.setValue(44, 1, 48.498);
data.setValue(45, 0, 'US-VA'); data.setValue(45, 1, 68.8455);
data.setValue(46, 0, 'US-VT'); data.setValue(46, 1, 56.23);
data.setValue(47, 0, 'US-WA'); data.setValue(47, 1, 63.3847);
data.setValue(48, 0, 'US-WI'); data.setValue(48, 1, 59.8317);
data.setValue(49, 0, 'US-WV'); data.setValue(49, 1, 55.4436);
data.setValue(50, 0, 'US-WY'); data.setValue(50, 1, 60.5817);
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// ]]>
I know that an online test is not scientific study but come on! Double the world average? Obviously, the readers of Dollars and Sex are not a random sample of the population. I can speculate that they are better educated, on average, and perhaps men are over-represented. But are either of these things enough to drive up the scores? We are all internet users—maybe that tells us something. And unlike the original survey we all speak English. Residents of the U.S. are overrepresented, but that is not driving up the average. As you can see from the map, the U.S. ranks only 30th out of the 61 countries whose results are illustrated there. Is it just that we have more sexual partners than the individuals in the original survey? Or maybe we have more liberal attitudes towards sex, without actually having more partners?
Promiscuity Index by Country
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data2.addColumn('string', 'Country');
data2.addColumn('number', 'Promiscuity Index');
data2.setValue(0, 0, 'AE'); data2.setValue(0, 1, 98.104);
data2.setValue(1, 0, 'AR'); data2.setValue(1, 1, 85.42);
data2.setValue(2, 0, 'AT'); data2.setValue(2, 1, 68.64);
data2.setValue(3, 0, 'AU'); data2.setValue(3, 1, 75.282);
data2.setValue(4, 0, 'BE'); data2.setValue(4, 1, 89.9308);
data2.setValue(5, 0, 'BG'); data2.setValue(5, 1, 46.58);
data2.setValue(6, 0, 'BR'); data2.setValue(6, 1, 65.5013);
data2.setValue(7, 0, 'BS'); data2.setValue(7, 1, 45.98);
data2.setValue(8, 0, 'CA'); data2.setValue(8, 1, 74.6537);
data2.setValue(9, 0, 'CH'); data2.setValue(9, 1, 95.22);
data2.setValue(10, 0, 'CL'); data2.setValue(10, 1, 52.386);
data2.setValue(11, 0, 'CN'); data2.setValue(11, 1, 65.8097);
data2.setValue(12, 0, 'CO'); data2.setValue(12, 1, 54.79);
data2.setValue(13, 0, 'CR'); data2.setValue(13, 1, 57.325);
data2.setValue(14, 0, 'CZ'); data2.setValue(14, 1, 101.257);
data2.setValue(15, 0, 'DE'); data2.setValue(15, 1, 75.6635);
data2.setValue(16, 0, 'DK'); data2.setValue(16, 1, 89.4716);
data2.setValue(17, 0, 'EC'); data2.setValue(17, 1, 69.055);
data2.setValue(18, 0, 'EE'); data2.setValue(18, 1, 89.5175);
data2.setValue(19, 0, 'ES'); data2.setValue(19, 1, 73.2935);
data2.setValue(20, 0, 'FI'); data2.setValue(20, 1, 90.153);
data2.setValue(21, 0, 'FR'); data2.setValue(21, 1, 84.5793);
data2.setValue(22, 0, 'GB'); data2.setValue(22, 1, 75.8398);
data2.setValue(23, 0, 'GR'); data2.setValue(23, 1, 76.3373);
data2.setValue(24, 0, 'HK'); data2.setValue(24, 1, 72.3352);
data2.setValue(25, 0, 'HR'); data2.setValue(25, 1, 38.5314);
data2.setValue(26, 0, 'HU'); data2.setValue(26, 1, 57.45);
data2.setValue(27, 0, 'ID'); data2.setValue(27, 1, 37.676);
data2.setValue(28, 0, 'IE'); data2.setValue(28, 1, 78.0282);
data2.setValue(29, 0, 'IL'); data2.setValue(29, 1, 66.6836);
data2.setValue(30, 0, 'IN'); data2.setValue(30, 1, 41.0557);
data2.setValue(31, 0, 'IT'); data2.setValue(31, 1, 71.2505);
data2.setValue(32, 0, 'JP'); data2.setValue(32, 1, 101.739);
data2.setValue(33, 0, 'KR'); data2.setValue(33, 1, 102.258);
data2.setValue(34, 0, 'LT'); data2.setValue(34, 1, 86.708);
data2.setValue(35, 0, 'LV'); data2.setValue(35, 1, 51.6333);
data2.setValue(36, 0, 'MX'); data2.setValue(36, 1, 74.9723);
data2.setValue(37, 0, 'MY'); data2.setValue(37, 1, 79.6283);
data2.setValue(38, 0, 'NL'); data2.setValue(38, 1, 63.7856);
data2.setValue(39, 0, 'NO'); data2.setValue(39, 1, 110.854);
data2.setValue(40, 0, 'NZ'); data2.setValue(40, 1, 66.9392);
data2.setValue(41, 0, 'PE'); data2.setValue(41, 1, 68.625);
data2.setValue(42, 0, 'PH'); data2.setValue(42, 1, 77.0867);
data2.setValue(43, 0, 'PK'); data2.setValue(43, 1, 45.66);
data2.setValue(44, 0, 'PL'); data2.setValue(44, 1, 74.1143);
data2.setValue(45, 0, 'PR'); data2.setValue(45, 1, 73.75);
data2.setValue(46, 0, 'PT'); data2.setValue(46, 1, 50.2433);
data2.setValue(47, 0, 'RO'); data2.setValue(47, 1, 43.1086);
data2.setValue(48, 0, 'RS'); data2.setValue(48, 1, 40.176);
data2.setValue(49, 0, 'RU'); data2.setValue(49, 1, 97.9175);
data2.setValue(50, 0, 'SE'); data2.setValue(50, 1, 79.5152);
data2.setValue(51, 0, 'SG'); data2.setValue(51, 1, 54.8413);
data2.setValue(52, 0, 'SI'); data2.setValue(52, 1, 39.1255);
data2.setValue(53, 0, 'TH'); data2.setValue(53, 1, 156.776);
data2.setValue(54, 0, 'TR'); data2.setValue(54, 1, 90.7889);
data2.setValue(55, 0, 'TW'); data2.setValue(55, 1, 60.8589);
data2.setValue(56, 0, 'UA'); data2.setValue(56, 1, 95.8333);
data2.setValue(57, 0, 'US'); data2.setValue(57, 1, 71.5969);
data2.setValue(58, 0, 'VE'); data2.setValue(58, 1, 58.592);
data2.setValue(59, 0, 'VN'); data2.setValue(59, 1, 55.8775);
data2.setValue(60, 0, 'ZA'); data2.setValue(60, 1, 82.1632);
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geomap2.draw(data2, options2);
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// ]]>
Last Friday we talked about promiscuity and happiness, and it just so happens that the data used in that survey can be used to calculate the average number of sexual partners, in the past year, of the 16,000 randomly selected Americans represented in their data. In that group 18% had no sexual partners, 70% had one sexual partner, 6% had two partners and 7% had more than three. In our group 15% had no sexual partners, 54% had one sexual partner, 10% had two partners and 14% had more than three. These results are not being driven by the fact that the data is international, in this regard the Americans look just like everyone else. So, it looks like one of the reasons the promiscuity score higher is that we (the online test takers) do have more partners on average, but is it enough to drive up the average by 35 points? If there are five points added to the measure per sexual partner, and with an average of 2 partners in the past year, that is probably not the explanation.
I don’t know how many one-night stands the average person has had (in fact I am not even sure how many I have had) but I do know that the number of sexual partners in the past year is positively correlated with the number of one-night stands (I checked, I am not making that up) so if the number of partners is higher here than the average person, then the number of one night stands is probably also higher. Ditto for expected number of future partners.I suspect though that the big driver of high scores is not actions. As a group we are pretty liberal in our views about sexuality. Thirty-five percent admit to fantasizing everyday about someone else, while only 8% said they never do. Thirty-two percent agree that sex without love is okay, with 62% giving that question score greater than 5 out of 9 (maybe that is how many men we have in the sample!). Sixteen percent said that they strongly disagreed with the statement that they could see themselves enjoying casual sex with different partners but most people were open to the idea. The same goes for feeling the need to have an emotional attachment to someone in order to enjoy having sex with them; while some people felt that was very important (17% strongly agreed) the average person choose 5 out of 9 (where 9 is strongly disagree).
So, are we more promiscuous than the subjects in the International Sexuality Description Project, I would say yes but that is being driven by some extent to having liberal views regarding sexual relationships.
So what about Finland? Is it still the top tourist destination for liberal minded Dollars and Sex readers? It is pretty high up the list along with its Scandinavian neighbours, but compared to the some of the Asian counties it is looking pretty tame. I am thinking Japan would be nice this time of year.
*To be consistent with the test done by the International Sexuality Description Project I dropped the top 1% of scores which meant dropping everyone with a score greater than 304. I also dropped duplicate tests; if there was more than one entry from the same IP address I keep the first and threw out the rest, this is about 5% of the sample.