While online dating offers a platform to obtain high size sample values from a naturalistic setting that should confer high external reliability. In speed dating all the interactions are enforced, because they are not the result of interaction of courtship. And other issues such as low population density (number of daters) and keeping artificially event operational sex ratios near 1:1. Speed dating eliminates the component of the pre-selection in the human mating. While in others systems as human natural leks (nightclubs, bar, etc) and online dating the attracting attention is the first goal. Attention is elicited through the display of signals that excite the interest of possible mates. In mating field non-verbal solicitation is mainly done by the female as a basis for the male decision to approach her.
What most studies tells us, is that since physical attractiveness (independent variable) is the limiting factor for both sexes (since other attributes act as dependent variables), I’m going to focus in this parameter to address other issues.
Attractiveness ratings:
In this article you illustrate how revealed preferences (, preferences inferred through a speed dating event) can be used to investigate the nature of mate preferences. You describe how revealed preferences can be estimated and how the reliability of these estimates can be established. Then revealed preference estimates were used to explore the level of consensus in judgments of who is and is not attractive and whether revealed preferences are systematically related to self-reported mate preferences and personality traits.
Some of the graphics are pretty obtuse me for me. I’d like to ask you if it would be possible to exposing other type of graphs where the data could become more clarifiers.
Participants of both genders showed substantial consensus in judgments of whom they found attractive and unattractive, but what sex showed higher consensus? Is the standard deviation in your speed dating study of attraction ratings for a specific opposite-sex face on average smaller when looking at a specific gender?
It seems that in most studies women have a higher variance in ratings of sex-objects than men (Jankowiak et al. 1992; Townsend & Wasserman 1997). But this should be taken with a grain of salt because attractiveness rankings have much higher variation when ranking males as opposed to females.
Schulman & Hoskins (1986) found that ratings of female photos had statistically significant lower variance than male photos for both male and female raters. Thus, the effect could partially be in that both sexes are worse at judging attractiveness of males.
There is never going to be rigorous agreement on any kind of informal attractiveness metric, so the subjective discussions are missing the point. And here’s where something interesting beings to happen with this whole rating system. The more imbalanced the mating dynamic becomes, the more asymmetric – in terms of their distribution between the male and female populations – these rankings become.
In their study is a notable absence of individuals at extremes of attractiveness. Rather, future work might best reveal decision rules by manipulating the distribution of quality among potential mates; such manipulations would predict if people, mainly females, are using sample-based or threshold-based decision rules. So, it comes to a point that I’ve usually observed on my own experiments, that male ‘ratings’ are bottom heavy in distribution, while female ‘ratings’ are top heavy (meaning there are more female 7′s than male 7′s, by virtue of the fact that a female 7 has a greater probability of attracting a male 7, than the reverse). Although this does not seem to be the case in your study.
Furthermore It would also be interesting to know the assortative/ disassortative mating coefficients. How do perceptions of male attractiveness differ from perceptions of female attractiveness? I know that a speed dating event does not represent a potentially robust source of attractiveness data. And it is clear, however, that the site’s audience may not be very representative of the population as a whole. Anyway I’d like if you could address one aspect of that problem by attempting to determine whether and how the distribution of male attractiveness in your speed dating sample differs from the distribution of female attractiveness: female/male population distribution. It seems your graph (which does not support that females are more selective, given that rating skew is a corollary of selectivity), which poses too many confounders in the data to rely upon too strongly.) differ substantially from those found here:
And what’s yes/no decisions distributions? Intuitively, several answers to this question seem plausible. On one hand, it seems anecdotally to be true that in our study there are not nobody extremely attractive people, many average looking people, and few extremely unattractive people. Such logic could lead one to predict a normal attractiveness distribution as your findings.
But Okcupid blog and Kreager/Cavanag study, for example, find this gaussian distribution only in male population distribution, since women women rate 80% of guys as worse-looking than medium.
I’d like to know whether participants’ ratings of hypothetical partners, for example, reflect whom they would actually choose to date (yes/no). I don’t understand the distribution of decisions/ attractiveness angles chart. What’s the relationship between individuals’ own physical attractiveness (as rated by other users) and the attractiveness of the people they wanted to meet?
“men’s decision were yes for 48% of the dates in the sample, and women’s decisions were yes for 33% of the dates in the sample.”
I’d like to know whether participants’ ratings of hypothetical partners, for example, reflect whom they would actually choose to date (yes/no). ie, How the percentage of acceptances (number of acceptances) is distributed for each attractiveness range of males and females in this system?. For example, for a woman 4 in attractiveness, what is her total number of yeses she gave respect of all male daters? and for a 6 women? And of this number of acceptances or yeses, what percentage of acceptances is corresponding to men rated as 1…4, 5, 6,..?or how their offerings are distributed between the different spectrum of quality, since the optimal threshold depends on the attributes of prospective mates ( and her own quality), and the distribution of the quality of these ones.
By the other hand, it would be interesting try to find out on here if there is a genetically determined threshold (threshold-based decisions) or there is any other unlearned threshold (sampled-based decisions) . These considerations would also reveal a simple algorithm by which the threshold could be learned. Peter M. Todd et al tried to make that test. See http://141.14.165.6/CogSci09/papers/547/paper547.pdf
First, it’s important to know ,analizing yes/no rates, if less attractive people is accepting less attractive dates (My own analysis of data from online dating suggests that this is not the case) or are focusing in most deserable opposite-sex individuals. And analyzing attractiveness data, if less attractive individuals’ assessment are higher than those from most attractive ones. (i.e. if less attractive people do not delude themselves into thinking that their dates are more physically attractive than others perceive them to be). True that it could be a conditioning problem the absence of highly attractive individuals (top of the beauty scale) in the study sample.
It would be necessary introducing into the sample several highly attractive daters (>8 points) to see if this data tend to remain constant or conversely betray a predictable patterns in demonstrating a near universal preference for this very narrow range of male/female physical phenotypes.
It is a mistake the absence of a number of subjects that can be classified as highly attractive (above 8). A speed dating event does not represent a potentially robust source of attractiveness data (small size). And it is clear, however, that the site’s audience may not be very representative of the population as a whole. Most people are within the medium spectrum, and only a handful are good-looking.
I would say that real mate choice (in broader mating leks) is concentrated in a narrow population range, especially in female choice. Since the most reliable data / investigation (online dating and field courship) agree in this frame of observation. And what this tells us, is that since physical attractiveness was a limiting factor for BOTH sexes, and women are MORE selective in assessing attractive males – women are MORE likely (than men) to cull prospects according to assessments of physical attractiveness. Where women tend to fixate on the top ~ %10-20 of males. See: freakanomics data, http://jonmillward.com/blog/attraction-dating/cupid-on-trial-a-4-month-online-dating-experiment/, or my own experiment::https://sirtyrionlannister.wordpress.com/2014/02/23/female-mating-skew-ii-supported-by-online-dating-experiment/), considering the bottom %80 of males as, inexplicably, less than average (see OK Cupid data), the variance in that top %10-20 tends to split a lot of trivial hairs (making the differences harder to quantify, with respect to an attractiveness ranking system).
While online dating offers a platform to obtain high size sample values from a naturalistic setting that should confer high external reliability. In speed dating all the interactions are enforced, because they are not the result of interaction of courtship. And other issues such as low population density (number of daters) and keeping artificially event operational sex ratios near 1:1. Speed dating eliminates the component of the pre-selection in the human mating. While in others systems as human natural leks (nightclubs, bar, etc) and online dating the attracting attention is the first goal. Attention is elicited through the display of signals that excite the interest of possible mates. In mating field non-verbal solicitation is mainly done by the female as a basis for the male decision to approach her.
What most studies tells us, is that since physical attractiveness (independent variable) is the limiting factor for both sexes (since other attributes act as dependent variables), I’m going to focus in this parameter to address other issues.
Attractiveness ratings:
In this article you illustrate how revealed preferences (, preferences inferred through a speed dating event) can be used to investigate the nature of mate preferences. You describe how revealed preferences can be estimated and how the reliability of these estimates can be established. Then revealed preference estimates were used to explore the level of consensus in judgments of who is and is not attractive and whether revealed preferences are systematically related to self-reported mate preferences and personality traits.
Some of the graphics are pretty obtuse me for me. I’d like to ask you if it would be possible to exposing other type of graphs where the data could become more clarifiers.
Participants of both genders showed substantial consensus in judgments of whom they found attractive and unattractive, but what sex showed higher consensus? Is the standard deviation in your speed dating study of attraction ratings for a specific opposite-sex face on average smaller when looking at a specific gender?
It seems that in most studies women have a higher variance in ratings of sex-objects than men (Jankowiak et al. 1992; Townsend & Wasserman 1997). But this should be taken with a grain of salt because attractiveness rankings have much higher variation when ranking males as opposed to females.
Schulman & Hoskins (1986) found that ratings of female photos had statistically significant lower variance than male photos for both male and female raters. Thus, the effect could partially be in that both sexes are worse at judging attractiveness of males.
There is never going to be rigorous agreement on any kind of informal attractiveness metric, so the subjective discussions are missing the point. And here’s where something interesting beings to happen with this whole rating system. The more imbalanced the mating dynamic becomes, the more asymmetric – in terms of their distribution between the male and female populations – these rankings become.
In their study is a notable absence of individuals at extremes of attractiveness. Rather, future work might best reveal decision rules by manipulating the distribution of quality among potential mates; such manipulations would predict if people, mainly females, are using sample-based or threshold-based decision rules. So, it comes to a point that I’ve usually observed on my own experiments, that male ‘ratings’ are bottom heavy in distribution, while female ‘ratings’ are top heavy (meaning there are more female 7′s than male 7′s, by virtue of the fact that a female 7 has a greater probability of attracting a male 7, than the reverse). Although this does not seem to be the case in your study.
Furthermore It would also be interesting to know the assortative/ disassortative mating coefficients. How do perceptions of male attractiveness differ from perceptions of female attractiveness? I know that a speed dating event does not represent a potentially robust source of attractiveness data. And it is clear, however, that the site’s audience may not be very representative of the population as a whole. Anyway I’d like if you could address one aspect of that problem by attempting to determine whether and how the distribution of male attractiveness in your speed dating sample differs from the distribution of female attractiveness: female/male population distribution. It seems your graph (which does not support that females are more selective, given that rating skew is a corollary of selectivity), which poses too many confounders in the data to rely upon too strongly.) differ substantially from those found here:
http://onlinelibrary.wiley.com/doi/10.1111/jomf.12072/full
http://blog.okcupid.com/index.php/your-looks-and-online-dating/
And what’s yes/no decisions distributions? Intuitively, several answers to this question seem plausible. On one hand, it seems anecdotally to be true that in our study there are not nobody extremely attractive people, many average looking people, and few extremely unattractive people. Such logic could lead one to predict a normal attractiveness distribution as your findings.
But Okcupid blog and Kreager/Cavanag study, for example, find this gaussian distribution only in male population distribution, since women women rate 80% of guys as worse-looking than medium.
I’d like to know whether participants’ ratings of hypothetical partners, for example, reflect whom they would actually choose to date (yes/no). I don’t understand the distribution of decisions/ attractiveness angles chart. What’s the relationship between individuals’ own physical attractiveness (as rated by other users) and the attractiveness of the people they wanted to meet?
“men’s decision were yes for 48% of the dates in the sample, and women’s decisions were yes for 33% of the dates in the sample.”
I’d like to know whether participants’ ratings of hypothetical partners, for example, reflect whom they would actually choose to date (yes/no). ie, How the percentage of acceptances (number of acceptances) is distributed for each attractiveness range of males and females in this system?. For example, for a woman 4 in attractiveness, what is her total number of yeses she gave respect of all male daters? and for a 6 women? And of this number of acceptances or yeses, what percentage of acceptances is corresponding to men rated as 1…4, 5, 6,..?or how their offerings are distributed between the different spectrum of quality, since the optimal threshold depends on the attributes of prospective mates ( and her own quality), and the distribution of the quality of these ones.
By the other hand, it would be interesting try to find out on here if there is a genetically determined threshold (threshold-based decisions) or there is any other unlearned threshold (sampled-based decisions) . These considerations would also reveal a simple algorithm by which the threshold could be learned. Peter M. Todd et al tried to make that test. See http://141.14.165.6/CogSci09/papers/547/paper547.pdf
First, it’s important to know ,analizing yes/no rates, if less attractive people is accepting less attractive dates (My own analysis of data from online dating suggests that this is not the case) or are focusing in most deserable opposite-sex individuals. And analyzing attractiveness data, if less attractive individuals’ assessment are higher than those from most attractive ones. (i.e. if less attractive people do not delude themselves into thinking that their dates are more physically attractive than others perceive them to be). True that it could be a conditioning problem the absence of highly attractive individuals (top of the beauty scale) in the study sample.
It would be necessary introducing into the sample several highly attractive daters (>8 points) to see if this data tend to remain constant or conversely betray a predictable patterns in demonstrating a near universal preference for this very narrow range of male/female physical phenotypes.
It is a mistake the absence of a number of subjects that can be classified as highly attractive (above 8). A speed dating event does not represent a potentially robust source of attractiveness data (small size). And it is clear, however, that the site’s audience may not be very representative of the population as a whole. Most people are within the medium spectrum, and only a handful are good-looking.
I would say that real mate choice (in broader mating leks) is concentrated in a narrow population range, especially in female choice. Since the most reliable data / investigation (online dating and field courship) agree in this frame of observation. And what this tells us, is that since physical attractiveness was a limiting factor for BOTH sexes, and women are MORE selective in assessing attractive males – women are MORE likely (than men) to cull prospects according to assessments of physical attractiveness. Where women tend to fixate on the top ~ %10-20 of males. See: freakanomics data, http://jonmillward.com/blog/attraction-dating/cupid-on-trial-a-4-month-online-dating-experiment/, or my own experiment::https://sirtyrionlannister.wordpress.com/2014/02/23/female-mating-skew-ii-supported-by-online-dating-experiment/), considering the bottom %80 of males as, inexplicably, less than average (see OK Cupid data), the variance in that top %10-20 tends to split a lot of trivial hairs (making the differences harder to quantify, with respect to an attractiveness ranking system).