Delivery of carbon, nitrogen, and sulfur to the silicate Earth by a giant impact. Damanveer S. Grewal, Rajdeep Dasgupta, Chenguang Sun, Kyusei Tsuno and Gelu Costin. Science Advances Jan 23 2019:Vol. 5, no. 1, eaau3669, DOI: 10.1126/sciadv.aau3669
Abstract: Earth’s status as the only life-sustaining planet is a result of the timing and delivery mechanism of carbon (C), nitrogen (N), sulfur (S), and hydrogen (H). On the basis of their isotopic signatures, terrestrial volatiles are thought to have derived from carbonaceous chondrites, while the isotopic compositions of nonvolatile major and trace elements suggest that enstatite chondrite–like materials are the primary building blocks of Earth. However, the C/N ratio of the bulk silicate Earth (BSE) is superchondritic, which rules out volatile delivery by a chondritic late veneer. In addition, if delivered during the main phase of Earth’s accretion, then, owing to the greater siderophile (metal loving) nature of C relative to N, core formation should have left behind a subchondritic C/N ratio in the BSE. Here, we present high pressure-temperature experiments to constrain the fate of mixed C-N-S volatiles during core-mantle segregation in the planetary embryo magma oceans and show that C becomes much less siderophile in N-bearing and S-rich alloys, while the siderophile character of N remains largely unaffected in the presence of S. Using the new data and inverse Monte Carlo simulations, we show that the impact of a Mars-sized planet, having minimal contributions from carbonaceous chondrite-like material and coinciding with the Moon-forming event, can be the source of major volatiles in the BSE.
Friday, January 25, 2019
“Forward flow”: A new measure to quantify free thought and predict creativity
Gray, K., Anderson, S., Chen, E. E., Kelly, J. M., Christian, M. S., Patrick, J., . . . Lewis, K. (2019). “Forward flow”: A new measure to quantify free thought and predict creativity. American Psychologist, http://dx.doi.org/10.1037/amp0000391
Abstract: When the human mind is free to roam, its subjective experience is characterized by a continuously evolving stream of thought. Although there is a technique that captures people’s streams of free thought—free association—its utility for scientific research is undermined by two open questions: (a) How can streams of thought be quantified? (b) Do such streams predict psychological phenomena? We resolve the first issue—quantification—by presenting a new metric, “forward flow,” that uses latent semantic analysis to capture the semantic evolution of thoughts over time (i.e., how much present thoughts diverge from past thoughts). We resolve the second issue—prediction—by examining whether forward flow predicts creativity in the lab and the real world. Our studies reveal that forward flow predicts creativity in college students (Study 1) and a representative sample of Americans (Study 2), even when controlling for intelligence. Studies also reveal that membership in real-world creative groups—performance majors (Study 3), professional actors (Study 4) and entrepreneurs (Study 5)—is predicted by forward flow, even when controlling for performance on divergent thinking tasks. Study 6 reveals that forward flow in celebrities’ social media posts (i.e., on Twitter) predicts their creative achievement. In addition to creativity, forward flow may also help predict mental illness, emotional experience, leadership ability, adaptability, neural dynamics, group productivity, and cultural success. We present open-access online tools for assessing and visualizing forward flow for both illustrative and large-scale data analytic purposes.
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Forward Flow and Creativity
Both anecdotal and scientific evidence suggest a potential link between forward flow and creativity—in particular, divergent thinking.3 Anecdotally, creative people are often good at generating works that leave behind the past: Jackson Pollock moved beyond easels and brushes and Einstein moved beyond Newtonian mechanics. This “forward movement” appears in many artistic and scientific creative works as visionaries eschew tradition for originality. Indeed, Walt Disney’s recipe for creativity makes this connection explicit: “Around here… we don't look backwards for very long. We keep moving forward, opening up new doors and doing new things.” As thinking is for doing (Fiske, 1992), those who complete more “forward-moving” creative actions might also have more “forward-moving” thoughts.
Recent studies support the idea that creativity is related to individual differences in memory organization (Hass, 2017; Heinen & Johnson, 2017)—differences that allow more creative participants to connect ideas that are further apart in memory (Kenett, Anaki, & Faust, 2014). Most relevant to the current work, associative dynamics appear related to both creative performance and default network activity (Marron et al., 2018). However, one limitation of these studies is that they all assess task-bound thoughts, measuring cognitive processes while participants are engaged in creative tasks or are explicitly instructed to be creative. Although many real-world situations entail conscious efforts to be creative, here we examine whether features of unconstrained thought—free association without instructions to be creative—might also predict creativity across diverse settings and populations. Can forward flow predict divergent thinking and perhaps even the choices and outcomes related to people’s careers?
Importantly, we do not claim that forward flow is the “best” predictor or measure of creativity. Creativity is predicted by expertise (Baer & Kaufman, 2005), personality (Kaufman et al., 2016), attentional control (Beaty, Benedek, Silvia, & Schacter, 2016), one’s social network (Perry-Smith & Shalley, 2003), and the broader cultural milieu (Rudowicz, 2003). There are also many measures of creativity which predict creative performance. Nevertheless, revealing the predictive power of forward flow in creativity would both contribute to this important body of work and point to the general methodological utility of assessing streams of free thought.
Linear or Non-Linear? Forward Flow and Mental Illness
One important remaining question is whether the relationship between forward flow and creativity is linear. Some psychological disorders are characterized by disorganized thoughts (e.g., schizophrenia; Moritz, Woodward, Küppers, Lausen, & Schickel, 2003); and while such disorganization likely yields high forward flow, it may not yield high creativity—especially insofar as creativity requires usefulness in addition to originality (Runco & Jaeger, 2012). While there are robust correlations between mental illness and creativity (Kyaga et al., 2013), even our most creative samples—acting students and creative professionals—had a mean forward flow of ~.83, which is some distance from the theoretical maximum of 1.00. It may be that a completely disorganized stream of consciousness represented by extreme forward flow is tied to detriments in creative performance. If true, this suggests forward flow—at its upper bounds—might also be a useful indicator of some kinds of mental illness, consistent with recent work on atypicality in semantic memory structure (Faust & Kenett, 2014). Moreover, although we have suggested high forward flow helps creativity, it may hinder task performance when focus is required—e.g., for air traffic controllers or pilots (Kanfer & Ackerman, 1989).
Abstract: When the human mind is free to roam, its subjective experience is characterized by a continuously evolving stream of thought. Although there is a technique that captures people’s streams of free thought—free association—its utility for scientific research is undermined by two open questions: (a) How can streams of thought be quantified? (b) Do such streams predict psychological phenomena? We resolve the first issue—quantification—by presenting a new metric, “forward flow,” that uses latent semantic analysis to capture the semantic evolution of thoughts over time (i.e., how much present thoughts diverge from past thoughts). We resolve the second issue—prediction—by examining whether forward flow predicts creativity in the lab and the real world. Our studies reveal that forward flow predicts creativity in college students (Study 1) and a representative sample of Americans (Study 2), even when controlling for intelligence. Studies also reveal that membership in real-world creative groups—performance majors (Study 3), professional actors (Study 4) and entrepreneurs (Study 5)—is predicted by forward flow, even when controlling for performance on divergent thinking tasks. Study 6 reveals that forward flow in celebrities’ social media posts (i.e., on Twitter) predicts their creative achievement. In addition to creativity, forward flow may also help predict mental illness, emotional experience, leadership ability, adaptability, neural dynamics, group productivity, and cultural success. We present open-access online tools for assessing and visualizing forward flow for both illustrative and large-scale data analytic purposes.
---
Forward Flow and Creativity
Both anecdotal and scientific evidence suggest a potential link between forward flow and creativity—in particular, divergent thinking.3 Anecdotally, creative people are often good at generating works that leave behind the past: Jackson Pollock moved beyond easels and brushes and Einstein moved beyond Newtonian mechanics. This “forward movement” appears in many artistic and scientific creative works as visionaries eschew tradition for originality. Indeed, Walt Disney’s recipe for creativity makes this connection explicit: “Around here… we don't look backwards for very long. We keep moving forward, opening up new doors and doing new things.” As thinking is for doing (Fiske, 1992), those who complete more “forward-moving” creative actions might also have more “forward-moving” thoughts.
Recent studies support the idea that creativity is related to individual differences in memory organization (Hass, 2017; Heinen & Johnson, 2017)—differences that allow more creative participants to connect ideas that are further apart in memory (Kenett, Anaki, & Faust, 2014). Most relevant to the current work, associative dynamics appear related to both creative performance and default network activity (Marron et al., 2018). However, one limitation of these studies is that they all assess task-bound thoughts, measuring cognitive processes while participants are engaged in creative tasks or are explicitly instructed to be creative. Although many real-world situations entail conscious efforts to be creative, here we examine whether features of unconstrained thought—free association without instructions to be creative—might also predict creativity across diverse settings and populations. Can forward flow predict divergent thinking and perhaps even the choices and outcomes related to people’s careers?
Importantly, we do not claim that forward flow is the “best” predictor or measure of creativity. Creativity is predicted by expertise (Baer & Kaufman, 2005), personality (Kaufman et al., 2016), attentional control (Beaty, Benedek, Silvia, & Schacter, 2016), one’s social network (Perry-Smith & Shalley, 2003), and the broader cultural milieu (Rudowicz, 2003). There are also many measures of creativity which predict creative performance. Nevertheless, revealing the predictive power of forward flow in creativity would both contribute to this important body of work and point to the general methodological utility of assessing streams of free thought.
Linear or Non-Linear? Forward Flow and Mental Illness
One important remaining question is whether the relationship between forward flow and creativity is linear. Some psychological disorders are characterized by disorganized thoughts (e.g., schizophrenia; Moritz, Woodward, Küppers, Lausen, & Schickel, 2003); and while such disorganization likely yields high forward flow, it may not yield high creativity—especially insofar as creativity requires usefulness in addition to originality (Runco & Jaeger, 2012). While there are robust correlations between mental illness and creativity (Kyaga et al., 2013), even our most creative samples—acting students and creative professionals—had a mean forward flow of ~.83, which is some distance from the theoretical maximum of 1.00. It may be that a completely disorganized stream of consciousness represented by extreme forward flow is tied to detriments in creative performance. If true, this suggests forward flow—at its upper bounds—might also be a useful indicator of some kinds of mental illness, consistent with recent work on atypicality in semantic memory structure (Faust & Kenett, 2014). Moreover, although we have suggested high forward flow helps creativity, it may hinder task performance when focus is required—e.g., for air traffic controllers or pilots (Kanfer & Ackerman, 1989).
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