# Probability of finding true love

The concept of true love has been invented by poets and other exaggerators. Evolutionarily, the optimal strategy is to settle with a good enough partner, not to seek the best in the world. But suppose for the sake of argument that a person A’s true love is another person B who exists somewhere in the world. What is the probability that A meets B?

There is no a priori reason why A and B have to be from the same country, have similar wealth or political views. Isn’t that what poets would have us believe – that love knows no boundaries, blossoms in unlikely places, etc?

Given the 7 billion people in the world, what fraction of them does a given person meet per lifetime? Depends on what is meant by “meets” – seeing each other from a distance, walking past each other on the street, looking at each other, talking casually. Let’s take literally the cliché “love at first sight” and assume that meeting means looking at each other. A person looks at a different number of people per day depending on whether they live in a city or in the countryside. There is also repetition, i.e. seeing the same person multiple times. A guess at an average number of new people a person looks at per day is 100. This times 365 times a 70-year lifespan is 2555000. Divide 7 billion by this and the odds of meeting one’s true love are thus about one in three thousand per lifetime.

Some questionable assumptions went into this conclusion, for example that the true love could be of any gender or age and that the meeting rate is 100 per day. Restricting the set candidates to a particular gender and age group proportionately lowers the number of candidates met and the total number of candidates, so leaves the conclusion unchanged.

Someone on the hunt for a partner may move to a big city, sign up for dating websites and thereby raise the meeting rate (raise number met while keeping total number constant), which would improve the odds. On the other hand, if recognizing one’s true love takes more than looking at them, e.g. a conversation, then the meeting rate could fall to less than one – how many new people per day do you have a conversation with?

Some people claim to have met their true love, at least in the hearing of their current partner. The fraction claiming this is larger than would be expected based on the calculations above. There may be cognitive dissonance at work (reinterpreting the facts so that one’s past decision looks correct). Or perhaps the perfect partner is with high probability from the same ethnic and socioeconomic background and the same high school class (this is called homophily in sociology). Then love blossoms in the most likely places.

The top journals publish a similar number of articles as decades ago, but there is a much larger number of researchers competing to get their work into a top journal. Correspondingly, it is more difficult over time to get a paper into a given journal. If articles are analogous to currency in the academic world, then this would be deflation: the value of the currency rises over time. If articles are like goods and services, but research effort is the currency that buys them, then there is inflation, because the amount of currency required to buy a given good rises.

The correct comparison between publications in different decades would take into account the increasing difficulty of publishing in a given journal. Instead of comparing papers in the top n journals, a better metric is papers in the top x percent of journals (accounting for the possibly expanding size of each journal). Similarly, being the number one researcher among a thousand in 1901 is less impressive than being the best among a million in 2001. Again the right comparison is by percentile rank, not by “top n” status.

The norms and metrics in academia are largely made by senior, established researchers. If people do not completely account for the deflation, then the top academics benefit from the increasing difficulty of publishing in the top n journals combined with the metric that counts the top n, not the top x percent. The research of old academics that was published in the top n long ago looks the more impressive the more difficult it is nowadays to get a paper into the top n. Comparison by percentile rank would correct for this artificial advantage, so the established members of the profession would not seem as high-achieving relative to new entrants.

A similar change in difficulty has occurred in getting accepted as a student in the top n universities, or getting hired as faculty in these. The right comparison to the students or faculty decades ago would compare the top x percent of universities, with the appropriate correction if the universities have expanded their enrollment or number of jobs.

# On photos at tourist attractions

At every tourist attraction, there are numerous people taking pictures of the attraction, themselves and their companions. The same photos have been taken thousands of times before and are available on the internet. It would save a lot of time for people overall if someone wrote a computer program that photoshops a person or group into these pictures. Basically, pick a location of which there are photos available online and load some pictures of yourself into the program, which returns photos of you at this place. With this, everyone can skip the photoshoot at the tourist sites, save money on the camera(phone) and still obtain all the generic tourist photos they would have had under the current system.

The next step for attractions that consist of sight and sound only is to experience them through virtual reality goggles instead of actually going there. It is more environmentally friendly, safer and cheaper this way. Most tourist attractions fall into the visual-auditory category, e.g. architecture, museums, monuments, some of nature tourism.

Technological advances are required before tourist attractions that rely on smell, taste or touch (physically doing something, e.g. surfing) are replaced with virtual reality.