Tuesday, January 12, 2021

Pornography Consumption and Attitudes Towards Pornography Legality Predict Attitudes of Sexual Equality

Pornography Consumption and Attitudes Towards Pornography Legality Predict Attitudes of Sexual Equality. David Speed  et al. The Journal of Sex Research, Jan 11 2021. https://www.tandfonline.com/doi/abs/10.1080/00224499.2020.1864263

Abstract: Some scholars argue that the existence of pornography is an ongoing assault on women and that it should be banned. However, the existing evidence suggests the connection between pornography consumption and sexism is overstated and may actually run in the opposite direction. Using data from the General Social Survey (2010–2018), the current study investigated if “pornography consumption” and “pornography tolerance” predicted sexism and whether these associations varied by sex. Results indicated that pornography consumption predicted lower levels of sexism, although these effects were rendered nonsignificant with the inclusion of sociodemographic, religious, and sociocultural covariates. When comparing the results of the current study to findings based on data from the 1970s–1990s, it appears that pornography consumption is now irrelevant to sexism rather than promoting egalitarianism. Our analyses focusing on “pornography tolerance” revealed that people who supported regulated pornography were more egalitarian than people who supported a pornography ban. Generally, men were more likely to report sexist attitudes than women, but sex moderated the relationship that pornography variables had with sexism in several of the models. Overall, pornography consumption and pornography tolerance were either irrelevant in predicting sexism or were associated with greater egalitarianism.

Ability emotional intelligence was a stronger predictor of performance in humanities than science; mechanisms under the EI/performance link can be regulating academic emotions & building social relationships at school

MacCann, C., Jiang, Y., Brown, L. E. R., Double, K. S., Bucich, M., & Minbashian, A. (2020). Emotional intelligence predicts academic performance: A meta-analysis. Psychological Bulletin, 146(2), 150-186, Jan 2021. http://dx.doi.org/10.1037/bul0000219

Abstract: Schools and universities devote considerable time and resources to developing students’ social and emotional skills, such as emotional intelligence (EI). The goals of such programs are partly for personal development but partly to increase academic performance. The current meta-analysis examines the degree to which student EI is associated with academic performance. We found an overall effect of ρ = .20 using robust variance estimation (N = 42,529, k = 1,246 from 158 citations). The association is significantly stronger for ability EI (ρ = .24, k = 50) compared with self-rated (ρ = .12, k = 33) or mixed EI (ρ = .19, k = 90). Ability, self-rated, and mixed EI explained an additional 1.7%, 0.7%, and 2.3% of the variance, respectively, after controlling for intelligence and big five personality. Understanding and management branches of ability EI explained an additional 3.9% and 3.6%, respectively. Relative importance analysis suggests that EI is the third most important predictor for all three streams, after intelligence and conscientiousness. Moderators of the effect differed across the three EI streams. Ability EI was a stronger predictor of performance in humanities than science. Self-rated EI was a stronger predictor of grades than standardized test scores. We propose that three mechanisms underlie the EI/academic performance link: (a) regulating academic emotions, (b) building social relationships at school, and (c) academic content overlap with EI. Different streams of EI may affect performance through different mechanisms. We note some limitations, including the lack of evidence for a causal direction.

Public Significance Statement: This meta-analysis shows that emotional intelligence has a small to moderate association with academic performance, such that students with higher emotional intelligence tend to gain higher grades and achievement test scores. The association is stronger for skill-based emotional intelligence tasks than rating scales of emotional intelligence. It is strongest for skill-based tasks measuring understanding emotions and managing emotions.

Keywords: academic performance, emotional intelligence, intelligence, meta-analysis, personality


Results from these meta-analyses demonstrate that EI shows a small to moderate relationship with academic performance, of similar effect size to well-known noncognitive predictors (e.g., ρ = .20 for EI vs. ρ = .22 for conscientiousness, based on the current meta-analysis and Poropat [2009]). Ability EI was a significantly stronger predictor than self-report or mixed EI, as hypothesized. Within ability EI, understanding and management branches had a stronger effect than perception or facilitation branches. There is no evidence for selective publication of larger effects, for stronger effects in younger students, nor that effects differ depending on the proportion of ethnic minority students in the sample. For the other moderators, effects were mixed or limited. There is limited evidence that the effect is stronger: (a) for less female-dominated samples (this effect was significant for total EI, but not for any of the three streams), (b) for grades than standardized test scores (this was significant for total EI and Stream 2 only), and (c) for humanities versus mathematics/science performance (this was significant for ability EI only).
There was evidence of incremental validity of EI over intelligence and personality, but this was largely restricted to mixed EI (which explained an additional 2.3% of the variance) and the understanding and management branches of ability EI (which explained an additional 3.9% and 3.6% of the variance respectively). That is, self-rated EI, total ability EI, and the lower two branches of ability EI (emotion perception and facilitation) provide little to no explanatory power for academic performance over intelligence and personality. These differences across the three streams suggest that the underlying mechanisms accounting for the EI/performance relationship may differ for ability EI, self-rated EI, and mixed EI.

Why Does EI Predict Academic Performance? Insights Based on Moderators

In our introduction, we suggested there were three reasons why EI may predict academic performance. First, students with higher EI may be more able to regulate the negative emotions such as anxiety, boredom, and disappointment involved in academic performance. If this is true, emotion management would be responsible for the effects. Second, students with higher EI may be better able to manage the social world around them, forming better relationships with teachers, peers, and family. If this was the case, emotion management would again be responsible for the effect, and the effect would be stronger for grades than for standardized tests. Third, EI competencies may overlap with the academic competencies required for humanities subjects like history and language arts (e.g., understanding human motivations and emotions). In this case (a) understanding—the knowledge base of EI—would show the strongest effect and (b) the effect would be bigger for humanities than sciences. Based on the significant moderations, there is some support for each of these effects, with slightly different results for different streams of EI. We discuss the significance moderations below, with respect to these three proposed mechanisms.

Evidence for Mechanism 1: Is Emotion Management the Key Ingredient in EI?

Joseph and Newman (2010) proposed a “key conceptual role” of emotion management for predicting job performance (p. 69), proposing emotion management as the proximal predictor of performance. The facet-level moderation for ability EI provides partial support for this assumption, finding that management and understanding are jointly the strongest predictors of academic performance. Both these branches (management and understanding) showed significantly stronger effects than the two other branches. The effect was larger for understanding than management, but not significantly so (ρ = .35 vs. ρ = .26) and was equal after accounting for the effects of intelligence and personality (partial ρ = .22 in both cases). That is, both emotion understanding and emotion management are active ingredients in the prediction of academic performance. We believe this is consistent with an interpretation that EI affects academic performance through the regulation of academic emotions, but also due to the relevance of emotion content knowledge for academic performance in the humanities.
The critical role of emotion understanding for academic performance has implications for comparing ability EI with self-rated EI. For self-rated EI, many of the effects in our meta-analysis used instruments that did not include emotion understanding content (because they were based on an older definition of EI that did not have emotion understanding in the definition). Specifically, 50% of the Stream 2 citations used the Schutte Self-Report Scale, Trait Meta-Mood Scale, or the Wong-Law Emotional Intelligence Scale, which do not include a subscale assessing emotion understanding. Given that ability EI shows the strongest relationship for emotion understanding, the difference in effect size between ability EI and self-rated EI measures may in fact represent a difference in content (i.e., prediction is greater for tests that include emotion understanding content) rather than a difference in method (ability scales vs. rating-scales). Many of the more recent self-rated EI tests do include an emotion understanding component (e.g., Anguiano-Carrasco, MacCann, Geiger, Seybert, & Roberts, 2015Brackett et al., 2006).

Evidence for Mechanism 2: Are EI Competencies Required for Academic Content?

Moderation analyses largely support the idea that performance on academic tasks require some EI competencies. First, academic performance related significantly more strongly to ability EI than to the other two streams. This finding differs from meta-analyses predicting job performance, where ability EI is consistently the weakest predictor of the three streams (Joseph & Newman, 2010Miao et al., 2017O’Boyle et al., 2011). This difference may relate to assessment methods. Academic performance is mainly assessed with objective tasks (i.e., evaluations of a product, such as an essay, lab report, speech, worksheet or test), whereas job performance is most often assessed via supervisor ratings. Similarly, ability EI is assessed with objective tasks and self-rated and mixed EI are assessed with rating scales. We would expect stronger predictor-criterion relationships when predictor and criterion have the same method. As such, a higher relationship for ability EI (as compared to the other streams) may represent method bias rather than content overlap of academic and emotional knowledge.
However, ability EI (but not self-rated or mixed EI) relates more strongly to performance in humanities than sciences. This is one of the larger differences we found, where the effect was nearly twice as large for humanities as sciences (ρ = .38 vs. .21). Objective measurement of performance is similar across humanities and sciences. The academic processes (social context and the student’s emotions and emotion regulation in the classroom) are also similar for different subdisciplines. Although subdisciplines differ in the degree of social interaction involved, the degree of social interaction does not align with the humanities versus science categorization (e.g., science frequently involves lab partners or group work, whereas this is rare for mathematics). As such, we interpret this difference in subject areas to be largely attributable to a difference in academic content, and specifically the relevance of emotion knowledge to subjects requiring an understanding of people and their interactions, motivations, and emotions (i.e., literature, history, geography, drama and other humanities subjects). The first standard of The Standards for the English Language Arts (1996), as put forward by the National Council of Teachers of English (1996) states that the purpose of reading texts is to “build an understanding of . . . themselves and the cultures of the United States and the world” and the second standard states that the purpose is “to build an understanding of the many dimensions (e.g., philosophical, ethical, aesthetic) of human experience” (p. 19). That is, broad statements of content for achievement in language arts inherently involve an understanding of oneself and of others in terms of the intangible nature of being human—which we would argue is essentially emotions and social interactions. That is, understanding human emotions and the social and situational causes appear to be an underlying component of achievement in language arts.
In addition, the fact that the emotion understanding showed the strongest relationship to academic performance (as compared to the other four branches) supports the interpretation mentioned above, where understanding emotional content is a key part of the content of language arts education. It is possible to view emotion understanding as a kind of domain-specific knowledge, where the content domain is emotions. Content knowledge of emotion words, as well as the causes and consequences of emotions, appear highly relevant for understanding character motivations in literature as well as other academic subject matter relating to people and how they shape societies, countries and history (i.e., history, geography, psychology, sociology).
One possible interpretation is that the ability EI/academic performance association may be due to a third variable—reading comprehension. Because ability EI tests involve interpreting written text, reading comprehension ability may constitute construct-irrelevant variance on such tests (AERA, APA, & NCME, 2014) that may partially explain the relationship between EI and academic performance. This particularly affects understanding and management tests, which involve more and more complex text (e.g., most management tests involve a paragraph of text in each item stem). However, the fact that emotion understanding and management predicted academic performance over-and-above the effect of intelligence suggests that this confound does not account for the entirety of the relationship between ability EI and academic performance. Nevertheless, the relationship was greatly reduced, particularly for emotion understanding. Because the partial correlations remained of small to moderate size after accounting for intelligence, our interpretation is that the bulk of the content overlap represents more than a reading comprehension method effect, particularly for emotion management. Taken together, results support the suggested mechanism whereby EI predicts academic performance because of the emotional content required in academic subjects.

Evidence for Mechanism 3: Does EI Affect Academic Performance Through Interpersonal Processes?

If EI exerts an influence on academic performance via the ability to develop social relationships in the educational context, then EI should have a stronger effect on grades than standardized tests (as the social networking and relationship building with other students and teachers should have a stronger effect on grades than on standardized tests). This difference was significant only for self-rated EI and the three streams combined (not for ability or mixed EI). Self-rated EI did not relate to standardized test scores at all (ρ = −.03). In contrast, ability EI and mixed EI related to both grades and standardized tests. This suggests that academic performance relates to self-rated EI through relationship building only. In contrast, academic performance relates to ability EI and mixed EI through both relationship building and mechanisms related to regulating academic emotions.
For all three streams of EI, there is evidence that higher EI relates to building social relationships in a school environment. Ability EI relates to peer-nominations of reciprocal friendship in college students and to higher-quality of social interactions with others (Lopes et al., 2004Lopes, Salovey, Coté, Beers, & Petty, 2005). Self-rated EI predicts greater social support in both high school and university students (Ciarrochi, Chan, & Bajgar, 2001Kong, Zhao, & You, 2012). Mixed EI is associated with peer reports of cooperative behavior (Mavroveli, Petrides, Rieffe, & Bakker, 2007Petrides, Sangareau, Furnham, & Frederickson, 2006). There is also evidence that both ability EI and mixed EI relate to using more effective strategies to regulate negative emotions (Peña-Sarrionandia, Mikolajczak, & Gross, 2015).
Taken together with these findings, we propose that differences between the three streams of EI relate to the number of mechanisms that underlie the EI/performance relationship. Specifically, (a) self-rated EI predicts academic performance only through a relationship building pathway (students with higher emotional self-efficacy can build better relationships with teachers and peers), (b) mixed EI predicts academic performance through both relationship building and the regulation of academic emotions, and (c) ability EI predicts academic performance through relationship building, regulation of academic emotions, and also through emotion content knowledge requirements of some academic areas. This explanation accounts for the relatively greater prediction of academic performance by ability EI than mixed EI than self-rated EI and is consistent with the pattern of moderators we found.

The Relative Importance of EI to Academic Achievement

One of the critical drivers of EI’s early popularity was the idea that emotional skills are more important than intelligence in predicting life success. Indeed, the title of Daniel Goleman’s first book, the catalyst for EI’s snowballing popularity, was Emotional intelligence: Why It Can Matter More Than IQ. The 1995 cover story of TIME magazine made similar claims, stating that “emotions, not IQ, may be the true measure of human intelligence” (Gibbs, 1995, p. 60). These early claims were generally not borne out by research on job performance. Although EI predicts better job performance (Joseph & Newman, 2010O’Boyle et al., 2011), a critical mass of research indicates that intelligence is a much stronger predictor and is in fact the single best predictor of job performance (Ree & Earles, 1992Salgado et al., 2003Schmidt & Hunter, 1998). We found largely similar results for academic performance. Although EI predicts academic performance, intelligence was a much stronger predictor, with relative importance analysis indicating that cognitive ability was the single most important predictor of academic performance.
Although the popular press hype about EI was not substantiated, we nevertheless believe that demonstrating a small to moderate effect size is informative for research and practice. Moreover, some of the recent changes occurring in education and assessment practices may increase the importance of noncognitive qualities, including EI.
The first such change to modern assessment and learning practice is the increasing use of group activities, including collaborative group assessments (Ahles & Bosworth, 2004). Managing the social relationships and interpersonal conflicts of the group may thus become more and more reflected in students’ end of semester grades. A second change to education practices is the extent to which graduate attributes (also referred to as 21st century skills or noncognitive constructs) are emphasized by schools and universities (e.g., Clarke, Double, & MacCann, 2017). Graduate attributes often include social-emotional skills such as leadership, communication, teamwork, and intercultural competencies, with some institutions explicitly including EI as a graduate attribute. For example, Australia uses Goleman’s model of EI as the basis for its national K–10 curriculum of personal and social competencies that students should be developing as they progress through primary and secondary education (ACARA, 2017). Schools and universities are increasingly attempting to embed these graduate qualities within the content that is taught and assessed. As such, high grades might increasingly reflect skill development in these areas.
A third change to the classroom is the extent to which computers and technology are now an integral part of education. In tertiary education, there are a large and increasing number of online only courses or courses that have at least some online-only content (most famously, the Massive Open Online Courses [MOOCs]). There are two main differences between traditional face-to-face learning and online learning. First, in a traditional face-to-face university course, the schedule of learning is set by the schedule of the face-to-face lectures. In contrast, an online only course requires the learner to manage their own schedule of accessing online content, such that students with poor time management will not succeed (MacCann, Fogarty, & Roberts, 2012). Second, in a traditional face-to-face course, communication with teachers and other students occurs through in-person conversation, with access to multiple channels of information (e.g., facial and vocal expression, body language, and real-time clarification of misunderstandings). Online communication is more often based on text (e.g., discussion boards, emails, or computer chat). Most neurotypical people find it more difficult to detect another person’s emotions and social needs from text rather than face-to-face contact. As such, greater emotional skills are required to build relationships with the instructor or other students in an online environment. Thus, social and emotional skills (both self-regulation and interpersonal skills) may become increasingly important as tertiary education involves a greater amount of online content.

Practical Implications

One of the major findings of this meta-analysis is that different parts of EI are differentially important for academic performance. Any applied uses of EI in education seem limited to the three parts of EI with nontrivial incremental validity: mixed EI, emotion management ability, and emotion understanding ability. There are three broad applications that might be considered: (a) identifying students at risk for failure, attrition, or underperformance; (b) selection decisions for high-stakes educational opportunities; and (c) policy decisions about the relative cost versus benefit of implementing SEL or EI training programs in schools.
The first two applications (identifying at risk students, and high-stakes selection) require careful consideration of response distortion issues. Particularly in a high-stakes selection context, test-takers are motivated to gain high scores and will distort their responses on rating scales to ‘fake high’ (Birkeland, Manson, Kisamore, Brannick, & Smith, 2006Viswesvaran & Ones, 1999). Faking is a consequential issue with personality scales, which use self-report or observer-report ratings that test takers can fake. Observer-reports do not necessarily solve this problem, as the observers are often not impartial, but may be school staff with a vested interest in their students gaining entrance to prestigious colleges or programs. Faking is a problem for rating-scale measures of EI, but not for ability scales (Day & Carroll, 2008Grubb & McDaniel, 2007Tett, Freund, Christiansen, Fox, & Coaster, 2012). The current meta-analysis is the first to demonstrate that the relationship between EI and academic performance holds for ability-based tests as well as rating scales (in fact, the relationship is actually higher for ability-based EI tests as compared to rating scales). As such, we demonstrate a pathway that might provide modest increments in high-stakes education selection decisions—using ability-based EI assessments of understanding and managing emotions (based on current results, other parts of ability EI are not important). Ability-based EI tests are already used for selection into medical schools in several countries, and evidence supports their use for selecting better candidates (Libbrecht, Lievens, Carette, & Côté, 2014Lievens & Sackett, 2006). However, such tests are rarely used in other broader education selection contexts. If EI is considered as a selection procedure (perhaps as an add-on to intelligence and personality assessment), we suggest that ability tests of understanding and managing emotions be preferred over rating scales (due to response distortion) or tests of facilitation or management (due to low incremental prediction over intelligence and personality).
A national and international focus on standardized tests to measure academic performance and milestones has lead schools, districts, states, and countries to focus on achievement in the narrow range of academic content that such tests focus on. Alongside this, classroom teachers face increasing challenges to their workload, including adapting the curriculum to individual students’ needs, the mainstreaming of students with special educational requirements, and adapting to rapidly changing curriculum and policy (Skaalvik & Skaalvik, 2007). Against this background, devoting resources to teaching children EI skills can be seen as taking teacher resources and classroom time away from more critical activities that will increase test scores and achievement. What our meta-analysis shows is that EI skills are in fact associated with higher academic performance. This implies that time spent teaching EI skills may not necessarily detract from student achievement, given that higher EI students also show higher achievement. Again, we highlight the different importance of the four EI abilities as a guide for where to focus skills training—a focus on perceiving emotions is likely to be less useful than a focus on understanding and managing emotions.
Our meta-analysis also has implications for the effects of the such training programs (or a focus on EI more generally) on the known achievement gaps between ethnic groups and between males and females. Although there is evidence that the Black-White achievement gap is slowly closing, differences in the achievement for minority students compared with White students remain substantial, at around 0.75 standard deviations for Black students and around 0.60 standard deviations for Hispanic students (Hansen, Mann Levesque, Quintero, & Valant, 2018). There is also increasing evidence that males are falling behind females in terms of the grades they receive and their participation in higher education (Fortin, Oreopoulos, & Phipps, 2015). Against this background, it is important to note that the effect of EI on academic performance does not appear to differ for minority students versus White students, and that gender differences are negligible and when significant favor males (who currently show lower achievement). These results imply, at the very least, that efforts to improve EI are unlikely to widen the achievement gaps.
The key role of emotion understanding and management is also important to consider in terms of EI training programs. Three recent meta-analyses on the effectiveness of EI training have reported significant increases in EI, with effect sizes of .45, .46, .51, and .61 (Hodzic, Scharfen, Ripoll, Holling, & Zenasni, 2018Mattingly & Kraiger, 2019Schutte, Malouff, & Thorsteinsson, 2013). Hodzic et al. found that programs based on the ability model were significantly more effective than those based on mixed models (g = .60 vs. .31), and that emotion understanding showed the largest increase of all the ability EI branches—significantly more than emotion facilitation (g = .69 vs. .42). That is, it seems that programs are effective for increasing ability EI, and particularly its emotion understanding facet. This is highly relevant for our own meta-analysis, where ability EI (and specifically emotion understanding) showed the highest association with academic performance. That is, EI training seems to produce the strongest increases in exactly those competencies that are most relevant for academic performance.
Although Hodzic et al. did not distinguish between EI training programs for workplace applications and EI training programs for schools and universities, several studies conducted in schools and universities report similar findings regarding the largest increases for emotion understanding. For example, Pool and Qualter (2012) conducted a training study in university students and found the largest increase in ability EI was for emotion understanding (and the second-largest for emotion management). Moreover, evidence from the RULER Feeling Words curriculum (an EI development program for secondary school students) shows that EI training programs increase grades as well as social and emotional competencies. Specifically, students completing the RULER showed improved school grades as well as improved teacher ratings of social and emotional competencies compared to control groups (Brackett, Rivers, Reyes, & Salovey, 2012). In fact, the relative increase in school grades was a larger effect than the relative increase in social and emotional competencies. That is, EI training programs are likely to increase academic performance as well as social and emotional outcomes, such that education decision-makers and policymakers are not faced with a decision of whether to invest in social/emotional wellbeing at the expense of student achievement—evidence suggests that these programs likely do both. This is a critical piece of information for schools deciding where to best allocate their resources.


Our results demonstrated only that EI and academic performance are significantly associated, but not that higher EI causes higher achievement. Only three of the citations reported a longitudinal design, such that the empirical evidence for EI causing later achievement is very weak (Costa & Faria, 2015Qualter et al., 2012Stewart & Chisholm, 2012). This association could occur because (a) higher EI causes increased academic performance, (b) higher achievement causes increased EI, or (c) there are one or more variables that influence both EI and academic performance. In the introduction, we outlined the reasons we believe theoretically that EI could cause later achievement. However, there are also feasible pathways by which greater academic performance could cause higher EI. Greater academic performance could feasibly result in increased self-esteem, greater opportunities for social and emotional development, and higher expectations for social skills and emotion regulation. High academic performance may act as a gateway for gifted and talented programs, streaming into enrichment activities, and a culture of high expectations from teachers, parents, and communities that permeate social and emotional behaviors as well as academic ones via the halo effect (Nisbett & Wilson, 1977). Conversely, low academic performance may act as a barrier to opportunities to develop social and emotional skills through loss of privileges for academic failures (e.g., losing recess playtime or evening socialization to complete work or denied extracurricular activity participation because of course failure), the development of strong negative emotions surrounding school and schoolwork, and the correspondingly low expectations for social and emotional behaviors. It seems likely that the reality is complex, with bidirectional effects of academic and emotional development, particularly in the earlier years of school.
One further limitation of the current article concerns the use of the meta-analytic correlation matrix (used to test Hypotheses 10 and 11). This was composed of estimates taken from different journal articles from different research teams, and therefore did not use the same methods for estimation nor the same samples. Although we used RVE in the current study, all other sources for effect sizes were obtained by aggregating multiple effect sizes from the same study. All studies except for Poropat (2009) corrected for unreliability as well as range restriction. The personality/academic performance estimation was not corrected for range restriction of measurement in either the predictor or criterion (Poropat, 2009). The possible effect of this would be to underestimate the prediction and relative importance of personality traits such as conscientiousness.

Future Research and Recommendations

One obvious future direction for further research is to test our three proposed mechanisms of the EI/performance relationship: (a) social relationship building, (b) regulation of academic emotions, and (c) content overlap between EI and academic subject matter. For point a, an analysis of content overlap between the competencies of EI and the different processes required for success in different disciplines could be undertaken by a panel of educators. Longitudinal research involving all three streams could test whether all three mediate ability EI, (a) and (b) mediate mixed EI, and (a) along mediates self-rated EI, as we proposed. As we mention above, there is a paucity of long-term longitudinal research on EI and academic performance. As such, examining mediators of the link as well as conducing lagged panel models to tease apart the direction of causation is important.
Although there is ample evidence that training EI works (e.g., Hodzic et al., 2018Mattingly & Kraiger, 2019Schutte et al., 2013), we are not aware of experimental studies on EI training that examine the effects of training different branches of EI. Such designs would isolate which facets of EI are most relevant for the improvement of which types of outcomes and would also provide stronger evidence for the causal direction from EI to academic performance.

US national survey of heterosexual & gay men: Sexual Practices and Satisfaction in Romantic Relationships

Sexual Practices and Satisfaction among Gay and Heterosexual Men in Romantic Relationships: A Comparison Using Coarsened Exact Matching in a U.S. National Sample. David Frederick  et al. The Journal of Sex Research, Jan 11 2021. https://www.tandfonline.com/doi/abs/10.1080/00224499.2020.1861424

Abstract: Gay men are underrepresented in research on sexual satisfaction. We examined sexual satisfaction and over 50 sexual practices in an online U.S. national survey of men in relationships. Coarsened exact matching created comparable samples of heterosexual (n = 3527) and gay (n = 452) men on six demographic factors, including relationship length. Results identified many similarities between the groups, including sexual frequency, orgasm frequency, duration of sex, and sexual satisfaction. The majority of heterosexual and gay men expressed physical or emotional affection during their last sexual encounter, reporting that they or their partner said “I love you” (66%; 57%) and engaged in deep kissing (69%; 75%) or gentle kissing (82%; 72%). Heterosexual men were less likely than gay men to usually-always receive (27%; 61%) or give (37%; 68%) oral sex when intimate in the past month; were less likely to view pornography with their partner (35%; 61%); but were more likely to give their partner massages in the past year to improve their sex lives (71%; 58%). Number of sexual communication behaviors was a strong predictor of sexual satisfaction, particularly for gay men (β =.36). These findings enhance our understanding of heterosexual and gay men’s sexual lives.

Popular version by Justin Lehmiller, Jun 28 2021: https://www.lehmiller.com/blog/2021/6/28/how-similar-or-different-are-the-sex-lives-of-gay-and-straight-men

The endowment effect may largely reflect “adaptively rational” behavior on the part of both buyers & sellers, given their beliefs about relevant markets, rather than any ownership-induced bias or change in intrinsic preferences

Achtypi, E., Ashby, N. J. S., Brown, G. D. A., Walasek, L., & Yechiam, E. (2021). The endowment effect and beliefs about the market. Decision, 8(1), 16-35. http://dx.doi.org/10.1037/dec0000143

Rolf Degen's take: https://twitter.com/DegenRolf/status/1348992873912479744

Abstract: The endowment effect occurs when people assign a higher value to an item they own than to the same item when they do not own it, and this effect is often taken to reflect an ownership-induced change in the intrinsic value people assign to the object. However recent evidence shows that valuations made by buyers and sellers are influenced by market prices provided for the individual products, suggesting a role for beliefs about the markets. Here we elicit individuals’ beliefs about whole distributions of market prices, enabling us to quantify whether or not a given transaction constitutes a “good deal” and to demonstrate how an endowment effect may reflect such considerations. In a meta-analysis and three laboratory experiments, we show for the first time that ownership has no effect on beliefs about either: (a) the quality of the item or (b) the appropriate market price for the item. Instead, we show that sellers demand a price for the item that matches their beliefs about the item’s relative quality and the distribution of market prices in the market. Buyers, in contrast, offer less than what they believe the appropriate market price is. Thus, we argue that the endowment effect may largely reflect “adaptively rational” behavior on the part of both buyers and sellers (given their beliefs about relevant markets) rather than any ownership-induced bias or change in intrinsic preferences.

Keywords: endowment effect, valuation, ownership, market price, good deal

General Discussion

We explored the hypothesis that valuations of buyers and sellers may reflect their differing beliefs about the broader market of prices and products (Brown, 2005Isoni, 2011Weaver & Frederick, 2012). Specifically, we developed a novel quantification of deal goodness in terms of the rank-based difference between the “appropriate” price (generated by the quality matched process) and the WTA and WTP monetary valuations. In terms of this good-dealness consideration, the endowment effect emerges because, given they will typically lack any strong desire to possess the object, buyers are only willing to purchase a product if they get a very good deal (relatively low market price given products’ quality). Sellers valuations, on the other hand, should correspond closely to the expected market price for a given good. Indeed, we show that sellers are willing to accept prices that correspond to their beliefs about what the given product should cost in the broader market. Buyers do not differ significantly from sellers in their beliefs about the market but are willing to pay substantially less than they believe the product costs in the market.
In Experiment 1, using a distribution elicitation task, we set out to determine whether beliefs about the distributions of market prices for a given class of consumer products (here water bottles) differ as a function of ownership status. We found no evidence of such a bias (see also Experiment 3 in Walasek, Yu, & Lagnado, 2018). In addition, we demonstrated that while both buyers and sellers value the object at less than its market price, buyers have a strong tendency to provide WTP amounts that correspond to the lowest end of the market price distribution. In Experiment 2, we replicated these findings and additionally found that owners and nonowners do not differ in their estimates of the product’s quality (in terms of how its quality ranks among other similar products). Moreover, owners and nonowners produced similar estimates of the product’s actual market price. Using a wide range of consumer products, valuations of sellers in Experiment 3 were closer to the estimated market price of each good than valuations of buyers were.
Our results are comparable to the findings reported in studies of the endowment effect for risky and ambiguous gambles. Sellers, not buyers, tend to set the minimum selling price to be close to the actual objective worth of a risky asset (Yechiam, Abofol, & Pachur, 2017Yechiam et al., 2017). Although in the present study we cannot make any statement about the ideal price of a consumer good for each person, our findings show that sellers’ valuations align with their perception of what the item should be worth as a product in the marketplace. Our results therefore extend previous efforts beyond the context of gambles.
Our study builds on and extends recent accounts suggesting that the endowment effect is at least in part driven by the considerations of what constitutes a good deal. This account differs from traditional explanations of the endowment effect in several key respects. Most importantly, unlike many accounts based on concepts such as loss aversion, our account does not assume ownership-induced changes in people’s valuations of the object if such valuation is defined in terms of underlying preferences (rather than, e.g., the profit that could possibly be made by selling it). In this respect, our account is similar to that of Isoni (2011). However, unlike Isoni, we do not need to assume “bad deal aversion” in that we do not require any asymmetry in hedonic impact of under- and overpaying. Of course, we do not discount the possibility that ownership status can influence people’s valuations via mechanisms such as asymmetric attention (Ashby, Walasek, & Glöckner, 2015Carmon & Ariely, 2000) or psychological ownership (Walasek et al., 2015Walasek et al., 2017).
It is important to note that our results do not provide direct causal evidence for the relation between perceptions of good dealness and valuations of owners and nonowners. Instead, our account is mostly descriptive—we illustrate how valuations of buyers and sellers map onto participants’ beliefs about the product and the broader context of the consumer market. By doing so, we can show patterns of valuations that fit well with recent theoretical and experimental developments in which the behavior of buyers and sellers is largely dictated by their consideration of how to secure (avoid) a good (bad) deal. Past work and our own results thus align with a simple pragmatic explanation of the endowment effect. When participants come to the lab and are offered a chance to purchase some consumer good, most people do not want it, even at a substantial discount (relative to its potential market value). Sellers on the other hand, value the product appropriately given on their knowledge of the market. If this account correctly captures people’s reasoning, there is no need to invoke any psychological biases, such as loss aversion, to explain the endowment effect. We do not provide direct evidence against loss aversion explanation of the endowment effect but rather offer an alternative explanation of the valuation gap. The conclusion of most researchers (i.e. that the endowment effect reflects loss aversion) is based on the assumption that participants’ valuations reveal their true underlying preferences, which are in turn assumed to be uncontaminated by strategic considerations or beliefs about the market. This assumption stands in contrast with the finding that even in an incentivized experiment, many buyers and sellers admit that their valuations were motivated by “seeking a good deal” or a consideration of a “reasonable or compromise price” and “selling cheaply to make sale likely” (for sellers, Brown, 2005). Further research is necessary to show how buyers and sellers might be differently influenced by their beliefs about the broader market. One potential extension of the present study would be to manipulate beliefs about the market. Using products that are less known among the participants, we would expect that valuations of sellers would be much more influenced than those of buyers by such a manipulation. The evidence presented by Weaver and Frederick (2012) is consistent with this prediction. Although our results do not disprove a role of loss aversion in the endowment effect, our alternative account suggests that the assumption of loss aversion is not necessary. We therefore suggest that explanations of the endowment effect in terms of loss aversion be discounted until and unless specific evidence for loss aversion is forthcoming. We argue that our account is parsimonious because it explains both the endowment effect and sellers’ greater sensitivity to observed market prices in terms of the difference between buyers’ and sellers’ beliefs about relevant markets without requiring the additional assumption of loss aversion (as postulated for instance by Weaver & Frederick, 2012).
In Experiments 2 and 3, we found that buyers and sellers did not differ in terms of how they rated the products on quality and benefit, respectively. These findings appear difficult to reconcile with the idea that endowment effect emerges, at least in part, due to the sense of emotional attachment that develops among owners (Shu & Peck, 2011Walasek et al., 2015). Indeed, participants who own an object have been shown in other studies to rate an object more favorably than nonowners—a phenomenon known as the mere ownership effect (Beggan, 1992). One plausible explanation for our results is that our design did not provide owners with enough opportunity (or reason) to develop any meaningful sense of psychological ownership. Even in the case of Experiment 2, where owners had more contact with the product than nonowners, such a short duration of ownership could simply be insufficient to generate any special bond between an individual and a consumer good.
The idea that perception of good dealness is an important influence on stated buying and selling prices has wider implications concerning the use of incentive compatible procedure like the BDM (Becker et al., 1964) to elicit true valuations. If the amount that people are willing to sell or buy an item for reflects market considerations relating to appropriate prices for an item of that quality, rather than or as well as an individual’s desire to possess the object, the valuations obtained using BDM-like procedures cannot be interpreted as unbiased measures of underlying preferences. At the very least, our results suggest that sellers and buyers engage in the valuation task differently, with sellers intuitively considering broader context of the market in making their decisions.

Men report stronger attraction to femininity in women's faces when their testosterone levels are high

Men report stronger attraction to femininity in women's faces when their testosterone levels are high. Lisa L.M. Welling et al. Hormones and Behavior, Volume 54, Issue 5, November 2008, Pages 703-708. https://doi.org/10.1016/j.yhbeh.2008.07.012

Abstract: Many studies have shown that women's judgments of men's attractiveness are affected by changes in levels of sex hormones. However, no studies have tested for associations between changes in levels of sex hormones and men's judgments of women's attractiveness. To investigate this issue, we compared men's attractiveness judgments of feminized and masculinized women's and men's faces in test sessions where salivary testosterone was high and test sessions where salivary testosterone was relatively low. Men reported stronger attraction to femininity in women's faces in test sessions where salivary testosterone was high than in test sessions where salivary testosterone was low. This effect was found to be specific to judgments of opposite-sex faces. The strength of men's reported attraction to femininity in men's faces did not differ between high and low testosterone test sessions, suggesting that the effect of testosterone that we observed for judgments of women's faces was not due to a general response bias. Collectively, these findings suggest that changes in testosterone levels contribute to the strength of men's reported attraction to femininity in women's faces and complement previous findings showing that testosterone modulates men's interest in sexual stimuli.

Keywords: TestosteroneMate preferencesSexual dimorphismFacesAttractiveness

Rolf Degen summarizing... Apes and monkeys lack the neural wiring necessary to deliberately articulate sounds

Primate Vocal Communication and the Evolution of Speech. Julia Fischer. Current Directions in Psychological Science, January 11, 2021. https://doi.org/10.1177/0963721420979580

Rolf Degen's take: https://twitter.com/DegenRolf/status/1348902265638289408

Abstract: Studies of nonhuman primate communication are often motivated by the desire to shed light on the evolution of speech. In contrast to human speech, the vocal repertoires of nonhuman primates are evolutionarily highly conserved. Within species-specific constraints, calls may vary in relation to the internal state of the caller or social experience. Receivers can use signalers’ calls to predict upcoming events or behavioral dispositions. Yet nonhuman primates do not appear to express or comprehend communicative or informative intent. Signalers are sensitive to the relation between their own actions and receivers’ responses, and thus, signaling behavior can be conceived as goal directed. Receivers’ ability to integrate information from multiple sources renders the system flexible and powerful. Researchers who take a linguistic or biological perspective on nonhuman primate communication should be aware of the strengths and limitations of their approaches. Both benefit from a focus on the mechanisms that underpin signaling and responses to signals.

Keywords: intention, meaning, primate communication, social cognition, vocalizations