A few years back someone had created a website called the Female Delusion Calculator. Using data collected from surveys conducted by the United States Census Bureau and National Center for Health Statistics (NCHS), the website claimed it could calculate the chances of a woman meeting the man of her dreams in the United States.
How? Single women would input the desired age range, height range, race, and minimum acceptable income of their ideal male partner and the website would then calculate the proportion of men of that race, height and income level within the age range you specified. The website would also rank how “delusional” your preference was, by assigning you one to five bags of kitty litter. The higher or more specific your standards were the more likely you were to become a lonely old cat lady. In the words of the creator…
How did I come up with the Female Delusion Calculator idea?
During my “dating career” as a man living in North America I couldn’t help noticing that women often have unrealistic expectations. They see themselves being passed around by those high quality men they feel entitled for, failing to realize those few men are in high demand. Time passes, options shrink, their standards don’t change and they wonder why they are still single.
The stats can prove there’re not enough high quality men for every girl out there.
The Female Delusion Calculator is a tool that can help women discern what is realistic from what is highly unlikely.
Enjoy!
The website was obviously made in bad faith and quickly went viral among its true intended audience, which was not single women but bitter men. The terms they use vary, but if you’ve spent some time online you’ve likely encountered these types of people. But were the statistics generated by this calculator accurate? Yes. So does that make the conclusions the Calculator puts forward true? No. To prove this let’s use the Calculator to generate the odds of marriage for a fictional user.
Amy is a 25-year-old Asian-American woman. She wants to calculate the odds of meeting her ideal man. Her requirements are quite modest. He must be between the ages of 25 and 30, unmarried, and of Asian racial ancestry. The calculator states, “according to statistical data, the probability a guy of the U.S. male population ages 25 to 30 meets your standards is 5.3%.” It goes on to assign her a delusion score of 3 out of 5 bags of kitty litter, an “aspiring cat lady”. Pretty depressing considering we didn’t even include a height or income requirement, and forget about the many metrics this website doesn’t track like physical appearance, hobbies, lifestyle and charisma. Add that stuff in and the quest for Amy’s compatible partner starts to seem impossible.
But should our fictional romantic Amy be concerned by that fact that just 5% of men match her specifications? No, because even though that figure is technically true it’s entirely irrelevant to any real-world matchmaking considerations. The mistake this website makes is assuming people operate in a singular marriage (or dating) market, where everyone has an equal shot with everyone else. In the real world, the marriage market is a myth, and the assumption that it exists is why so many of the conclusions drawn from statistics pertaining to dating, relationships and marriage are so inaccurate.
The Myth of the Marriage Market
The marriage market is a concept that applies economic theories of supply and demand to the process in which people are matched with one another (dating, relationships, and marriage). In an era, where relationship statistics have become significantly more common, analyses of personal matchmaking woes are increasingly be understood and analyzed through marriage market supply and demand logic. The problem is, most of the conclusions drawn from marriage market logic are inaccurate because they assume we all operate with a singular market. In the real world we actually operate in tens of thousands of mostly, but not entirely, separate marriage markets. Each one the product of a unique combination of factors including age, race, ethnicity, religion, religiosity, language, income, education, geographic location, hobbies, physical attributes, disability status and sexual orientation. Each one of these marriage pools experiences its own unique trends and demands. Overarching trends, like an economic recession, may still exert pressure across the markets.
Going back to the Female Delusion Calculator, though the calculator is correct in identifying that only 5% of American men aged 25 to 30 are unmarried Asians, it is wrong in suggesting that Amy is unrealistic in her expectation to meet a man like that because they make such a small fraction of the US population. The Calculator assumes everyone has an equal chance of meeting and attracting everyone else, making the small number of Asians in USA a real problem. But, thanks to assortative selection we attract and gravitate towards people who share the same characteristics as ourselves, leading to the creation of distinct marriage pools of people of similar qualities and expectations. Chances are twenty something Asian men make up the majority of Amy’s hypothetical marriage pool. And the phenomenon of assortive selection and the distinct marriage pools they produce isn’t just limited to obvious distinctions like race.
Of course I don’t doubt that there are some people, men and women, with unrealistic expectations for their ideal partner. But it would be impossible to determine whether those expectations are realistic or not without first taking into consideration the attributes of that person. Marrying a doctor isn’t hard if you’re also a doctor. In fact, 40% of married physicians, in the USA, are married to other physicians. This replicates for almost any trait you can imagine. The Calculator falls short because it assumes that a male doctor has an equal likelihood of ending up with either a female doctor and a female cashier.
But it’s not just the Calculator that’s inaccurate. In general, high level statistics on dating, relationships and marriage are often inaccurate because they are the aggregate of numerous independent trends occurring in mostly separate marriage pools. This creates issues when we to attempt generalize conclusions drawn from this data to individuals who are operating in unique marriage pools. These inaccurate conclusions are made by pretty much everyone, from experts and academics to anonymous posters online.
Why This Matters?
Anthropologists have known for quite some time that that the notion of a singular, hom*ogenized marriage market is a fallacy. As the French demographer Christophe Guilmoto explains:
Demographic forecasts are commonly based on large administrative units and pay no attention to local heterogeneity or social entities [..] and they ignore regional, social or ethnic configurations.
When applied to marriage patterns we see that:
The marriage market is in fact an ongoing process of unification of local marriage networks in which individual characteristics — typically, age, size, income, education and assets — are expected to gain ascendency over collective attributes of patrilineage and community. The transformation is still incomplete, especially in India, and there is hardly a unified, competitive marriage market at the national or even regional level. This is a domain where only sociologists and anthropologists can dispel the demographers’ simplification. They need to describe in particular how the marriage squeeze may force communities to expand gradually their endogamous boundaries — that is, to open up marriage markets in order to lessen the crisis.
Demography is limited by the quality and detail of statistics collected, which even when accurate, are reductionist in nature. No census, no matter how detailed, can capture the depth of experiences taking place in any society. It is unsurprising then, that it was anthropologists and sociologists, whose fields are built on ethnographic field work, that first identified that oversimplification marriage market explanations came with. Though Guilmoto references India, this phenomenon is applicable globally. Even in the United States, research shows marriages tend to happen between people with similar levels of income, education and social values. Interracial marriage is on the uptick, but even here there’s nuance. For example, interracial marriage rates for U.S. born Asians is significantly higher than that of Asian immigrants, suggesting that cultural assimilation is a prerequisite for high levels of interracial marriage.
Unfortunately, though experts in certain fields such as economics, security analysis and demography sometimes fail to consider this reality and instead draw conclusions and make predictions based on aggregated data collected at the national or sub-national level. This can result in inaccurate predictions.
For example, in the 1990s when India’s gender imbalance gained international recognition as a major demographic issue, some academics began predicting that imbalance could have the unintended consequences of eliminating dowries as a requirement for marriage. For context, despite being illegal, the majority of marriages in India involve a dowry, in which the bride’s family transfers money, assets or gifts to the groom’s family in order proceed with the marriage. This cultural practice frequently results in exploitation and abuse and is also a major factor behind why many Indian families have chosen to abort female fetuses.
Demographers assumed that a shortage of brides would result in increased competition for a bride leading bride seekers to abandon the requirement for a dowry in order to seem more enticing to potential prospects. Intuitively, it makes sense. But it didn’t pan out in reality. Instead, dowries continue to climb to record highs, even in districts with the worst gender imbalances.
Ethnographic field work has revealed that the surplus of men, caused by the sex-selective abortion of girls in India, has resulted in a major marriage squeeze, particularly in the North Indian states of Punjab and Haryana. But not all men, have been equally impacted by this imbalance.
In a culture, where female participation in the labor force was discouraged, the financial well being of a woman was entirely dependent on her husband. The dowry system in India, operates as a hypergamous strategy families use to secure well-off, upwardly mobile grooms for their daughters. As the shortage of brides became more acute, low-income men, who were most effected began to drop the demand for a dowry in order to make themselves more enticing. Unfortunately, for many would-be brides and their families these men, because of their low socioeconomic status and lack of upward mobility were not viewed as potential suitors right from the start. These men existed in a marginalized marriage pool defined by an acute shortage of would-be brides who instead were using dowries to land a husband in a superior income bracket. For these families of would-be brides, the competition for upwardly mobile husbands was fierce, which when combined with growing income disparities, led to the rapid rise in inflation.
Had India really operated as a singular marriage market, a surplus of men would have likely led to the elimination of dowries, as demographers predicted. However, as we now know the families of would-be brides paying exorbitant dowries and the men waving the requirement for dowries belong to two distinct marriage pools, never interacting.
However, the dangers of the marriage market don’t simply end at bad demographic prediction making. A failure to recognize the heterogeneity of the real-world marriage market has in the past led to ineffectual policy decision making. The end result being, pouring millions of dollars into well meaning programs that address the wrong issues.
Few people know that under the Bush administration made rebuilding the nuclear family within the American lower class a major policy priority. Worried, rightly, that the high rates of single motherhood, divorce and familial breakdown would permanently damage the lower class’s chance for upward mobility, the Bush Government took a page out of the handbook of couple’s therapists and began devising programs that sought to teach unwed low-income parents the relational skills needed to build successful long-term relationships. Did it work? No.
The Bush administration had made the mistake of assuming that the marriage market for low-income Americans mirrored the realities of the marriage market for middle- and upper-class Americans. Anthropologists, familiar with American lower class knew this wasn’t the case. Deindustrialization, poverty, addiction, mass incarceration and a higher level of mortality and created a marriage market defined by an extreme shortage of marriageable men. This left low-income women with little choice but to take the plunge with men who were fundamentally ill-equipped to succeed in a long-term relationship. Marrying better off men was not an option, as marriages in the US are highly stratified by income. In short, these relationships were not breaking down due to a lack of communication or because of overbearing in-laws. They were breaking down due to chronic unemployment, addiction, domestic violence, criminal activities, chronic infidelity and the stress poverty places on a relationship. Had the U.S. Government’s marriage intervention strategies taken this into consideration they would’ve probably been better equipped to deal with the actual challenges facing low-income couples and single mothers.
Conclusion
An overarching theme of this blog is highlighting the shortcomings of demographic predictions and the consequences these have on the real world. As demographic challenges like low fertility, migration and population aging increasingly enter the mainstream consciousness we are seeing more public discussion on these issues. I welcome this, but caution readers that predictions made from high level statistics and personal experiences are prone to inaccuracy, tunnel vision and ultimately alarmism.
