Women's Attraction to Benevolent Sexism: Needing Relationship Security Predicts Greater Attraction to Men who Endorse Benevolent Sexism. Emily Cross and Nickola Overall. European Journal of Social Psychology, doi: 10.1002/ejsp.2334.
Abstract: Benevolent sexism prescribes that men should cherish and protect women in intimate relationships. Despite the romantic tone of these attitudes, prior research indicates that benevolent sexism undermines women's competence, ambition and independence. Ambivalent sexism theory proposes that benevolent sexism is able to incur these costs because the promise of a chivalrous protective partner offers women security in their intimate relationships. We tested this key proposition by examining whether women who intensely need relationship security — women higher in attachment anxiety — are more attracted to men who endorse benevolent sexism. Highly anxious women (N = 632) rated men described as endorsing benevolent sexism as relatively more attractive, and reported greater preferences for partners to hold benevolently sexist attitudes. These results advance understanding regarding the underlying reasons women find benevolent sexism appealing and identify who will be most vulnerable to the potential costs of benevolent sexism.
Monday, October 2, 2017
Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction
Is Romantic Desire Predictable? Machine Learning Applied to Initial Romantic Attraction. Samantha Joel, Paul Eastwick and Eli Finkel. Psychological Science, http://journals.sagepub.com/doi/10.1177/0956797617714580
Abstract: Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people’s self-reported traits and preferences. We used machine learning to test how well such measures predict people’s overall tendencies to romantically desire other people (actor variance) and to be desired by other people (partner variance), as well as people’s desire for specific partners above and beyond actor and partner variance (relationship variance). In two speed-dating studies, romantically unattached individuals completed more than 100 self-report measures about traits and preferences that past researchers have identified as being relevant to mate selection. Each participant met each opposite-sex participant attending a speed-dating event for a 4-min speed date. Random forests models predicted 4% to 18% of actor variance and 7% to 27% of partner variance; crucially, however, they were unable to predict relationship variance using any combination of traits and preferences reported before the dates. These results suggest that compatibility elements of human mating are challenging to predict before two people meet.
KEYWORDS: attraction; dating; ensemble methods; machine learning; open data; open materials; random forests; romantic desire; romantic relationships; speed dating; statistical learning
Abstract: Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people’s self-reported traits and preferences. We used machine learning to test how well such measures predict people’s overall tendencies to romantically desire other people (actor variance) and to be desired by other people (partner variance), as well as people’s desire for specific partners above and beyond actor and partner variance (relationship variance). In two speed-dating studies, romantically unattached individuals completed more than 100 self-report measures about traits and preferences that past researchers have identified as being relevant to mate selection. Each participant met each opposite-sex participant attending a speed-dating event for a 4-min speed date. Random forests models predicted 4% to 18% of actor variance and 7% to 27% of partner variance; crucially, however, they were unable to predict relationship variance using any combination of traits and preferences reported before the dates. These results suggest that compatibility elements of human mating are challenging to predict before two people meet.
KEYWORDS: attraction; dating; ensemble methods; machine learning; open data; open materials; random forests; romantic desire; romantic relationships; speed dating; statistical learning
Chief science adviser attacks academic ‘arrogance’ on policy
Chief science adviser attacks academic ‘arrogance’ on policy. By David Matthews. Times Higher Education. September 29, 2017
Sir Peter Gluckman, who advises New Zealand’s prime minister, cautions scientists against overreach
https://www.timeshighereducation.com/news/chief-science-adviser-attacks-academic-arrogance-policy
The chief science adviser to the prime minister of New Zealand has accused scientists of displaying “hubris” and “arrogance” when they comment on government policy.
Sir Peter Gluckman, who also chairs the International Network for Science Advice to Governments, levelled a series of sharp criticisms at researchers and science organisations during an event in Brussels that debated the role of policy and evidence in a “post-fact” world.
He argued that scientists needed to appreciate that politicians made their decisions based on values as well as scientific evidence.
“Individual scientists, professional and scientific organisations too often exhibit hubris in reflecting on policy implications of science,” Sir Peter told delegates at “EU for facts: evidence for policy in a post-fact world”, held on 26 September.
“This arrogance can become the biggest enemy of science effectively engaging with policy – the policy decisions inevitably involve dimensions beyond science.”
Scientists needed to appreciate that political ideology, financial and diplomatic constraints, and “electoral contracts” also had to be taken into account by politicians, Sir Peter said. “It is important that [scientific] knowledge is provided [to policymakers] in a way that does not usurp the ability of policy process to consider these broader dimensions: otherwise trust in advice can be lost as it becomes perceived as advocacy,” he argued.
He also said that he avoided using the “somewhat arrogant” term “evidence-based policy”, preferring “evidence-informed” instead. Meanwhile, “too often academy reports are focused on academic demonstration rather than meeting policy needs or answering an unasked question”, he added.
Similar warnings have come from other figures in science. Last year, Jeremy Berg, the editor-in-chief of Science, said that academics have too often ventured into giving policy prescriptions rather than just explaining the evidence, for example in the area of climate change.
Although he named no names, Sir Peter also warned that “individual scientists” were now using their “scientific standing” to make claims “well beyond the evidence and their expertise”. Universities may also “over-hype” their science, he added.
In addition, the pressures of “performance measurement, bibliometrics, and the quest for societal and industrial impact” also have the potential to undermine public trust in science, he said, “due to perceived or actual conflicts of interest and the potential to affect the behaviour of individual scientists”.
[More at the link above.]
Sir Peter Gluckman, who advises New Zealand’s prime minister, cautions scientists against overreach
https://www.timeshighereducation.com/news/chief-science-adviser-attacks-academic-arrogance-policy
The chief science adviser to the prime minister of New Zealand has accused scientists of displaying “hubris” and “arrogance” when they comment on government policy.
Sir Peter Gluckman, who also chairs the International Network for Science Advice to Governments, levelled a series of sharp criticisms at researchers and science organisations during an event in Brussels that debated the role of policy and evidence in a “post-fact” world.
He argued that scientists needed to appreciate that politicians made their decisions based on values as well as scientific evidence.
“Individual scientists, professional and scientific organisations too often exhibit hubris in reflecting on policy implications of science,” Sir Peter told delegates at “EU for facts: evidence for policy in a post-fact world”, held on 26 September.
“This arrogance can become the biggest enemy of science effectively engaging with policy – the policy decisions inevitably involve dimensions beyond science.”
Scientists needed to appreciate that political ideology, financial and diplomatic constraints, and “electoral contracts” also had to be taken into account by politicians, Sir Peter said. “It is important that [scientific] knowledge is provided [to policymakers] in a way that does not usurp the ability of policy process to consider these broader dimensions: otherwise trust in advice can be lost as it becomes perceived as advocacy,” he argued.
He also said that he avoided using the “somewhat arrogant” term “evidence-based policy”, preferring “evidence-informed” instead. Meanwhile, “too often academy reports are focused on academic demonstration rather than meeting policy needs or answering an unasked question”, he added.
Similar warnings have come from other figures in science. Last year, Jeremy Berg, the editor-in-chief of Science, said that academics have too often ventured into giving policy prescriptions rather than just explaining the evidence, for example in the area of climate change.
Although he named no names, Sir Peter also warned that “individual scientists” were now using their “scientific standing” to make claims “well beyond the evidence and their expertise”. Universities may also “over-hype” their science, he added.
In addition, the pressures of “performance measurement, bibliometrics, and the quest for societal and industrial impact” also have the potential to undermine public trust in science, he said, “due to perceived or actual conflicts of interest and the potential to affect the behaviour of individual scientists”.
[More at the link above.]
Physicists find we’re not living in a computer simulation
Physicists find we’re not living in a computer simulation
Summary:
https://cosmosmagazine.com/physics/physicists-find-we-re-not-living-in-a-computer-simulationRingel and Kovrizhi showed that attempts to use quantum Monte Carlo to model systems exhibiting anomalies, such as the quantum Hall effect, will always become unworkable.
They discovered that the complexity of the simulation increased exponentially with the number of particles being simulated.
If the complexity grew linearly with the number of particles being simulated, then doubling the number of partices would mean doubling the computing power required. If, however, the complexity grows on an exponential scale – where the amount of computing power has to double every time a single particle is added – then the task quickly becomes impossible.
The researchers calculated that just storing information about a couple of hundred electrons would require a computer memory that would physically require more atoms than exist in the universe.
Paper:
Quantized gravitational responses, the sign problem, and quantum complexity. Zohar Ringel and Dmitry L. Kovrizhin. Science Advances, Sep 27 2017, Vol. 3, no. 9, e1701758, DOI: 10.1126/sciadv.1701758
Abstract: It is believed that not all quantum systems can be simulated efficiently using classical computational resources. This notion is supported by the fact that it is not known how to express the partition function in a sign-free manner in quantum Monte Carlo (QMC) simulations for a large number of important problems. The answer to the question—whether there is a fundamental obstruction to such a sign-free representation in generic quantum systems—remains unclear. Focusing on systems with bosonic degrees of freedom, we show that quantized gravitational responses appear as obstructions to local sign-free QMC. In condensed matter physics settings, these responses, such as thermal Hall conductance, are associated with fractional quantum Hall effects. We show that similar arguments also hold in the case of spontaneously broken time-reversal (TR) symmetry such as in the chiral phase of a perturbed quantum Kagome antiferromagnet. The connection between quantized gravitational responses and the sign problem is also manifested in certain vertex models, where TR symmetry is preserved.
Individuals reared together are no more similar to one another in their personalities than if chosen at random in the population
Theoretical Concepts in the Genetics of Personality Development. Elliot M. Tucker-Drob & Daniel A. Briley. To appear in Handbook of Personality Development, by Dan P. McAdams, Rebecca L. Shiner, and Jennifer L. Tackett (Eds.). June 2017. http://labs.la.utexas.edu/tucker-drob/files/2015/02/Tucker-Drob-Briley-Genetics-of-Personality-Development-Chapter.pdf
Conventional work in the behavioral genetics of personality largely focused on single point estimates of heritability of personality. For instance, point estimates for the heritability of all of the Big Five personality traits have been reported to be approximately .40-.60 (for a review see Bouchard & McGue, 2003), with no consistent differences reported across different Big Five traits (Turkheimer, Pettersson, & Horn, 2014). Evidence for genetic influences on personality are derived from the observation that genetically more related individuals (e.g. identical twins) are more similar in their personality traits than genetically less related individuals (e.g. fraternal twins), even when holding shared rearing environment constant across relationship types. Also of note is that, after accounting for genetic relatedness, individuals reared together are no more similar to one another in their personalities than would be expected for individuals chosen at random out of the population. Nongenetic factors that differentiate individuals regardless of whether their rearing environment was shared with one another are termed the nonshared environment. These two important and interesting observations, that the heritability of personality is approximately 40%-60% at the population level and that nongenetic variation in personality is attributable to nonshared environmental factors, are the primary findings from behavioral genetics used to inform conventional personality theories. Yet, they do not do justice to the important developmental patterns in the genetics of personality.
The relative influence of genetic and environmental effects may shift across the lifespan, rather than remain static. Age trends in the heritability of personality have been reported in quantitative syntheses by Kandler (2012) for Neuroticism and Extraversion, and Briley and Tucker-Drob (2014) for all of the Big Five. In both syntheses, age trends have been very similar across each of the Big Five traits. [...] Heritability of personality is estimated at approximately 70% in early childhood, declines to approximately 50% by late adolescence, and subsequently declines to approximately 35% by late adulthood. Nonshared environmentality increases from approximately 30% to 50% to 65% from infancy to late adolescence, to late adulthood. However, at least some of this trend may reflect method bias, as nearly all of the effect sizes for very young children come from parent-reports. These ratings may exaggerate differences between siblings and thus inflate heritability.
Conventional work in the behavioral genetics of personality largely focused on single point estimates of heritability of personality. For instance, point estimates for the heritability of all of the Big Five personality traits have been reported to be approximately .40-.60 (for a review see Bouchard & McGue, 2003), with no consistent differences reported across different Big Five traits (Turkheimer, Pettersson, & Horn, 2014). Evidence for genetic influences on personality are derived from the observation that genetically more related individuals (e.g. identical twins) are more similar in their personality traits than genetically less related individuals (e.g. fraternal twins), even when holding shared rearing environment constant across relationship types. Also of note is that, after accounting for genetic relatedness, individuals reared together are no more similar to one another in their personalities than would be expected for individuals chosen at random out of the population. Nongenetic factors that differentiate individuals regardless of whether their rearing environment was shared with one another are termed the nonshared environment. These two important and interesting observations, that the heritability of personality is approximately 40%-60% at the population level and that nongenetic variation in personality is attributable to nonshared environmental factors, are the primary findings from behavioral genetics used to inform conventional personality theories. Yet, they do not do justice to the important developmental patterns in the genetics of personality.
The relative influence of genetic and environmental effects may shift across the lifespan, rather than remain static. Age trends in the heritability of personality have been reported in quantitative syntheses by Kandler (2012) for Neuroticism and Extraversion, and Briley and Tucker-Drob (2014) for all of the Big Five. In both syntheses, age trends have been very similar across each of the Big Five traits. [...] Heritability of personality is estimated at approximately 70% in early childhood, declines to approximately 50% by late adolescence, and subsequently declines to approximately 35% by late adulthood. Nonshared environmentality increases from approximately 30% to 50% to 65% from infancy to late adolescence, to late adulthood. However, at least some of this trend may reflect method bias, as nearly all of the effect sizes for very young children come from parent-reports. These ratings may exaggerate differences between siblings and thus inflate heritability.
Access to other options during drug access can divert the vast majority of rats from continued drug use
Trying to make sense of rodents' drug choice behavior. Serge H. Ahmed. Progress in Neuro-Psychopharmacology and Biological Psychiatry, https://doi.org/10.1016/j.pnpbp.2017.09.027
Highlights
• Rodents are the most frequently used animal models in experimental addiction research.
• Rodents discount future delayed reward at a relatively high rate.
• This behavioral trait seems to be protective against harmful drug use in certain choice settings.
• In other settings, however, the same trait seems to confer a high vulnerability to harmful drug use.
• More research effort should be expended to study the interactions between the set, the drug, and the setting.
Abstract: Since the first experimental hint for the existence of “an actual desire or striving for the drug” in nonhuman animals by Sidney Spragg in the late 1930s, much effort has been expended by lab researchers to try to model in a valid manner the key behavioral aspects and signs of addiction in animals, typically in rodents (i.e., mainly rats and, to a lesser extent, mice). Despite much advances, there still remains a lingering doubt about the disordered status of drug use in rodents. This is mainly because drug use occurs in a particular setting where animals have access to a drug for self-administration but without access to other valuable behavioral options that could compete with and divert from drug use. Here I review evidence showing that enriching the drug setting with other behavioral options can dramatically influence the pattern of drug choices in rodents. Overall, access to other options during drug access can divert the vast majority of rats from continued drug use. Only few individuals continue to engage in drug use despite access to and at the expense of other options. However, there exist certain high-risk settings in which virtually all animals are vulnerable to develop a harmful pattern of exclusive drug use that can even become fatal in the long run if not discontinued by an outside intervention. Paradoxically, it appears that the behavioral trait that is hypothesized to uniquely render rodents vulnerable to the latter settings (i.e., a narrow focus on the local, current choice, with no consideration of the global pattern of choice) would also protect most of them from using drugs in other choice settings. I conclude with an attempt to make sense of this peculiar setting-specific behavior and with some general propositions for future research.
Highlights
• Rodents are the most frequently used animal models in experimental addiction research.
• Rodents discount future delayed reward at a relatively high rate.
• This behavioral trait seems to be protective against harmful drug use in certain choice settings.
• In other settings, however, the same trait seems to confer a high vulnerability to harmful drug use.
• More research effort should be expended to study the interactions between the set, the drug, and the setting.
Abstract: Since the first experimental hint for the existence of “an actual desire or striving for the drug” in nonhuman animals by Sidney Spragg in the late 1930s, much effort has been expended by lab researchers to try to model in a valid manner the key behavioral aspects and signs of addiction in animals, typically in rodents (i.e., mainly rats and, to a lesser extent, mice). Despite much advances, there still remains a lingering doubt about the disordered status of drug use in rodents. This is mainly because drug use occurs in a particular setting where animals have access to a drug for self-administration but without access to other valuable behavioral options that could compete with and divert from drug use. Here I review evidence showing that enriching the drug setting with other behavioral options can dramatically influence the pattern of drug choices in rodents. Overall, access to other options during drug access can divert the vast majority of rats from continued drug use. Only few individuals continue to engage in drug use despite access to and at the expense of other options. However, there exist certain high-risk settings in which virtually all animals are vulnerable to develop a harmful pattern of exclusive drug use that can even become fatal in the long run if not discontinued by an outside intervention. Paradoxically, it appears that the behavioral trait that is hypothesized to uniquely render rodents vulnerable to the latter settings (i.e., a narrow focus on the local, current choice, with no consideration of the global pattern of choice) would also protect most of them from using drugs in other choice settings. I conclude with an attempt to make sense of this peculiar setting-specific behavior and with some general propositions for future research.
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