Ben Gelbart, Ph.D.
Computational Approaches to Affective Science
. In my research, I use computational modeling and large-scale cross-cultural surveys to understand the cognitive architecture of romantic jealousy and romantic love.
Publications:
Jealousy Decreases as Rival Number Increases: Preregistered Tests Differentiating Between Functional and Intuitive Views
Abstract: Intuition and theory alike suggest that romantic jealousy should track the “amount” of cheating, with jealousy increasing as the number of affair partners increases. A functional account—conceptualizing romantic jealousy as an adaptation for managing the relationship-relevant fitness threats posed by romantic rivals—suggests instead that jealousy should track the implications entailed by infidelity. In this view, repeated infidelity involving a single affair partner may imply greater emotional involvement than the same number of encounters divided across multiple partners. We tested between these accounts using two preregistered studies of U.S.-residing CloudResearch participants (N = 1,318) conducted in 2023. In Experiment 1, using a repeated-measures design, jealousy appeared to decrease as the number of affair partners increased—despite the total number of sexual encounters remaining constant across scenarios. In Experiment 2, we replicated this effect using a between-subjects design and found evidence for the potential mediating role of emotional attachment concerns. Participants in Experiment 2 also rated one-off encounters across multiple affair partners as “more” cheating than the same number of encounters with a single affair partner, suggesting greater jealousy in response to “less” cheating. Importantly, anger at one’s partner did not differ across scenarios, indicating some degree of specificity to jealousy. These seemingly paradoxical findings support functional accounts of romantic jealousy and highlight the utility of adaptationist approaches to affective science.
The Function of Love: A Signaling-to-Alternatives Account of the Commitment Device Hypothesis
Abstract: Love is commonly hypothesized to function as an evolved commitment device, disincentivizing the pursuit of romantic alternatives and signaling this motivational shift to a partner. Here, we test this possibility against a novel signaling-to-alternatives account, in which love instead operates by dissuading alternatives from pursuing oneself. Overall, we find stronger support for the latter account. In Studies 1 and 2, we find that partner quality relative to alternatives positively predicts feelings of love, and love fails to mitigate the negative effects of desirable alternatives on relationship satisfaction—contradicting the classic commitment device account. In Study 3, using a longitudinal design, we replicate these effects and find that changes in partner quality relative to alternatives predict changes in love over time. In Study 4, we replicate the relationship between love and relative partner quality across 44 countries. In Study 5, we find a nearly one-to-one correspondence between the extent to which partner-directed actions are diagnostic of love and reductions in romantic alternatives’ attraction to the actor. These results suggest that love may not act as a commitment device in the classic sense by disincentivizing the pursuit of alternatives but by disincentivizing alternatives from pursuing oneself.
Deconfounding Sex and Sex of Partner in Mate-Preference Research
Abstract: Much of the previous research examining sex differences in human mate preferences has relied exclusively on heterosexual participants. Consequently, prior work overlooks a critical limitation: In heterosexual populations, participant sex and partner sex are perfectly confounded. Here, we tease apart this fundamental problem by separately examining ideal preferences for male and female partners across two studies—one using a large bisexual sample (n = 442) and another using a sample of both bisexual and heterosexual participants (n = 380). The results revealed that sex differences in mate preferences were largely driven by the participants’ own sex. However, both males and females set higher standards overall for the traits of male partners. These findings suggest that a person’s mate-preference psychology is shaped by both one’s own sex and the sex of the target being evaluated. More broadly, these results expand our understanding of the proximate psychology underlying human mate preferences.
Predictors of Enhancing Human Physical Attractiveness: Data from 93 Countries
Abstract: People across the world and throughout history have gone to great lengths to enhance their physical appearance. Evolutionary psychologists and ethologists have largely attempted to explain this phenomenon via mating preferences and strategies. Here, we test one of the most popular evolutionary hypotheses for beauty-enhancing behaviors, drawn from mating market and parasite stress perspectives, in a large cross-cultural sample. We also test hypotheses drawn from other influential and non-mutually exclusive theoretical frameworks, from biosocial role theory to a cultural media perspective. Survey data from 93,158 human participants across 93 countries provide evidence that behaviors such as applying makeup or using other cosmetics, hair grooming, clothing style, caring for body hygiene, and exercising or following a specific diet for the specific purpose of improving ones physical attractiveness, are universal. Indeed, 99% of participants reported spending >10 min a day performing beauty-enhancing behaviors. The results largely support evolutionary hypotheses: more time was spent enhancing beauty by women (almost 4 h a day, on average) than by men (3.6 h a day), by the youngest participants (and contrary to predictions, also the oldest), by those with a relatively more severe history of infectious diseases, and by participants currently dating compared to those in established relationships. The strongest predictor of attractiveness-enhancing behaviors was social media usage. Other predictors, in order of effect size, included adhering to traditional gender roles, residing in countries with less gender equality, considering oneself as highly attractive or, conversely, highly unattractive, TV watching time, higher socioeconomic status, right-wing political beliefs, a lower level of education, and personal individualistic attitudes. This study provides novel insight into universal beauty-enhancing behaviors by unifying evolutionary theory with several other complementary perspectives.
Joint Action Enhances Subsequent Social Learning by Strengthening a Mirror Mechanism
Abstract: Many of our activities involve joint action. Here, we explore a possible consequence of joint action: Completing a task may improve one’s ability to learn a novel task from a partner. In the Joint condition of three experiments, participants and experimenters jointly used a wire to cut candles for five minutes. In the control condition, the participants used the wire to cut the candles alone. After cutting, the experimenter demonstrated a novel, complex movement that was imitated by the participant. Compared to the control condition, participants in the Joint condition imitated the experimenter more accurately, at a shorter lag, and reproduced the sequence more accurately without the experimenter’s involvement. In experiments using electroencephalography, we used mu-desynchronization to track changes in the action mirror neuron system produced by candle-cutting. Although we did not confirm all predictions of a mirror neuron account, the results were generally consistent with our hypothesis that joint action enhances subsequent social learning by changing a mirror mechanism. In addition, the Joint participants reported greater closeness to the experimenter. We end the chapter by briefly exploring the consequences of joint modification of the mirror neuron system for social relations, teaching, and rehabilitation.
Contact Me:
If you’re interested in collaborating on a project or wish to know more about the research I am currently conducting, contact me at my email address below, or get in touch on BlueSky or LinkedIn.
Email: Ben.gelbart@yale.edu
