Results for 'bacterial learning '

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  1. The biosemiotic implications of 'bacterial wisdom'.Felipe-Andres Piedra & Donald R. Frohlich - manuscript
    Eshel Ben-Jacob’s manuscript entitled ‘Bacterial wisdom, Gödel’s theorem and creative genomic webs’ summarizes decades of work demonstrating adaptive mutagenesis in bacterial genomes. Bacterial genomes, each an essential part of a Kantian whole that is a single bacterium, are thus not independent of the environment as sensed; and a single bacterium is therefore a semiotic entity. Ben-Jacob suggests this but errs in 1) assigning autonomy to the genome, and 2) analogizing through computation without making clear whether he is (...)
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  2. Bacterial species pluralism in the light of medicine and endosymbiosis.Javier Suárez - 2016 - Theoria: Revista de Teoría, Historia y Fundamentos de la Ciencia 31 (1):91-105.
    This paper aims to offer a new argument in defence bacterial species pluralism. To do so, I shall first present the particular issues derived from the conflict between the non-theoretical understanding of species as units of classification and the theoretical comprehension of them as units of evolution. Secondly, I shall justify the necessity of the concept of species for the bacterial world, and show how medicine and endosymbiotic evolutionary theory make use of different concepts of bacterial species (...)
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  3. Bacterial Biofilm and its Clinical Implications.Prof Shakibaie - 2018 - Ann Microbiol Res 2 (1):45-50.
    Microbial biofilm created huge burden in treatment of both community and hospital infections. A biofilm is complex communities of bacteria attached to a surface or interface enclosed in an exopolysaccharide matrix and protected from unfavorable conditions such as presence of antibiotics, host defense or oxidative stresses. Biofilms are often considered hot spot for horizontal gene transfer among same or different bacterial species. Furthermore, bacteria with increased hydrophobicity facilitate biofilm formation by reducing repulsion between the extracellular matrix and the bacterium. (...)
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  4. The significances of bacterial colony patterns.James A. Shapiro - 1995 - Bioessays 17 (7):597-607.
    Bacteria do many things as organized populations. We have recently learned much about the molecular basis of intercellular communication among prokaryotes. Colonies display bacterial capacities for multicellular coordination which can be useful in nature where bacteria predominantly grow as films, chains, mats and colonies. E. coli colonies are organized into differentiated non-clonal populations and undergo complex morphogenesis. Multicellularity regulates many aspects of bacterial physiology, including DNA rearrangement systems. In some bacterial species, colony development involves swarming (active migration (...)
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  5. Perceptual Learning and the Contents of Perception.Kevin Connolly - 2014 - Erkenntnis 79 (6):1407-1418.
    Suppose you have recently gained a disposition for recognizing a high-level kind property, like the property of being a wren. Wrens might look different to you now. According to the Phenomenal Contrast Argument, such cases of perceptual learning show that the contents of perception can include high-level kind properties such as the property of being a wren. I detail an alternative explanation for the different look of the wren: a shift in one’s attentional pattern onto other low-level properties. Philosophers (...)
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  6. Comparison of the Bacterial Microbiota in a Bale of Collected Cardboard Determined by 454 Pyrosequencing and Clone Library.Valérie Lalande - 2014 - Advances in Microbiology 4:754-760.
    Biofouling, the accumulation of microorganisms, is a major problem in paper mills processing paper and cardboard. This leads to the production of lower quality recycled products. Several studies have focused on the microbial content in the paper mill and the final products. Our aim was to determine the microbial biota in a bale of collected cardboard prior to entering the paper mill. Total genomic DNA was isolated and analyzed using two different methods for comparison purposes: 454 pyrosequencing and clone library. (...)
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  7. Deep learning and synthetic media.Raphaël Millière - 2022 - Synthese 200 (3):1-27.
    Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of (...)
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  8. Perceptual Learning Explains Two Candidates for Cognitive Penetration.Valtteri Arstila - 2016 - Erkenntnis 81 (6):1151-1172.
    The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we possess change the (...)
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  9. Learning Organizations and Their Role in Achieving Organizational Excellence in the Palestinian Universities.Mazen J. Al Shobaki, Samy S. Abu Naser, Youssef M. Abu Amuna & Amal A. Al Hila - 2017 - International Journal of Digital Publication Technology 1 (2):40-85.
    The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery (...)
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  10.  49
    Effect of antimicrobial susceptibility testing on treating Libyan outpatients with a suspected bacterial infection.Abdallah A. Mahjoub - 2024 - Mediterranean Journal of Pharmacy and Pharmaceutical Sciences 4 (3):41-50.
    Clinical microbiology serves as a partner to clinicians in the diagnosis and treatment of infectious diseases. Antibiotics are prescribed empirically before the availability of antimicrobial susceptibility testing data, especially when the patient's medical status could deteriorate by suspending the treatment. To investigate the impact of antimicrobial susceptibility testing on the management of outpatients with suspected bacterial infection in Libyan patients, a cross-sectional prospective study concluded on microbial microdroplet culture by including outpatients with suspected bacterial infection, who have done (...)
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  11. Perceptual learning.Zoe Jenkin - 2023 - Philosophy Compass 18 (6):e12932.
    Perception provides us with access to the external world, but that access is shaped by our own experiential histories. Through perceptual learning, we can enhance our capacities for perceptual discrimination, categorization, and attention to salient properties. We can also encode harmful biases and stereotypes. This article reviews interdisciplinary research on perceptual learning, with an emphasis on the implications for our rational and normative theorizing. Perceptual learning raises the possibility that our inquiries into topics such as epistemic justification, (...)
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  12. Perceptual learning and reasons‐responsiveness.Zoe Jenkin - 2022 - Noûs 57 (2):481-508.
    Perceptual experiences are not immediately responsive to reasons. You see a stick submerged in a glass of water as bent no matter how much you know about light refraction. Due to this isolation from reasons, perception is traditionally considered outside the scope of epistemic evaluability as justified or unjustified. Is perception really as independent from reasons as visual illusions make it out to be? I argue no, drawing on psychological evidence from perceptual learning. The flexibility of perceptual learning (...)
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  13. Distributed learning: Educating and assessing extended cognitive systems.Richard Heersmink & Simon Knight - 2018 - Philosophical Psychology 31 (6):969-990.
    Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip on (...)
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  14. Bayesian Learning Models of Pain: A Call to Action.Abby Tabor & Christopher Burr - 2019 - Current Opinion in Behavioral Sciences 26:54-61.
    Learning is fundamentally about action, enabling the successful navigation of a changing and uncertain environment. The experience of pain is central to this process, indicating the need for a change in action so as to mitigate potential threat to bodily integrity. This review considers the application of Bayesian models of learning in pain that inherently accommodate uncertainty and action, which, we shall propose are essential in understanding learning in both acute and persistent cases of pain.
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  15. Learning to love the reviewer.Quan-Hoang Vuong - 2017 - European Science Editing 43 (4):83-83.
    Learning to love the reviewer -/- Issue: 43(4) November 2017. Viewpoint Page 83 -/- Quan Hoang Vuong Western University Hanoi, Centre for Interdisciplinary Social Research, Hanoi, Vietnam.
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  16.  54
    Autonomous Learning in Religious Education in Slovakia.Jana Kucharová - 2024 - Theology and Philosophy of Education 3 (1):5-11.
    The article deals with the issue of autonomous learning in the context of religious education. It offers a definition of autonomous learning and its characteristics. Autonomous learning is subsequently included in the context of religious education. The implementation of autonomous learning in the teaching of religious education is carried out based on the competency model of religious education, which is part of the prepared curriculum for this subject in Slovakia. The paper justifies using autonomous learning (...)
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  17. (1 other version)Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems.Owen C. King - 2019 - In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence. Springer Verlag. pp. 265-282.
    Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which (...)
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  18. Learning Motivation and Utilization of Virtual Media in Learning Mathematics.Almighty Tabuena & Jupeth Pentang - 2021 - Asia-Africa Journal of Recent Scientific Research 1 (1):65-75.
    This study aims to describe the learning motivation of students using virtual media when they are learning mathematics in grade 5. The research design applied in this research is classroom action research. The research is conducted in two phases which involve planning, action and observation and reflection. The results of the study revealed that intrinsic motivation to learn is most prevalent in the form of fun to learn mathematics with virtual media. Other forms of intrinsic motivation include curiosity, (...)
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  19. Learning Incommensurate Concepts.Hayley Clatterbuck & Hunter Gentry - forthcoming - Synthese.
    A central task of developmental psychology and philosophy of science is to show how humans learn radically new concepts. Famously, Fodor has argued that such learning is impossible if concepts have definitional structure and all learning is hypothesis testing. We present several learning processes that can generate novel concepts. They yield transformations of the fundamental feature space, generating new similarity structures which can underlie conceptual change. This framework provides a tractable, empiricist-friendly account that unifies and shores up (...)
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  20. Learning to Discriminate: The Perfect Proxy Problem in Artificially Intelligent Criminal Sentencing.Benjamin Davies & Thomas Douglas - 2022 - In Jesper Ryberg & Julian V. Roberts (eds.), Sentencing and Artificial Intelligence. Oxford: OUP.
    It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that (...)
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  21. Learning Places: Building Dwelling Thinking Online.David Kolb - 2000 - Journal of Philosophy of Education 34 (1):121-133.
    Lack of information is hardly our problem. Information comes at us in waves, sloshing out of the magazine rack, lapping at our computer monitors. It repeats and repeats on all-day news shows. It comes neatly packaged as sound bites, or little nuggets ready for trivia games. We have plenty of information, but it is not often the information we need. Even if it is, we need to learn how to deal with it. It is not just the amount, but the (...)
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  22. Clinical applications of machine learning algorithms: beyond the black box.David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi - 2019 - British Medical Journal 364:I886.
    Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.
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  23. Modular Learning Efficiency: Learner’s Attitude and Performance Towards Self-Learning Modules.April Clarice C. Bacomo, Lucy P. Daculap, Mary Grace O. Ocampo, Crystalyn D. Paguia, Jupeth Pentang & Ronalyn M. Bautista - 2022 - IOER International Multidisciplinary Research Journal 4 (2):60-72.
    Learner’s attitude towards modular distance learning catches uncertainties as a world crisis occurs up to this point. As self-learning modules (SLMs) become a supplemental means of learning in new normal education, this study investigated efficiency towards the learners’ attitude and performance. Specifically, the study described the learners’ profile and their attitude and performance towards SLMs. It also ascertained the relationship between the learner’s profile with their attitude and performance, as well as the relationship between attitude and performance (...)
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  24. Learning from Conditionals.Benjamin Eva, Stephan Hartmann & Soroush Rafiee Rad - 2020 - Mind 129 (514):461-508.
    In this article, we address a major outstanding question of probabilistic Bayesian epistemology: how should a rational Bayesian agent update their beliefs upon learning an indicative conditional? A number of authors have recently contended that this question is fundamentally underdetermined by Bayesian norms, and hence that there is no single update procedure that rational agents are obliged to follow upon learning an indicative conditional. Here we resist this trend and argue that a core set of widely accepted Bayesian (...)
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  25. Learning Strategies, Motivation, and Its Relationship to the Online Learning Environment Among College Students.Ana Mhey M. Tabinas, Jemimah Abigail R. Panuncio, Dianah Marie T. Salvo, Rebecca A. Oliquino, Shaena Bernadette D. Villar & Jhoselle Tus - 2023 - Psychology and Education: A Multidisciplinary Journal 11 (2):622-628.
    Online education has become an essential component of education. Thus, several factors, such as the student’s learning strategy and motivation, generally contribute to their academic success. This study investigates the relationship between learning strategies, motivation, and online learning environment among 150 first-year college students. Employing correlational design, the statistical findings of the study reveal that the r coefficient of 0.59 indicates a moderate positive correlation between the variables. The p-value of 0.00, which is less than 0.05, leads (...)
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  26. Learning and Selection Processes.Marc Artiga - 2010 - Theoria 25 (2):197-209.
    In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections.
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  27. Machine Learning-Based Diabetes Prediction: Feature Analysis and Model Assessment.Fares Wael Al-Gharabawi & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):10-17.
    This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to (...)
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  28. Learning Networks and Connective Knowledge.Stephen Downes - 2010 - In Harrison Hao Yang & Steve Chi-Yin Yuen (eds.), Collective Intelligence and E-Learning 2.0: Implications of Web-Based Communities and Networking. IGI Global.
    The purpose of this chapter is to outline some of the thinking behind new e-learning technology, including e-portfolios and personal learning environments. Part of this thinking is centered around the theory of connectivism, which asserts that knowledge - and therefore the learning of knowledge - is distributive, that is, not located in any given place (and therefore not 'transferred' or 'transacted' per se) but rather consists of the network of connections formed from experience and interactions with a (...)
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  29. Learning Concepts: A Learning-Theoretic Solution to the Complex-First Paradox.Nina Laura Poth & Peter Brössel - 2020 - Philosophy of Science 87 (1):135-151.
    Children acquire complex concepts like DOG earlier than simple concepts like BROWN, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Werning 2010). This is the Complex- First Paradox. We present a novel solution to the Complex-First Paradox. Our solution builds on a generalization of Xu and Tenenbaum’s (2007) Bayesian model of word learning. By focusing on a rational theory of concept learning, (...)
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  30. Understanding from Machine Learning Models.Emily Sullivan - 2022 - British Journal for the Philosophy of Science 73 (1):109-133.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding (...)
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  31. Learning in Lithic Landscapes: A Reconsideration of the Hominid “Toolmaking” Niche.Peter Hiscock - 2014 - Biological Theory 9 (1):27-41.
    This article reconsiders the early hominid ‘‘lithic niche’’ by examining the social implications of stone artifact making. I reject the idea that making tools for use is an adequate explanation of the elaborate artifact forms of the Lower Palaeolithic, or a sufficient cause for long-term trends in hominid technology. I then advance an alternative mechanism founded on the claim that competency in making stone artifacts requires extended learning, and that excellence in artifact making is attained only by highly skilled (...)
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  32. Learning from errors in digital patient communication: Professionals’ enactment of negative knowledge and digital ignorance in the workplace.Rikke Jensen, Charlotte Jonasson, Martin Gartmeier & Jaana Parviainen - 2023 - Journal of Workplace Learning 35 (5).
    Purpose. The purpose of this study is to investigate how professionals learn from varying experiences with errors in health-care digitalization and develop and use negative knowledge and digital ignorance in efforts to improve digitalized health care. Design/methodology/approach. A two-year qualitative field study was conducted in the context of a public health-care organization working with digital patient communication. The data consisted of participant observation, semistructured interviews and document data. Inductive coding and a theoretically informed generation of themes were applied. Findings. The (...)
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  33.  83
    Machine Learning-Based Cyberbullying Detection System with Enhanced Accuracy and Speed.M. Arulselvan - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):421-429.
    The rise of social media has created a new platform for communication and interaction, but it has also facilitated the spread of harmful behaviors such as cyberbullying. Detecting and mitigating cyberbullying on social media platforms is a critical challenge that requires advanced technological solutions. This paper presents a novel approach to cyberbullying detection using a combination of supervised machine learning (ML) and natural language processing (NLP) techniques, enhanced by optimization algorithms. The proposed system is designed to identify and classify (...)
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  34. (1 other version)Learning as Differentiation of Experiential Schemas.Jan Halák - 2019 - In Jim Parry & Pete Allison (eds.), Experiential Learning and Outdoor Education: Traditions of practice and philosophical perspectives. Routledge. pp. 52-70.
    The goal of this chapter is to provide an interpretation of experiential learning that fully detaches itself from the epistemological presuppositions of empiricist and intellectualist accounts of learning. I first introduce the concept of schema as understood by Kant and I explain how it is related to the problems implied by the empiricist and intellectualist frameworks. I then interpret David Kolb’s theory of learning that is based on the concept of learning cycle and represents an attempt (...)
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  35. Perceptual learning, the mere exposure effect and aesthetic antirealism.Bence Nanay - 2017 - Leonardo 50:58-63.
    It has been argued that some recent experimental findings about the mere exposure effect can be used to argue for aesthetic antirealism: the view that there is no fact of the matter about aesthetic value. The aim of this paper is to assess this argument and point out that this strategy, as it stands, does not work. But we may still be able to use experimental findings about the mere exposure effect in order to engage with the aesthetic realism/antirealism debate. (...)
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  36. Learning, evolvability and exploratory behaviour: extending the evolutionary reach of learning.Rachael L. Brown - 2013 - Biology and Philosophy 28 (6):933-955.
    Traditional accounts of the role of learning in evolution have concentrated upon its capacity as a source of fitness to individuals. In this paper I use a case study from invasive species biology—the role of conditioned taste aversion in mitigating the impact of cane toads on the native species of Northern Australia—to highlight a role for learning beyond this—as a source of evolvability to populations. This has two benefits. First, it highlights an otherwise under-appreciated role for learning (...)
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  37. Machine Learning, Misinformation, and Citizen Science.Adrian K. Yee - 2023 - European Journal for Philosophy of Science 13 (56):1-24.
    Current methods of operationalizing concepts of misinformation in machine learning are often problematic given idiosyncrasies in their success conditions compared to other models employed in the natural and social sciences. The intrinsic value-ladenness of misinformation and the dynamic relationship between citizens' and social scientists' concepts of misinformation jointly suggest that both the construct legitimacy and the construct validity of these models needs to be assessed via more democratic criteria than has previously been recognized.
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  38. Pupils’ Learning Styles and Academic Performance in Modular Learning.June Albert V. Cavite & Maria Victoria A. Gonzaga - 2023 - International Journal of Multidisciplinary Educational Research and Innovation 1 (3): 72-88.
    This study assesses the student learning styles and academic performance in modular learning among Grade IV, V, and VI learners of Hindang Central School. This considered the learning styles and academic performance of the respondents in modular learning. A total of 252 learners from Hindang Central School participated as respondents in the evaluative method of research that consists of two parts questionnaires. This study used a modified survey questionnaire from the University of California at Merced, Student (...)
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  39. Learning and Value Change.J. Dmitri Gallow - 2019 - Philosophers' Imprint 19:1--22.
    Accuracy-first accounts of rational learning attempt to vindicate the intuitive idea that, while rationally-formed belief need not be true, it is nevertheless likely to be true. To this end, they attempt to show that the Bayesian's rational learning norms are a consequence of the rational pursuit of accuracy. Existing accounts fall short of this goal, for they presuppose evidential norms which are not and cannot be vindicated in terms of the single-minded pursuit of accuracy. I propose an alternative (...)
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  40. Networked Learning and Three Promises of Phenomenology.Lucy Osler - forthcoming - In Phenomenology in Action for Researching Networked Learning Experiences.
    In this chapter, I consider three ‘promises’ of bringing phenomenology into dialogue with networked learning. First, a ‘conceptual promise’, which draws attention to conceptual resources in phenomenology that can inspire and inform how we understand, conceive of, and uncover experiences of participants in networked learning activities and environments. Second, a ‘methodological promise’, which outlines a variety of ways that phenomenological methodologies and concepts can be put to use in empirical research in networked learning. And third, a ‘critical (...)
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  41. Learning in the social being system.Zoe Jenkin & Lori Markson - 2024 - Behavioral and Brain Sciences 47:e132.
    We argue that the core social being system is unlike other core systems in that it participates in frequent, widespread learning. As a result, the social being system is less constant throughout the lifespan and less informationally encapsulated than other core systems. This learning supports the development of the precursors of bias, but also provides avenues for preempting it.
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  42. Amidst the Online Learning Modality: The Social Support and Its Relationship to the Anxiety of Senior High School Students.Jastine Joy Basilio, Twinkle Pangilinan, Jeremiah Joy Kalong & Jhoselle Tus - 2022 - Psychology Abd Education: A Multidisciplinary Journal 1 (1):1-6.
    Senior high school is known to be part of the newly implemented K-12 program in the Philippines' educational system. Hence, this program added two years to the academic learning program of students, which mainly focuses on different theoretical and vocational strands that aim to prepare and fully furnish the students for education and employment in the future. Due to adjustments to new online learning amidst the pandemic, students begin to experience various challenges, primarily social support and mental well-being. (...)
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  43. Deep Learning as Method-Learning: Pragmatic Understanding, Epistemic Strategies and Design-Rules.Phillip H. Kieval & Oscar Westerblad - manuscript
    We claim that scientists working with deep learning (DL) models exhibit a form of pragmatic understanding that is not reducible to or dependent on explanation. This pragmatic understanding comprises a set of learned methodological principles that underlie DL model design-choices and secure their reliability. We illustrate this action-oriented pragmatic understanding with a case study of AlphaFold2, highlighting the interplay between background knowledge of a problem and methodological choices involving techniques for constraining how a model learns from data. Building successful (...)
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  44. Learning from Failure: Shame and Emotion Regulation in Virtue as Skill.Matt Stichter - 2020 - Ethical Theory and Moral Practice 23 (2):341-354.
    On an account of virtue as skill, virtues are acquired in the ways that skills are acquired. In this paper I focus on one implication of that account that is deserving of greater attention, which is that becoming more skillful requires learning from one’s failures, but that turns out to be especially challenging when dealing with moral failures. In skill acquisition, skills are improved by deliberate practice, where you strive to correct past mistakes and learn how to overcome your (...)
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  45. Learning to Imagine.Amy Kind - 2022 - British Journal of Aesthetics 62 (1):33-48.
    Underlying much current work in philosophy of imagination is the assumption that imagination is a skill. This assumption seems to entail not only that facility with imagining will vary from one person to another, but also that people can improve their own imaginative capacities and learn to be better imaginers. This paper takes up this issue. After showing why this is properly understood as a philosophical question, I discuss what it means to say that one imagining is better than another (...)
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  46. Learning and Business Incubation Processes and Their Impact on Improving the Performance of Business Incubators.Shehada Y. Rania, El Talla A. Suliman, J. Shobaki Mazen & Samy S. Abu-Naser - 2020 - International Journal of Academic Multidisciplinary Research (IJAMR) 4 (5):120-142.
    This study aimed to identify the learning and business incubation processes and their impact on developing the performance of business incubators in Gaza Strip, and the study relied on the descriptive analytical approach, and the study population consisted of all employees working in business incubators in Gaza Strip in addition to experts and consultants in incubators where their total number reached (62) individuals, and the researchers used the questionnaire as a main tool to collect data through the comprehensive survey (...)
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  47. Unlimited Associative Learning and the Origins of Consciousness: A Primer and Some Predictions.Jonathan Birch, Simona Ginsburg & Eva Jablonka - 2020 - Biology and Philosophy 35 (6):1-23.
    Over the past two decades, Ginsburg and Jablonka have developed a novel approach to studying the evolutionary origins of consciousness: the Unlimited Associative Learning framework. The central idea is that there is a distinctive type of learning that can serve as a transition marker for the evolutionary transition from non-conscious to conscious life. The goal of this paper is to stimulate discussion of the framework by providing a primer on its key claims and a clear statement of its (...)
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  48. The Learning-Consciousness Connection.Jonathan Birch, Simona Ginsburg & Eva Jablonka - 2021 - Biology and Philosophy 36 (5):1-14.
    This is a response to the nine commentaries on our target article “Unlimited Associative Learning: A primer and some predictions”. Our responses are organized by theme rather than by author. We present a minimal functional architecture for Unlimited Associative Learning that aims to tie to together the list of capacities presented in the target article. We explain why we discount higher-order thought theories of consciousness. We respond to the criticism that we have overplayed the importance of learning (...)
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  49.  59
    Effect of antimicrobial susceptibility testing on treating Libyan outpatients with a suspected bacterial infection.Abdallah A. Mahjoub - 2024 - Mediterranean Journal of Pharmacy and Pharmaceutical Sciences 4 (3):41-50.
    Clinical microbiology serves as a partner to clinicians in the diagnosis and treatment of infectious diseases. Antibiotics are prescribed empirically before the availability of antimicrobial susceptibility testing data, especially when the patient's medical status could deteriorate by suspending the treatment. To investigate the impact of antimicrobial susceptibility testing on the management of outpatients with suspected bacterial infection in Libyan patients, a cross-sectional prospective study concluded on microbial microdroplet culture by including outpatients with suspected bacterial infection, who have done (...)
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  50. Strategies to improve the reliability of a theory: the experiment of bacterial invasion into cultured epithelial cells.Hubertus Nederbragt - 2003 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 34 (4):593-614.
    An analysis is presented of published methods that have been used by experimenters to justify the reliability of the theory of invasion of microorganisms into cultured cells. The results show that, to demonstrate this invasion, many experimenters used two or more methods that were based on independent technical and theoretical principles, and by doing so improved the reliability of the theory. Subsequently I compare this strategy of 'multiple derivability' with other strategies, discussed in the literature in relation to the mesosome, (...)
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