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• W3009231711 abstract "Human metacognition involves discrimination, interpretation, and broadcasting of subtle cues indicating the rightness of ongoing thought and behaviour.We propose that human metacognition is made fit for purpose by cultural evolution rather than genetic evolution.In particular, we present evidence that the effective discrimination, interpretation, and broadcasting of metacognitive cues depends on cultural learning.The cultural origins hypothesis advances a programme of research on the development of metacognition, cultural variation, individual differences, and cross-species comparisons. Metacognition – the ability to represent, monitor and control ongoing cognitive processes – helps us perform many tasks, both when acting alone and when working with others. While metacognition is adaptive, and found in other animals, we should not assume that all human forms of metacognition are gene-based adaptations. Instead, some forms may have a social origin, including the discrimination, interpretation, and broadcasting of metacognitive representations. There is evidence that each of these abilities depends on cultural learning and therefore that cultural selection might shape human metacognition. The cultural origins hypothesis is a plausible and testable alternative that directs us towards a substantial new programme of research. Metacognition – the ability to represent, monitor and control ongoing cognitive processes – helps us perform many tasks, both when acting alone and when working with others. While metacognition is adaptive, and found in other animals, we should not assume that all human forms of metacognition are gene-based adaptations. Instead, some forms may have a social origin, including the discrimination, interpretation, and broadcasting of metacognitive representations. There is evidence that each of these abilities depends on cultural learning and therefore that cultural selection might shape human metacognition. The cultural origins hypothesis is a plausible and testable alternative that directs us towards a substantial new programme of research. How do cognitive mechanisms become fit for purpose? They are all complex products of nature and nurture, but who or what designs the features that enable cognitive processes to do their jobs? How come visual systems can see, learning mechanisms can learn, and reasoning processes can reason? In many cases, gene-based selection (see Glossary) leads the design team. The visual system can see primarily because it has been honed by natural selection over biological generations. Variant systems were genetically inherited, and, through differential reproduction, those that were better at processing visual information proliferated while the others died out. In some cases, intentional design is also involved [1.Dennett D.C. From Bacteria to Bach and Back: The Evolution of Minds. W. W. Norton, 2017Google Scholar]. The cognitive mechanisms enabling you to read these words were designed in part by educationalists. The people who teach us to read, and designers of literacy programmes, make new cognitive mechanisms from old parts. With foresight and deliberation, they turn mechanisms that were designed by genetic evolution for small object recognition into a cognitive system for reading [2.Dehaene S. Dehaene-Lambertz G. Is the brain prewired for letters?.Nat. Neurosci. 2016; 19: 1192-1193Crossref PubMed Scopus (16) Google Scholar]. For some cognitive mechanisms, cultural selection is a third member of the design team, alongside genetic evolution and intentional design. Recent evidence suggests that a range of cognitive mechanisms, including imitation and mindreading (or theory of mind), have been shaped by a cultural selection process analogous to gene-based selection [3.Atzil S. et al.Growing a social brain.Nat. Hum. Behav. 2018; 2: 624-636Crossref PubMed Google Scholar, 4.Germar M. Mojzisch A. Learning of social norms can lead to a persistent perceptual bias: a diffusion model approach.J. Exp. Soc. Psychol. 2019; 84: 103801Crossref Scopus (1) Google Scholar, 5.Heyes C.M. Frith C.D. The cultural evolution of mind reading.Science. 2014; 344: 1243091Crossref PubMed Scopus (157) Google Scholar, 6.Ho M.K. et al.Social is special: a normative framework for teaching with and learning from evaluative feedback.Cognition. 2017; 167: 91-106Crossref PubMed Scopus (9) Google Scholar, 7.Heyes C. Empathy is not in our genes.Neurosci. Biobehav. Rev. 2018; 95: 499-507Crossref PubMed Scopus (11) Google Scholar]. In this cultural evolutionary process, variants arise in individual development, rather than by genetic mutation, and are inherited via social interaction rather than DNA. Good variants are culturally learned (e.g., copied) by more agents, but, unlike intentional design, this need not be because the teachers or the learners understand what makes them good. In this opinion article, we suggest that an important kind of metacognition has been made fit for purpose primarily by the latter two members of the team – intentional design and cultural evolution – rather than genetic selection. Here, we focus on the role of cultural evolution. We survey evidence that explicit metacognition (Box 1) is social in origin, and we outline an empirical programme that would allow the cultural origins hypothesis to be further developed and tested. First, however, we outline the many functions of metacognition in individual and group decision-making.Box 1Explicit MetacognitionIn this article we are concerned with what we call explicit metacognition. A representation is explicit, in our sense, when it is conscious and represented in working memory so that it can be used by processes of cognitive control. Thus, a hallmark of explicit metacognition is that it is sensitive to concurrent processing load. Humans typically communicate explicit metacognitive representations verbally. For example, we can tell others when we are uncertain about what we have seen. However, we can also communicate nonverbally about our explicit metacognitive states; and it is an open question whether language is necessary for an individual to have the capacity for explicit metacognition.Metacognition also operates in implicit processes that are automatic and relatively insensitive to cognitive load. The contrast between explicit and implicit metacognition can be seen in research on error monitoring in skilled typists [130.Logan G.D. Crump M.J.C. Cognitive illusions of authorship reveal hierarchical error detection in skilled typists.Science. 2010; 330: 683-686Crossref PubMed Scopus (86) Google Scholar]. Automatic monitoring processes make skilled typists fractionally slower on the next keystroke after they have made an error. Explicit metacognition, by contrast, allows the typist to report that they have made an error. The factors that affect implicit and explicit metacognition in these scenarios are experimentally dissociable.Metacognition is sometimes assumed to require consciousness, but here we adopt the more liberal definition that does not presuppose that metacognitive processes are conscious. So, a nonconscious representation or evaluation of a cognitive state or process can count as metacognitive. Explicit metacognition does require consciousness but note that our usage does not make explicit synonymous with conscious (which is another common usage). Our use is more restrictive. It excludes automatic metacognitive processes that do not depend on working memory and are insensitive to cognitive load, even if they involve conscious states like feelings of fluency.We can further distinguish two ways in which a metacognitive assessment of a decision can be computed [48.Fleming S.M. Daw N.D. Self-evaluation of decision-making: a general Bayesian framework for metacognitive computation.Psychol. Rev. 2017; 124: 91-114Crossref PubMed Scopus (103) Google Scholar]. First-order confidence is based wholly on the state or states used to take the decision itself. Second-order confidence is computed by a separate system and considers further factors (see Figure 2 in main text). Explicit metacognition is typically the result of a second-order computation. In this article we are concerned with what we call explicit metacognition. A representation is explicit, in our sense, when it is conscious and represented in working memory so that it can be used by processes of cognitive control. Thus, a hallmark of explicit metacognition is that it is sensitive to concurrent processing load. Humans typically communicate explicit metacognitive representations verbally. For example, we can tell others when we are uncertain about what we have seen. However, we can also communicate nonverbally about our explicit metacognitive states; and it is an open question whether language is necessary for an individual to have the capacity for explicit metacognition. Metacognition also operates in implicit processes that are automatic and relatively insensitive to cognitive load. The contrast between explicit and implicit metacognition can be seen in research on error monitoring in skilled typists [130.Logan G.D. Crump M.J.C. Cognitive illusions of authorship reveal hierarchical error detection in skilled typists.Science. 2010; 330: 683-686Crossref PubMed Scopus (86) Google Scholar]. Automatic monitoring processes make skilled typists fractionally slower on the next keystroke after they have made an error. Explicit metacognition, by contrast, allows the typist to report that they have made an error. The factors that affect implicit and explicit metacognition in these scenarios are experimentally dissociable. Metacognition is sometimes assumed to require consciousness, but here we adopt the more liberal definition that does not presuppose that metacognitive processes are conscious. So, a nonconscious representation or evaluation of a cognitive state or process can count as metacognitive. Explicit metacognition does require consciousness but note that our usage does not make explicit synonymous with conscious (which is another common usage). Our use is more restrictive. It excludes automatic metacognitive processes that do not depend on working memory and are insensitive to cognitive load, even if they involve conscious states like feelings of fluency. We can further distinguish two ways in which a metacognitive assessment of a decision can be computed [48.Fleming S.M. Daw N.D. Self-evaluation of decision-making: a general Bayesian framework for metacognitive computation.Psychol. Rev. 2017; 124: 91-114Crossref PubMed Scopus (103) Google Scholar]. First-order confidence is based wholly on the state or states used to take the decision itself. Second-order confidence is computed by a separate system and considers further factors (see Figure 2 in main text). Explicit metacognition is typically the result of a second-order computation. Explicit metacognition uses conscious representations in working memory to monitor or evaluate – and often to control – cognitive states and processes. Explicit metacognition (here metacognition, when not qualified) is sensitive to cognitive load, and is typically slow, deliberate, and verbally reportable [8.Shea N. Frith C.D. Dual-process theories and consciousness: the case for ‘Type Zero’ cognition.Neurosci. Conscious. 2016; 2016niw005Crossref PubMed Google Scholar,9.Shea N. et al.Supra-personal cognitive control and metacognition.Trends Cogn. Sci. 2014; 18: 186-193Abstract Full Text Full Text PDF PubMed Scopus (118) Google Scholar]. It yields feelings of knowing and confidence judgements, allowing us to think and report ‘I’m sure’ and ‘I’m not so sure’ about our perceptions, memories, and decisions. The adoption of frameworks inherited from psychophysics and signal detection theory has made possible the objective measurement of metacognitive ability in laboratory tasks, by assessing the bias and sensitivity of judgments of confidence in relation to task performance [10.Fleming S.M. Lau H.C. How to measure metacognition.Front. Hum. Neurosci. 2014; 8: 1-9Crossref PubMed Scopus (245) Google Scholar]. Metacognitive representations allow information captured by specialised sensorimotor processes to be accessed by other processes in the same agent and by the cognitive systems of other agents – it has both intrapersonal and suprapersonal control functions [9.Shea N. et al.Supra-personal cognitive control and metacognition.Trends Cogn. Sci. 2014; 18: 186-193Abstract Full Text Full Text PDF PubMed Scopus (118) Google Scholar]. Metacognition contributes to effective intrapersonal decision-making in a range of contexts. For instance, it helps ensure the smooth operation of ongoing thought and behaviour, by helping us recognise our errors [11.Rabbit P.M.A. Error correction time without external error signals.Nature. 1966; 212: 438Crossref PubMed Scopus (147) Google Scholar], regulate deployment of executive functions [12.Bryce D. et al.The relationships among executive functions, metacognitive skills and educational achievement in 5 and 7 year-old children.Metacogn. Learn. 2015; 10: 181-198Crossref Scopus (37) Google Scholar,13.Spiess M.A. et al.Development and longitudinal relationships between children’s executive functions, prospective memory, and metacognition.Cogn. Dev. 2016; 38: 99-113Crossref Scopus (16) Google Scholar], and detect lapses of attention [14.Adam K.C.S. Vogel E.K. Confident failures: lapses of working memory reveal a metacognitive blind spot.Atten. Percept. Psychophys. 2017; 79: 1506-1523Crossref PubMed Scopus (14) Google Scholar]. It also enables cognitive offloading – the use of physical actions such as tilting the head, making notes, and finger counting – to alter the information processing requirements of a task to reduce cognitive demand [15.Risko E.F. Gilbert S.J. Cognitive offloading.Trends Cogn. Sci. 2016; 20: 676-688Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar,16.Hu X. et al.A role for metamemory in cognitive offloading.Cognition. 2019; 193: 104012Crossref PubMed Scopus (0) Google Scholar]. In educational settings, metacognition regulates study time, and thereby enables children and adults to learn more from reading texts [17.Michalsky T. et al.Elementary school children reading scientific texts: effects of metacognitive instruction.J. Educ. Res. 2009; 102: 363-374Crossref Scopus (27) Google Scholar, 18.Metcalfe J. Metacognitive judgments and control of study.Curr. Dir. Psychol. Sci. 2009; 18: 159-163Crossref PubMed Scopus (187) Google Scholar, 19.Metcalfe J. Finn B. Metacognition and control of study choice in children.Metacogn. Learn. 2013; 8: 19-46Crossref Scopus (35) Google Scholar], which in turn may contribute to the development of general intelligence [20.Fandakova Y. et al.Changes in ventromedial prefrontal and insular cortex support the development of metamemory from childhood into adolescence.Proc. Natl. Acad. Sci. U. S. A. 2017; 114: 7582-7587Crossref PubMed Scopus (9) Google Scholar]. Accordingly, failures of metacognition may lead to maladaptive decision-making: people who are overconfident of their knowledge about information security (a positive metacognitive bias) are more likely to take risks when using the internet [21.Sawaya Y. et al.Self-confidence trumps knowledge: a cross-cultural study of security behavior.in: Conf. Hum. Factors Comput. Syst. - Proc. 2017-May. 2017: 2202-2214Crossref Scopus (14) Google Scholar], and people with weaker metacognitive sensitivity are more likely to hold radical beliefs at both ends of the political spectrum [22.Rollwage M. et al.Metacognitive failure as a feature of those holding radical beliefs.Curr. Biol. 2018; 28: 4014-4021.e8Abstract Full Text Full Text PDF PubMed Scopus (25) Google Scholar,23.Zmigrod L. et al.Cognitive inflexibility predicts extremist attitudes.Front. Psychol. 2019; 10: 1-13Crossref PubMed Scopus (3) Google Scholar]. Metacognition also plays a central role in suprapersonal decision-making [9.Shea N. et al.Supra-personal cognitive control and metacognition.Trends Cogn. Sci. 2014; 18: 186-193Abstract Full Text Full Text PDF PubMed Scopus (118) Google Scholar,24.Dunstone J. Caldwell C.A. Cumulative culture and explicit metacognition: a review of theories, evidence and key predictions.Palgrave Commun. 2018; 4: 1-11Crossref Scopus (0) Google Scholar,25.Heyes C. Who knows? metacognitive social learning strategies.Trends Cogn. Sci. 2016; 20: 204-213Abstract Full Text Full Text PDF PubMed Scopus (59) Google Scholar]. It not only enables individuals to monitor their own cognitive processes, but it also enables broadcast and sharing of otherwise private mental states with others. Cognitive offloading often involves depositing information with, or soliciting information from, other agents [15.Risko E.F. Gilbert S.J. Cognitive offloading.Trends Cogn. Sci. 2016; 20: 676-688Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar,26.Goupil L. et al.Infants ask for help when they know they don’t know.Proc. Natl. Acad. Sci. U. S. A. 2016; 113: 3492-3496Crossref PubMed Google Scholar]. When people are making perceptual decisions together, ‘two heads are better than one’ when each person communicates accurate metacognitive representations about their judgements [27.Bahrami B. et al.Optimally interacting minds.Science. 2010; 329: 1081-1085Crossref PubMed Scopus (303) Google Scholar, 28.Fusaroli R. et al.Coming to terms: quantifying the benefits of linguistic coordination.Psychol. Sci. 2012; 23: 931-939Crossref PubMed Scopus (128) Google Scholar, 29.Bang D. et al.Does interaction matter? Testing whether a confidence heuristic can replace interaction in collective decision-making.Conscious. Cogn. 2014; 26: 13-23Crossref PubMed Scopus (33) Google Scholar, 30.Bang D. et al.Confidence matching in group decision-making.Nat. Hum. Behav. 2017; 1Crossref Scopus (21) Google Scholar]. Jurors use witness confidence and other metacognitive representations (e.g., calibration of confidence relative to accuracy) in deciding whether to trust witness testimony [31.Tenney E.R. et al.Calibration trumps confidence as a basis for witness credibility: research report.Psychol. Sci. 2007; 18: 46-50Crossref PubMed Scopus (68) Google Scholar]. When coordinating complex actions in team sports, people use metacognitive representations to decide the contribution of each team member [32.Poizat G. et al.Analysis of contextual information sharing during table tennis matches: An empirical study of coordination in sports.Int. J. Sport Exerc. Psychol. 2009; 7: 465-487Crossref Google Scholar,33.Lausic D. et al.Intrateam communication and performance in doubles tennis.Res. Q. Exerc. Sport. 2009; 80: 281-290Crossref PubMed Google Scholar]. The suprapersonal functions of metacognition make it plausible, from an engineering perspective, that metacognition has been shaped by cultural selection. The benefits of enhanced metacognitive skills accrue, not only to the owner of the skills, but also to other members of the social group with whom they make decisions and coordinate action. Consequently, it is in the interests of a person with enhanced metacognitive skills to teach those skills, deliberately or inadvertently, to others in their group, and there is reason to expect more skilled individuals to be more effective teachers – a condition for cultural selection. In comparison to this focus on the functions of metacognition, there has been little enquiry about its origins – about the design team that enables metacognition to fulfil its intra- and suprapersonal roles. Researchers tend to assume that genetic evolution has played a major part in making metacognition fit for purpose [34.Schwarz N. Metacognitive experiences in consumer judgment and decision making.J. Consum. Psychol. 2004; 14: 332-348Crossref Google Scholar,35.Mercier H. Sperber D. The Enigma of Reason. Harvard University Press, 2017Crossref Google Scholar] and/or to underline the importance of individual learning [36.Alter A.L. Oppenheimer D.M. Uniting the tribes of fluency to form a metacognitive nation.Personal. Soc. Psychol. Rev. 2009; 13: 219-235Crossref PubMed Scopus (603) Google Scholar, 37.Carpenter J. et al.Domain-general enhancements of metacognitive ability through adaptive training.J. Exp. Psychol. Gen. 2019; 148: 51-64Crossref PubMed Scopus (20) Google Scholar, 38.Schmidt C. et al.Meditation focused on self-observation of the body impairs metacognitive efficiency.Conscious. Cogn. 2019; 70: 116-125Crossref PubMed Scopus (0) Google Scholar, 39.Timmermans B. et al.Higher order thoughts in action: consciousness as an unconscious re-description process.Philos. Trans. R. Soc. B Biol. Sci. 2012; 367: 1412-1423Crossref PubMed Scopus (45) Google Scholar, 40.Carruthers P. The Opacity of Mind: An Integrative Theory of Self-Knowledge. Oxford University Press, 2011Crossref Google Scholar]. We have no doubt that genetic evolution has played a role, and, given the continuing development of metacognition in late childhood and adolescence [13.Spiess M.A. et al.Development and longitudinal relationships between children’s executive functions, prospective memory, and metacognition.Cogn. Dev. 2016; 38: 99-113Crossref Scopus (16) Google Scholar,20.Fandakova Y. et al.Changes in ventromedial prefrontal and insular cortex support the development of metamemory from childhood into adolescence.Proc. Natl. Acad. Sci. U. S. A. 2017; 114: 7582-7587Crossref PubMed Scopus (9) Google Scholar,41.de Bruin A.B.H. van Gog T. Improving self-monitoring and self-regulation: from cognitive psychology to the classroom.Learn. Instr. 2012; 22: 245-252Crossref Scopus (61) Google Scholar,42.Weil L.G. et al.The development of metacognitive ability in adolescence.Conscious. Cogn. 2013; 22: 264-271Crossref PubMed Scopus (94) Google Scholar], that learning is crucial. Indeed, recent studies of human infants suggest that they may have a core, genetically inherited capacity for implicit metacognition [26.Goupil L. et al.Infants ask for help when they know they don’t know.Proc. Natl. Acad. Sci. U. S. A. 2016; 113: 3492-3496Crossref PubMed Google Scholar,43.Goupil L. Kouider S. Developing a reflective mind: from core metacognition to explicit self-reflection.Curr. Dir. Psychol. Sci. 2019; (Published online May 31, 2019. https://doi.org/10.1177/0963721419848672)Crossref Scopus (2) Google Scholar], providing a platform for the slow development of explicit metacognition through learning and experience. However, by contrast with previous work on metacognition, we suggest that a particular kind of learning – cultural learning – is of overriding importance. Learning is cultural when one agent, a receiver, learns from another agent, a sender. In cultural learning, by contrast with other kinds of social learning, what the receiver learns through social interaction with the sender is similar to, and causally dependent on, what the sender knows [44.Heyes C. Is morality a gadget? Nature, nurture and culture in moral development.Synthese. 2019; (Published online October 11, 2019. https://doi.org/10.1007/s11229-019-02348-w)Crossref Scopus (0) Google Scholar]. Cultural learning often, but not always, involves teaching. The sender may intend to communicate information to the receiver, or instead involuntarily leak information that is picked up by the receiver. If metacognition is acquired through cultural learning, it may be fit for purpose not because of gene-based selection and intentional design, but also due to cultural selection – a selection process operating on variants transmitted culturally over generations of learners. Here, we survey evidence that metacognition is acquired through cultural learning. A stronger claim would be that metacognition is made fit for purpose by cultural selection; acquired through cultural learning and rendered adaptive by a process of natural selection acting on the culturally learned variants. There is currently less evidence in support of the stronger claim, partly because it has not yet been seriously investigated. However, there is evidence of adaptively relevant variation in metacognitive ability (i.e., in the relevant phenotype) across cultural groups and societies. Given the timescales involved, this is unlikely to be the result of gene-based selection. It is therefore plausible that cultural selection has been at work, selecting the adaptive variants in the metacognitive abilities observed in different cultural groups. Current models of metacognition suggest that a range of first-order monitoring signals need to be re-represented by the metacognitive system in order to become available for the kind of intra- and suprapersonal control functions highlighted above [9.Shea N. et al.Supra-personal cognitive control and metacognition.Trends Cogn. Sci. 2014; 18: 186-193Abstract Full Text Full Text PDF PubMed Scopus (118) Google Scholar,45.Clark A. Karmiloff-Smith A. The cognizer’s innards: a psychological and philosophical perspective on the development of thought.Mind Lang. 1993; 8: 487-519Crossref Scopus (125) Google Scholar,46.Cleeremans A. Connecting conscious and unconscious processing.Cogn. Sci. 2014; 38: 1286-1315Crossref PubMed Scopus (12) Google Scholar] (Figure 1). Many of these first-order signals are encapsulated within the perception-action loop. For instance, if a reaching movement is subtly deviated from its trajectory by an unseen force, the person will correct the deviation without any explicit metacognitive awareness that this correction has been applied [47.Fourneret P. Jeannerod M. Limited conscious monitoring of motor performance in normal subjects.Neuropsychologia. 1998; 36: 1133-1140Crossref PubMed Scopus (353) Google Scholar]. Metacognitive representations of performance are instead the result of second-order computations with respect to the perception–action cycle. One useful perspective on the computational problem facing metacognition is to treat it as analogous to regular perception albeit with different inputs. Just as perception is engaged with building a model of the environment from limited data, so metacognition needs to build a model of system performance using some form of inference about various cues [48.Fleming S.M. Daw N.D. Self-evaluation of decision-making: a general Bayesian framework for metacognitive computation.Psychol. Rev. 2017; 124: 91-114Crossref PubMed Scopus (103) Google Scholar]. This is consistent with the popular inferential view of how metamemory judgments are formed [49.Koriat A. Monitoring one’s own knowledge during study: a cue-utilization approach to judgments of learning.J. Exp. Psychol. Gen. 1997; 126: 349-370Crossref Google Scholar], and implies that first-order monitoring signals need to be discriminated and interpreted by the metacognitive system. In the following, we identify three components that comprise the capacity for metacognition (Figure 1): (i) discrimination – distinguishing metacognitive feelings from one another, and from feelings that do not arise from metacognitive computations; (ii) interpretation – working out the significance of metacognitive representations, for example, whether ease of processing indicates that an object is familiar; and (iii) broadcasting – learning efficient communicative conventions for sharing metacognitive representations with other agents. As we introduce each of these components, and in the section that follows, we survey evidence that their development depends on cultural learning, and we identify opportunities to test this hypothesis further in future research. Relevant inputs for metacognition must be distinguished from one another (e.g., stimulus visibility versus decision confidence) and from interoceptive signals, including emotional states (e.g., low confidence versus fear). It would be maladaptive to share within the cognitive system, or broadcast to other agents, feelings that reflect states of the body or the world as if they represent properties of cognitive representations and processes. For instance, fear of a bear should not be mistaken for uncertainty about whether one has seen a bear. However, exactly this kind of crosstalk can be observed in laboratory experiments on metacognition. For example, when people were briefly flashed a face with a disgusted expression, their confidence in an incidental perceptual task was subtly modulated [50.Allen M. et al.Unexpected arousal modulates the influence of sensory noise on confidence.eLife. 2016; 5: 1-17Crossref Scopus (52) Google Scholar]. 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• W3009231711 title "Knowing Ourselves Together: The Cultural Origins of Metacognition" @default.
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