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  1. The Cyclical Return of the IQ Controversy: Revisiting the Lessons of the Resolution on Genetics, Race and Intelligence.Davide Serpico - 2021 - Journal of the History of Biology 54 (2):199-228.
    In 1976, the Genetics Society of America published a document entitled “Resolution of Genetics, Race, and Intelligence.” This document laid out the Society’s position in the IQ controversy, particularly that on scientific and ethical questions involving the genetics of intellectual differences between human populations. Since the GSA was the largest scientific society of geneticists in the world, many expected the document to be of central importance in settling the controversy. Unfortunately, the Resolution had surprisingly little influence on the discussion. In (...)
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  2. Philosophie de l'intelligence émotionnelle.Sfetcu Nicolae - manuscript
    Une préoccupation des chercheurs est de savoir si l'intelligence émotionnelle est une théorie de la personnalité, une forme d'intelligence ou une combinaison des deux. De nombreuses études considèrent l'intelligence émotionnelle comme un facteur personnel associé à la compétence. Mais la plupart des chercheurs considèrent l'intelligence émotionnelle comme une conscience émotionnelle de soi et des autres, en plus de l'efficacité professionnelle et de la gestion émotionnelle. L'intelligence émotionnelle est considéré comme une capacité au niveau ontologique incluant la compétence personnelle et sociale, (...)
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  3. Intelligence and Creativity Share a Common Cognitive and Neural Basis.Emily Frith, Daniel B. Elbich, Alexander P. Christensen, Monica D. Rosenberg, Qunlin Chen, Michael J. Kane, Paul J. Silvia, Paul Seli & Roger E. Beaty - 2021 - Journal of Experimental Psychology: General 150 (4):609-632.
    Are intelligence and creativity distinct abilities, or do they rely on the same cognitive and neural systems? We sought to quantify the extent to which intelligence and creative cognition overlap in brain and behavior by combining machine learning of fMRI data and latent variable modeling of cognitive ability data in a sample of young adults (N = 186) who completed a battery of intelligence and creative thinking tasks. The study had 3 analytic goals: (a) to assess contributions of specific facets (...)
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  4. La connaissance tacite dans l'analyse du renseignement.Sfetcu Nicolae - manuscript
    Le point de vue de Michael Polanyi sur la science peut aider à comprendre le processus et le « produit » de l'analyse du renseignement. Les arguments de Michael Polanyi concernant les activités des scientifiques sont transférables dans le domaine de l'analyse du renseignement, offrant une perspective nuancée pour percevoir les défis épistémologiques et les problèmes auxquels sont confrontés les analystes. Les concepts de « connaissance tacite » et de « connaissance personnelle » de Polanyi contribuent au développement d'une compréhension (...)
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  5. Intelligence as Accurate Prediction.Trond A. Tjøstheim & Andreas Stephens - 2021 - Review of Philosophy and Psychology 1:1-25.
    This paper argues that intelligence can be approximated by the ability to produce accurate predictions. It is further argued that general intelligence can be approximated by context dependent predictive abilities combined with the ability to use working memory to abstract away contextual information. The flexibility associated with general intelligence can be understood as the ability to use selective attention to focus on specific aspects of sensory impressions to identify patterns, which can then be used to predict events in novel situations (...)
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  6. The First Minds: Caterpillars, ‘Karyotes and Consciousness.William B. Miller - 2021 - Philosophical Psychology 34 (2):322-325.
  7. When Can Young Children Reason About an Exclusive Disjunction? A Follow Up To.Shalini Gautam, Thomas Suddendorf & Jonathan Redshaw - 2021 - Cognition 207:104507.
    Mody and Carey (2016) investigated children's capacity to reason by the disjunctive syllogism by hiding stickers within two pairs of cups (i.e., there is one sticker in cup A or B, and one in cup C or D) and then showing one cup to be empty. They found that children as young as 3 years of age chose the most likely cup (i.e., not A, therefore choose B; and disregard C and D) and suggested that these children were representing the (...)
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  8. Galton and Spearman Revisited: Can Single General Discrimination Ability Drive Performance on Diverse Sensorimotor Tasks and Explain Intelligence?Jan Jastrzębski, Bartłomiej Kroczek & Adam Chuderski - forthcoming - Journal of Experimental Psychology: General.
    The well-known hypothesis of Sir Francis Galton (1883) posed that individual differences in performance on diverse sensorimotor tasks are rooted in single general sensory discrimination ability. Relatedly, Charles Spearman (1904) hypothesized that this discrimination ability and intelligence share the same neural basis and thus should be statistically equivalent. Despite a century of research, existing evidence for these 2 hypotheses is still inconclusive. Study 1 modeled the factor structure for, to date, the most comprehensive battery of tasks tapping into visual discrimination, (...)
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  9. ‘The Intelligent and the Rest’: British Mensa and the Contested Status of High Intelligence.Susanne Schregel & Tineke Broer - 2020 - History of the Human Sciences 33 (5):3-11.
    This special section evolved out of a workshop entitled ‘Minds and Brains in Everyday Life: Embedding and Negotiating Scientific Concepts in Popular Discourses’, held at the Institute for Advanced Studies in the Humanities at the University of Edinburgh. Our discussions at the workshop and for this special section began with the observation that scientific interpretations and everyday explanations regularly meet and come together in debates about aspects of the mind and the brain. Such entanglements between science and the wider public (...)
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  10. Superinteligentny Lewiatan: Zarys problemu autonomii człowieka a autonomizacji urządzeń.Adrian Mróz - 2020 - Kultura I Historia 37 (1):1-18.
    Celem niniejszej pracy jest zastosowanie wizji „Lewiatana” Thomasa Hobbesa do koncepcji superinteligencji lub nadludzkiej inteligencji, które dyskutowane jest wśród transhumanistów i poruszone jest przez takich filozofów i futurologów jak między innymi Nick Bostrom, Stanisław Lem, albo Ray Kurzweil. Inspiracją mojej pracy były pytania w rodzaju: „kiedy człowiek przestaje być autonomicznym podmiotem?” albo „czy człowiek w ogóle może być samodzielny?”. Niemniej jednak wydaje mi się, że takie pytania mogą się pojawić wtedy, kiedy człowieka rozpoznamy jako zwierzę polityczne (politikon zoon w sensie (...)
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  11. The Fashionable Scientific Fraud: Collingwood’s Critique of Psychometrics.Joel Michell - 2020 - History of the Human Sciences 33 (2):3-21.
    In his review of Charles Spearman’s The Nature of ‘Intelligence’, R. G. Collingwood launched an attack upon psychometrics that was expanded in his Essay on Metaphysics. Although underrated by friend and foe alike, Collingwood’s critique identified a number of defects in the thinking of psychometricians that subsequently became entrenched. However, his main complaint was that psychology generally was a ‘fashionable scientific fraud’. This charge was inspired by his more general views on logic and metaphysics, which, however, as I argue, are (...)
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  12. Street Smarts.Devin Sanchez Curry - 2021 - Synthese 199 (1-2):161-180.
    A pluralistic approach to folk psychology must countenance the evaluative, regulatory, predictive, and explanatory roles played by attributions of intelligence in social practices across cultures. Building off of the work of the psychologist Robert Sternberg and the philosophers Gilbert Ryle and Daniel Dennett, I argue that a relativistic interpretivism best accounts for the many varieties of intelligence that emerge from folk discourse. To be intelligent is to be comparatively good at solving intellectual problems that an interpreter deems worth solving.
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  13. Artificial Intelligence Versus Agape Love.Ted Peters - 2019 - Forum Philosophicum: International Journal for Philosophy 24 (2):259-278.
    As Artificial Intelligence researchers attempt to emulate human intelligence and transhumanists work toward superintelligence, philosophers and theologians confront a dilemma: we must either, on the one horn, abandon the view that the defining feature of humanity is rationality and propose an account of spirituality that dissociates it from reason; or, on the other horn, find a way to invalidate the growing faith in a posthuman future shaped by the enhancements of Intelligence Amplification or the progress of Artificial Intelligence. I grasp (...)
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  14. Belief-Desire Coherence.Stephen David Petersen - 2003 - Dissertation, University of Michigan
    Broadly construed, this dissertation addresses a question central to normative epistemology: "what makes for good thinking?" My answer is a computational, internal, pragmatic, coherence epistemology. I call it, somewhat incompletely and inaccurately, "belief-desire coherence". It is designed to draw from progress in artificial intelligence and cognitive psychology. ;Probably the standard philosophical answer to "what makes for good thinking?" is a variation on "thinking directed toward the truth." I save the bulk of my arguments against this traditional alethic approach for the (...)
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  15. Model of Intelligence.Miro Brada - manuscript
    Model of intelligence and new methods to assess IQ. MA thesis in 1998 (Comenius University). Art exhibitions "From Animation" London 2013, "Fading Memory" Weißenohe 2015, TAIF Tokyo 2017. Conferences in Santorini, Daejon 2016, Geneva 2017.
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  16. Epistemological Problems in the Philosophy of Science, II.Edward MacKinnon - 1968 - Review of Metaphysics 22 (2):329 - 358.
    This article completes the study begun in I by a detailed consideration of errol harris's, "the foundations of metaphysics in science" and by an independent interpretation of the epistemological foundations of scientific theories. This is done in terms of two components labelled 'a physical language' and 'a mathematical language'. A physical language is conceived as a transformed extension of ordinary language which preserves its basic structural principles while modifying its descriptive metaphysics. The relation between such a physical language and a (...)
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  17. Octology.Andrej Poleev - 2010
    The manuscript describes a new scientific discipline called Octology, which should unify morphogenetic linguistics and neurobiology to investigate the development of the words, cognition and behavior.
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  18. The Need for an Examination of Certain Hypotheses in Mental Tests.Beardsley Ruml - 1920 - Journal of Philosophy, Psychology and Scientific Methods 17 (3):57-61.
  19. Celebrating 300 Million Years of the Mind : A Bird's Eye View.Pater J. Snyder - 2007 - In Henri Cohen & Brigitte Stemmer (eds.), Consciousness and Cognition: Fragments of Mind and Brain. Elxevier Academic Press.
The Concept of Intelligence
  1. G as Bridge Model.Devin Sanchez Curry - 2021 - Philosophy of Science 88 (5):1067-1078.
    Psychometric g—a statistical factor capturing intercorrelations between scores on different IQ tests—is of theoretical interest despite being a low-fidelity model of both folk psychological intelligence and its cognitive/neural underpinnings. Psychometric g idealizes away from those aspects of cognitive/neural mechanisms that are not explanatory of the relevant variety of folk psychological intelligence, and it idealizes away from those varieties of folk psychological intelligence that are not generated by the relevant cognitive/neural substrate. In this manner, g constitutes a high-fidelity bridge model of (...)
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  2. Formal Theory of Thinking.Anton Venglovskiy - manuscript
    The definition of thinking in general form is given. The constructive logic of thinking is formulated. An algorithm capable of arbitrarily complex thinking is built. I am proposing a model of super-abstract self-organizing, algorithmic chaos, which, in my opinion, is the algorithmic mind at its ideal, purest form. This mind can spontaneously evolve and produce knowledge, but it has no a priori knowledge about any world. The algorithm behavior is logical and evolves through generalizations to any given complexity of behavior.
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  3. How to Count Biological Minds: Symbiosis, the Free Energy Principle, and Reciprocal Multiscale Integration.Matthew Sims - 2020 - Synthese 199 (1-2):2157-2179.
    The notion of a physiological individuals has been developed and applied in the philosophy of biology to understand symbiosis, an understanding of which is key to theorising about the major transition in evolution from multi-organismality to multi-cellularity. The paper begins by asking what such symbiotic individuals can help to reveal about a possible transition in the evolution of cognition. Such a transition marks the movement from cooperating individual biological cognizers to a functionally integrated cognizing unit. Somewhere along the way, did (...)
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General Intelligence
  1. G as Bridge Model.Devin Sanchez Curry - 2021 - Philosophy of Science 88 (5):1067-1078.
    Psychometric g—a statistical factor capturing intercorrelations between scores on different IQ tests—is of theoretical interest despite being a low-fidelity model of both folk psychological intelligence and its cognitive/neural underpinnings. Psychometric g idealizes away from those aspects of cognitive/neural mechanisms that are not explanatory of the relevant variety of folk psychological intelligence, and it idealizes away from those varieties of folk psychological intelligence that are not generated by the relevant cognitive/neural substrate. In this manner, g constitutes a high-fidelity bridge model of (...)
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  2. Formal Theory of Thinking.Anton Venglovskiy - manuscript
    The definition of thinking in general form is given. The constructive logic of thinking is formulated. An algorithm capable of arbitrarily complex thinking is built. I am proposing a model of super-abstract self-organizing, algorithmic chaos, which, in my opinion, is the algorithmic mind at its ideal, purest form. This mind can spontaneously evolve and produce knowledge, but it has no a priori knowledge about any world. The algorithm behavior is logical and evolves through generalizations to any given complexity of behavior.
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Measures of Intelligence
  1. G as Bridge Model.Devin Sanchez Curry - 2021 - Philosophy of Science 88 (5):1067-1078.
    Psychometric g—a statistical factor capturing intercorrelations between scores on different IQ tests—is of theoretical interest despite being a low-fidelity model of both folk psychological intelligence and its cognitive/neural underpinnings. Psychometric g idealizes away from those aspects of cognitive/neural mechanisms that are not explanatory of the relevant variety of folk psychological intelligence, and it idealizes away from those varieties of folk psychological intelligence that are not generated by the relevant cognitive/neural substrate. In this manner, g constitutes a high-fidelity bridge model of (...)
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  2. Numbering the Mind: Questionnaires and the Attitudinal Public.Jacy L. Young - 2017 - History of the Human Sciences 30 (4):32-53.
    During the interwar years psychologists Louis Leon Thurstone and Rensis Likert produced newly standardized forms of questionnaires. Both built on developments in mental testing, including the use of restricted sets of answers and the emergence of statistical techniques, to create questionnaires that employed numerical scaling. This transformation in shape of questionnaires was intimately tied up with both psychologists’ nominal subject of investigation: attitudes. Efforts to render psychology a socially valuable and influential science spurred psychologists to create sophisticated and increasingly precise (...)
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  3. The Mental Test as a Boundary Object in Early-20th-Century Russian Child Science.Andy Byford - 2014 - History of the Human Sciences 27 (4):22-58.
    This article charts the history of mental testing in the context of the rise and fall of Russian child science between the 1890s and the 1930s. Tracing the genealogy of testing in scientific experimentation, scholastic assessment, medical diagnostics and bureaucratic accounting, it follows the displacements of this technology along and across the boundaries of the child science movement. The article focuses on three domains of expertise – psychology, pedagogy and psychiatry, examining the key guises that mental testing assumed in them (...)
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  4. The Definition of a Profession: The Authority of Metaphor in the History of Intelligence Testing, 1890-1930 by JoAnne Brown. [REVIEW]John Carson - 1994 - Isis 85:722-723.
  5. Measuring the Mind: Education and Psychology in England, C. 1860-C. 1990 by Adrian Wooldridge. [REVIEW]John Carson - 1996 - Isis 87:191-192.
  6. IQ And Mental Testing: An Unnatural Science And Its Social History By Brian Evans; Bernard Waites. [REVIEW]Daniel N. Robinson - 1982 - Isis 73 (3):480-481.
  7. Measuring Minds: Henry Herbert Goddard and the Origins of American Intelligence Testing by Leila Zenderland. [REVIEW]Katherine Pandora - 1999 - Isis 90:395-396.
  8. Schools as Sorters: Lewis M. Terman, Applied Psychology, and the Intelligence Testing Movement, 1890-1930 by Paul Davis Chapman; Lewis M. Terman: Pioneer in Psychological Testing by Henry L. Minton. [REVIEW]Leila Zenderland - 1991 - Isis 82:415-416.
Intelligence, Misc
  1. Science is Not Always “Self-Correcting” : Fact–Value Conflation and the Study of Intelligence.Nathan Cofnas - 2016 - Foundations of Science 21 (3):477-492.
    Some prominent scientists and philosophers have stated openly that moral and political considerations should influence whether we accept or promulgate scientific theories. This widespread view has significantly influenced the development, and public perception, of intelligence research. Theories related to group differences in intelligence are often rejected a priori on explicitly moral grounds. Thus the idea, frequently expressed by commentators on science, that science is “self-correcting”—that hypotheses are simply abandoned when they are undermined by empirical evidence—may not be correct in all (...)
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  2. Brilliant Green: The Surprising History and Science of Plant Intelligence by Stefano Mancuso and Alessandra Viola. [REVIEW]Franklin G. Miller - 2014 - Perspectives in Biology and Medicine 57 (4):569-574.