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Learn · Attraction without mythology

Your ideal-partner list versus who you click with

Lesson 3 of 7 in this module · about 7 minutes · Romantic communication

The idea

Ask almost anyone what they want in a partner and they can answer at once. The research finds a gap: the description still does a poor job of predicting whom people end up drawn to.

Surveys across dozens of countries find average differences in stated preferences. A 1989 study covered 37 samples, and a 2020 replication covered 45 countries and 14,399 people. In both, men on average rated a partner’s attractiveness and youth as more important, and women on average rated financial prospects and older age as more important 1. The two groups overlap heavily, countries vary, and the findings describe heterosexual pairings as studied 1. They are tendencies in groups and say nothing about what any one person wants, since no one is a group average 1. The surveys recorded answers to questions, not choices 1.

In one speed-dating study, people described the usual sex differences when they listed their ideal partner. Their ideals, measured beforehand, then failed to predict whom they wanted in person 2 3. The attractiveness and earning prospects of the people they actually met predicted desire about equally for both sexes 3. A 2014 review likewise finds that ideals predict outcomes only in some contexts and with some measures 2.

In a pair of lab experiments, matching a written profile to a person’s ideals raised interest, and after a live interaction that effect vanished 3. The authors suggest that people may not have good insight into what draws them, but that was not tested directly 3. Two further results fit. Questionnaire answers about one’s own traits and preferences, given before meeting, predicted who tends to like or be liked in general, not how much one person liked one particular partner 4. And in one large dataset, speed daters who faced many possible partners leaned more on quickly visible traits such as height and weight, and less on slower-to-learn ones such as occupation and education 5. That is a single dataset from one paper, and it is Plausible, not settled 5.

Ideals are not useless: they can predict outcomes at other stages, such as how someone evaluates a current partner 3. Most of the evidence comes from speed-dating events and labs, largely with students and largely from one research group, so independence is limited 3.

Why it matters

The list tells you about your expectations before you met her. The authors of these studies suggest that traits that looked decisive on paper may be reinterpreted in person 3. So a list is a weak guide to how you will respond to this person.

What it looks like

Example

Your list says outdoorsy and ambitious. At a friend’s barbecue you end up talking with Mina, 33, who works part-time at a library and has never hiked. You ask, “What do you do when you’re not working?” She tells you about her choir. An hour passes, and you are curious to hear more. You stop checking her against the list.

The same moment, handled the other way

Counterexample

Same barbecue. Mina says she works part-time and has never hiked. You check her against your list, decide she does not fit, and drift off mid-answer.

A list is made before you meet someone, so it tells you what you expected, not how you will respond to her.

The one thing to remember

The rule

Keep your non-negotiables, then find out in conversation how this person is, not whether she matches your list.

Non-negotiables such as honesty and kindness are about how you want to live. Hold the rest loosely. Don’t conclude that someone is out of reach because you don’t match a typical list, and don’t conclude that matching her stated preferences means she will like you. A stated preference is not a decision about you.

Try it now

Item 1 of this lesson’s set: Averages and the person in front of you.

Open the exercise set

In the real world (optional)

If you like, write down what you want in a partner. Then think of a conversation you enjoyed for an hour or more, and ask whether what made it good is on that list.

What this doesn’t tell you

It does not show that preferences are meaningless, and it does not tell you which traits to look for. It cannot say whether your list works for you, only that stated lists as a group predict poorly after meeting. It may not hold everywhere, since most of the evidence comes from US student and speed-dating samples 2 3.

Why do we believe this?

Each numbered mark in the text opens the evidence behind that sentence. Every claim in this course carries one of five labels.

Well supported
A meta-analysis or several independent studies agree, with no serious failure to replicate.
Supported with caveats
Several studies agree, with stated limits such as student samples or lab settings.
Plausible
One study, or indirect evidence from a nearby question.
Speculative
An idea or argument that hasn't been directly tested.
Marketing claim
Something a seller says about their product, without published evidence.
  1. Well supportedIn surveys across dozens of countries, men on average rate a partner's attractiveness and youth as more important, and women on average rate a partner's financial prospects and older age as more important.

    Why this label

    A meta-analysis or several independent studies agree, with no serious failure to replicate. A 1989 study of 37 samples and a 2020 replication in 45 countries (N=14,399) found the same direction of average difference. The two sexes overlap heavily and countries vary, so these are tendencies in groups and say nothing about what any one person wants.

    What it does not show

    • Stated preferences in questionnaires, not choices; see the next claims.
    • Samples are volunteers and often students; the 1989 study is decades old.
    • Effect sizes were not read here; averages hide large overlap.
    • Concerns heterosexual pairings as studied; not a claim about what women or men as a group 'want'.

    Who it applies to

    A pattern across groups of people, not a statement about any one person.

    Sources

    • Buss, D. M. (1989). Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures, Behavioral and Brain Sciences.
    • Walter, K. V., Conroy-Beam, D., Buss, D. M., Asao, K., Sorokowska, A., Sorokowski, P., Aavik, T., Akello, G., Alhabahba, M. M., Alm, C., Amjad, N., Anjum, A., Atama, C. S., Atamtürk Duyar, D., Ayebare, R., Batres, C., Bendixen, M., Bensafia, A., Bizumic, B., Boussena, M., Butovskaya, M., Can, S., Cantarero, K., Carrier, A., Cetinkaya, H., Croy, I., Cueto, R. M., Czub, M., Dronova, D., Dural, S., Duyar, I., Ertugrul, B., Espinosa, A., Estevan, I., Esteves, C. S., Fang, L., Frackowiak, T., Garduño, J. C., González, K. U., Guemaz, F., Gyuris, P., Halamová, M., Herak, I., Horvat, M., Hromatko, I., Hui, C. M., Jaafar, J. L., Jiang, F., Kafetsios, K., Kavčič, T., Kennair, L. E. O., Kervyn, N., Khanh Ha, T. T., Khilji, I. A., Köbis, N. C., Lan, H. M., Láng, A., Lennard, G. R., León, E., Lindholm, T., Linh, T. T., Lopez, G., Van Luot, N., Mailhos, A., Manesi, Z., Martinez, R., McKerchar, S. L., Meskó, N., Misra, G., Monaghan, C., Mora, E. C., Moya-Garófano, A., Musil, B., Natividade, J. C., Niemczyk, A., Nizharadze, G., Oberzaucher, E., Oleszkiewicz, A., Omar-Fauzee, M. S., Onyishi, I. E., Özener, B., Pagani, A. F., Pakalniskiene, V., Parise, M., Pazhoohi, F., Pisanski, A., Pisanski, K., Ponciano, E., Popa, C., Prokop, P., Rizwan, M., Sainz, M., Salkičević, S., Sargautyte, R., Sarmány-Schuller, I., Schmehl, S., Sharad, S., Siddiqui, R. S., Simonetti, F., Stoyanova, S. Y., Tadinac, M., Varella, M. A. C., Vauclair, C. M., Vega, L. D., Widarini, D. A., Yoo, G., Zat’ková, M., Zupančič, M. (2020). Sex differences in mate preferences across 45 countries: A large-scale replication, Psychological Science.
  2. Supported with caveatsWhat people say they want in a partner often fails to predict who they actually respond to when they meet.

    Why this label

    Several studies agree, with stated limits such as student samples or lab settings. In a speed-dating study, people showed the usual sex differences when describing an ideal partner, but those ideals, measured beforehand, did not predict whom they wanted in person. The 2014 review likewise finds ideals predict outcomes only in some contexts and measures.

    What it does not show

    • Core evidence is one speed-dating sample (largely US university students) plus a review.
    • Self-reported interest after brief meetings, not long-term choice.
    • Some preference measures predict better than others.

    Who it applies to

    A pattern across groups of people, not a statement about any one person.

    Sources

  3. Supported with caveatsWhat people say they want in an ideal partner does a poor job of predicting who they actually feel drawn to after meeting someone in person.

    Why this label

    Several studies agree, with stated limits such as student samples or lab settings. Ideals reported before a speed-dating event did not predict real desire at the event, and in lab experiments, matching a written profile to someone's ideals raised interest, but the effect vanished after a live interaction. The traits that are decisive on paper are reinterpreted when you meet the person.

    What it does not show

    • Mainly speed-dating and lab samples (largely students, plus one middle-aged adult longitudinal sample), largely from one research group, so independence is limited.
    • Ideals can predict outcomes in other stages, such as evaluating a current partner, per the review and the longitudinal study.
    • Self-report of preferences and desire; people may lack introspective access, which is the authors' interpretation, not directly tested here.

    Who it applies to

    A pattern across groups of people, not a statement about any one person.

    Sources

  4. Supported with caveatsBefore two people meet, their questionnaire answers about their own traits and preferences predict who tends to like or be liked in general, but not how much they will like one particular partner.

    Why this label

    Several studies agree, with stated limits such as student samples or lab settings. In two speed-dating studies, machine-learning models predicted part of each person's general tendency to desire or be desired, but none of the unique desire for a specific partner. A preregistered seven-month study of singles found only modest support for specific perceiver-by-target compatibility and none for matching on ideal preferences.

    What it does not show

    • Two speed-dating samples of romantically unattached people, plus a seven-month study of singles with a different design; largely the same research group.
    • Unpredictable from the measures used does not mean random; other measures could predict compatibility.
    • Self-report predictors collected before meeting; short four-minute dates.
    • Population-level: it cannot tell any individual how a given person will respond to them.

    Who it applies to

    A pattern across groups of people, not a statement about any one person.

    Sources

  5. PlausibleWhen speed daters faced many possible partners, they leaned more on quickly visible traits such as height and weight and less on slower-to-learn traits such as occupation and education.

    Why this label

    One study, or indirect evidence from a nearby question. Across 84 events and 3,738 people, larger choice sets shifted attention toward traits that are fast to assess, consistent with limits on how much information people can process in a few minutes.

    What it does not show

    • One large dataset analysed in one paper; abstract-level reading only.
    • Observational events with self-selected participants; heterosexual events likely but not checked.
    • Real-life choice overload in everyday settings may differ.

    Who it applies to

    A pattern across groups of people, not a statement about any one person.

    Source

More practice

The rest of the set, Evidence check: stated preferences and real attraction: 4 items, about 4 minutes. Decide what the evidence supports, and how well. Open the exercise set.