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  1. Intelligent Behaviour.Dimitri Coelho Mollo - 2022 - Erkenntnis 89 (2):705-721.
    The notion of intelligence is relevant to several fields of research, including cognitive and comparative psychology, neuroscience, artificial intelligence, and philosophy, among others. However, there is little agreement within and across these fields on how to characterise and explain intelligence. I put forward a behavioural, operational characterisation of intelligence that can play an integrative role in the sciences of intelligence, as well as preserve the distinctive explanatory value of the notion, setting it apart from the related concepts of cognition and (...)
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  2. L’intelligenza tra generalità, integrazione e controllo cognitivo.Davide Serpico - 2022 - Rivista Internazionale di Filosofia e Psicologia 13 (1):66-71.
    ITA: In che modo il nostro cervello è in grado di produrre quel tipo di comportamento flessibile e volto a specifici scopi che chiamiamo intelligenza? Le differenze cognitive tra individui sono dovute a una varietà di abilità mentali o a una sola? Questo articolo discute gli elementi centrali della teoria dell’intelligenza generale proposta da John Duncan nel volume How intelligence happens, tradotto recentemente in italiano e corredato da un capitolo conclusivo inedito. Prendendo le mosse dalla ricerca di Charles Spearman sull’intelligenza (...)
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  3. L'intelligenza tra natura e cultura.Davide Serpico - 2022 - Turin: Rosenberg & Sellier.
    ENG: We all have our own ideas about what it is like to be intelligent. Indeed, even the experts disagree on this topic. This has generated diverse theories on the nature of intelligence and its genetic and environmental bases. Many scientific and philosophical questions thus remain unaddressed: is it possible to characterize intelligence in scientific terms? What do IQ tests measure? How is intelligence influenced by genetics, epigenetics, and the environment? What are the ethical and social implications of the research (...)
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  4. Intelligence as Accurate Prediction.Trond A. Tjøstheim & Andreas Stephens - 2022 - Review of Philosophy and Psychology 1 (2):475-499.
    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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  5. 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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  6. 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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  7. Introduction: Contested narratives of the mind and the brain: Neuro/psychological knowledge in popular debates and everyday life.Susanne Schregel - 2020 - History of the Human Sciences 33 (5):12–36.
    This article explores the history of British Mensa to examine the contested status of high intelligence in Great Britain between the late 1940s and the late 1980s. Based on journals and leaflets from the association and newspaper articles about it, the article shows how protagonists from the high IQ society campaigned for intelligence and its testing among the British public. Yet scathing reactions to the group in newspapers suggest that journalists considered it socially provocative to stress one’s own brainpower as (...)
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  8. Where the standard approach in comparative neuroscience fails and where it works: General intelligence and brain asymmetries.Davide Serpico & Elisa Frasnelli - 2018 - Comparative Cognition and Behavior Reviews 13:95-98.
    Although brain size and the concept of intelligence have been extensively used in comparative neuroscience to study cognition and its evolution, such coarse-grained traits may not be informative enough about important aspects of neurocognitive systems. By taking into account the different evolutionary trajectories and the selection pressures on neurophysiology across species, Logan and colleagues suggest that the cognitive abilities of an organism should be investigated by considering the fine-grained and species-specific phenotypic traits that characterize it. In such a way, we (...)
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  9. Can the g Factor Play a Role in Artificial General Intelligence Research?Davide Serpico & Marcello Frixione - 2018 - In Davide Serpico & Marcello Frixione (eds.), Proceedings of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2018. pp. 301-305.
    In recent years, a trend in AI research has started to pursue human-level, general artificial intelli-gence (AGI). Although the AGI framework is characterised by different viewpoints on what intelligence is and how to implement it in artificial systems, it conceptualises intelligence as flexible, general-purposed, and capable of self-adapting to different contexts and tasks. Two important ques-tions remain open: a) should AGI projects simu-late the biological, neural, and cognitive mecha-nisms realising the human intelligent behaviour? and b) what is the relationship, if (...)
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  10. Intelligence, race, and psychological testing.Mark Alfano, Latasha Holden & Andrew Conway - 2017 - In Naomi Zack (ed.), The Oxford Handbook of Philosophy and Race. New York, USA: Oxford University Press USA.
    This chapter has two main goals: to update philosophers on the state of the art in the scientific psychology of intelligence, and to explain and evaluate challenges to the measurement invariance of intelligence tests. First, we provide a brief history of the scientific psychology of intelligence. Next, we discuss the metaphysics of intelligence in light of scientific studies in psychology and neuroimaging. Finally, we turn to recent skeptical developments related to measurement invariance. These have largely focused on attributability: Where do (...)
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  11. G but not g: In search of the evolutionary continuity of intelligence.Moran Bar-Hen-Schweiger, Avraham Schweiger & Avishai Henik - 2017 - Behavioral and Brain Sciences 40:e199.
    Conceptualizing intelligence in its biological context, as the expression of manifold adaptations, compels a rethinking of measuring this characteristic in humans, relying also on animal studies of analogous skills. Mental manipulation, as an extension of object manipulation, provides a continuous, biologically based concept for studying G as it pertains to individual differences in humans and other species.
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  12. What kind of kind is intelligence?Serpico Davide - 2017 - Philosophical Psychology 31 (2):232-252.
    The model of human intelligence that is most widely adopted derives from psychometrics and behavioral genetics. This standard approach conceives intelligence as a general cognitive ability that is genetically highly heritable and describable using quantitative traits analysis. The paper analyzes intelligence within the debate on natural kinds and contends that the general intelligence conceptualization does not carve psychological nature at its joints. Moreover, I argue that this model assumes an essentialist perspective. As an alternative, I consider an HPC theory of (...)
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  13. Increasing the Sum Total of General Intelligence, As Measured by Individual IQ Scores.Matti Häyry - 2016 - Cambridge Quarterly of Healthcare Ethics 25 (3):505-514.
  14. The Centered Mind: What the Science of Working Memory Shows Us About the Nature of Human Thought.Peter Carruthers - 2015 - Oxford, GB: Oxford University Press UK.
    The Centered Mind offers a new view of the nature and causal determinants of both reflective thinking and, more generally, the stream of consciousness. Peter Carruthers argues that conscious thought is always sensory-based, relying on the resources of the working-memory system. This system enables sensory images to be sustained and manipulated through attentional signals directed at midlevel sensory areas of the brain. When abstract conceptual representations are bound into these images, we consciously experience ourselves as making judgments or arriving at (...)
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  15. General Intelligence ( g_): _Overview of a Complex Construct and Its Implications for Genetics Research.Jonathan A. Plucker & Amy L. Shelton - 2015 - Hastings Center Report 45 (S1):21-24.
    Current technology has dramatically increased the prevalence of studies to establish the genetic correlates of a wide variety of human characteristics, including not only the physical attributes that determine what we look like and the risk of physiological disease but also the psychological and cognitive characteristics that often define who we are as individuals. Perhaps one of the most deeply personal and often controversial characteristics is the concept of general intelligence, known in the psychological literature as “g.” As with the (...)
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  16. Dual processes, probabilities, and cognitive architecture.Mike Oaksford & Nick Chater - 2012 - Mind and Society 11 (1):15-26.
    It has been argued that dual process theories are not consistent with Oaksford and Chater’s probabilistic approach to human reasoning (Oaksford and Chater in Psychol Rev 101:608–631, 1994 , 2007 ; Oaksford et al. 2000 ), which has been characterised as a “single-level probabilistic treatment[s]” (Evans 2007 ). In this paper, it is argued that this characterisation conflates levels of computational explanation. The probabilistic approach is a computational level theory which is consistent with theories of general cognitive architecture that invoke (...)
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  17. Iq and Human Intelligence.Nicholas Mackintosh - 2011 - Oxford University Press UK.
    The question 'What is intelligence?' may seem simple to answer, but the study and measurement of human intelligence is one of the most controversial subjects in psychology. For much of its history, the focus has been on differences between people, on what it means for one person to be more intelligent than another, and how such differences might have arisen, obscuring efforts to understand the general nature of intelligence. These are obviously fundamental questions, still widely debated and misunderstood. New definitions (...)
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  18. Intelligence? What intelligence?Roberto Colom - 2007 - Behavioral and Brain Sciences 30 (2):155-156.
    Neuroimaging evidence, both within and between research strategies, is largely heterogeneous. This results from the way the construct of interest (i.e., intelligence) is measured. Every single available measure comprises several cognitive abilities, although the so-called g factor is always present. Here I suggest that studies must always control for this empirical fact to arrive at solid conclusions.
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  19. The parieto-frontal integration theory (P-FIT) of intelligence: Converging neuroimaging evidence.Rex E. Jung & Richard J. Haier - 2007 - Behavioral and Brain Sciences 30 (2):135-154.
    Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict (...)
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  20. Fluid intelligence as cognitive decoupling.Keith E. Stanovich - 2006 - Behavioral and Brain Sciences 29 (2):139-140.
    The dissociation of fluid cognitive functions from g is implicit in the Cattell-Horn-Carroll gF-gC theory. Nevertheless, Blair is right that fluid functions are extremely important. I suggest that the key mental operation assessed by measures of gF is the ability to sustain mental simulation while keeping the relevant representations decoupled from the actual world – an ability that underlies all hypothetical thinking. (Published Online April 5 2006).
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  21. Vocabulary and general intelligence.Arthur R. Jensen - 2001 - Behavioral and Brain Sciences 24 (6):1109-1110.
    Acquisition of word meanings, or vocabulary, reflects general mental ability (psychometric g) more than than do most abilities measured in test batteries. Among diverse subtests, vocabulary is especially high on indices of genetic influences. Bloom's exposition of the psychological complexities of understanding words, involving the primacy of concepts, the theory of mind, and other processes, explains vocabulary's predominant g saturation.
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  22. Beyond the Turing test.Jose Hernandez-Orallo - 2000 - Journal of Logic, Language and Information 9 (4):447-466.
    The main factor of intelligence is defined as the ability tocomprehend, formalising this ability with the help of new constructsbased on descriptional complexity. The result is a comprehension test,or C- test, which is exclusively defined in computational terms. Due toits absolute and non-anthropomorphic character, it is equally applicableto both humans and non-humans. Moreover, it correlates with classicalpsychometric tests, thus establishing the first firm connection betweeninformation theoretical notions and traditional IQ tests. The TuringTest is compared with the C- test and the (...)
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  23. General intelligence is central to many forms of talent.Lloyd G. Humphreys - 1998 - Behavioral and Brain Sciences 21 (3):418-418.
    Howe et al.'s rejection of traditional discussion of talent is clearly acceptable, but their alternative has a weakness. They stress practice and hard work while referring vaguely to some basic biological substrate. High scores on a valid test of general intelligence provide a cultural-genetic basis for talented performance in a wide variety of specialties, ranging from engineering to the humanities. These choices may be entirely environmentally determined, and the highest levels of achievement do require practice and hard work.
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  24. Gilbert Ryle and the Philosophy of Education.Timothy John Counihan - 1991 - Dissertation, Columbia University Teachers College
    The idiom of description for instances of intelligent action that Gilbert Ryle proposes in The Concept of Mind--the grammar of pedagogy--is the same as that employed in descriptions and judgments of education. Thus, that part of philosophy of education that addresses cognition and its description is an exercise in philosophy of mind and an extension of Ryle's project of mapping the logical geography of mental life. ;Ryle's philosophy of mind is based on his work in the theory of meaning. He (...)
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  25. Beyond IQ: A Triarchic Theory of Human Intelligence.Robert J. Sternberg - 1986 - British Journal of Educational Studies 34 (2):205-207.
  26. Neural adaptability: A biological determinant of g factor intelligence.Edward W. P. Schafer - 1985 - Behavioral and Brain Sciences 8 (2):240-241.
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  27. IQ, Heritability and Inequality, Part 2.N. J. Block & Gerald Dworkin - 1974 - Philosophy and Public Affairs 4 (1):40-99.
  28. IQ, Heritability and Inequality, Part 1.N. J. Block & Gerald Dworkin - 1974 - Philosophy and Public Affairs 3 (4):331-409.
  29. Progress and degeneration in the 'IQ debate' (II).Peter Urbach - 1974 - British Journal for the Philosophy of Science 25 (3):235-259.
  30. Progress and degeneration in the 'IQ debate' (I).Peter Urbach - 1974 - British Journal for the Philosophy of Science 25 (2):99-135.
  31. Do linguistic group tests of intelligence, non-linguistic group tests of intelligence and scholastic tests measure the same thing?J. G. Cannon - 1927 - Australasian Journal of Philosophy 5 (3):216 – 226.
  32. The Abilities of Man: Their Nature and Measurement.Charles Spearman - 1927 - Mind 37 (146):215-221.
  33. On the Measure of Intelligence.François Chollet - manuscript
    To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans. Over the past hundred years, there has been an abundance of attempts to define and measure intelligence, across both the fields of psychology and AI. We summarize and critically assess these definitions and evaluation approaches, (...)
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  34. A general intelligence factor in dogs.Rosalind Arden & Mark James Adams - unknown
    Hundreds of studies have shown that, in people, cognitive abilities overlap yielding an underlying ‘g’ factor, which explains much of the variance. We assessed individual differences in cognitive abilities in 68 border collies to determine the structure of intelligence in dogs. We administered four configurations of a detour test and repeated trials of two choice tasks. We used confirmatory factor analysis to test alternative models explaining test performance. The best-fitting model was a hierarchical model with three lower-order factors for the (...)
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