On natural and technical knowledge domains

A distinction is introduced between technical and natural knowledge domains. Four criteria by which they can be distinguished are presented, and examples given. The distinction is applied to the study of problem solving. The conclusion is that certain problem solving methods cannot be expected to occur in natural knowledge domains.     

Shareability: The social psychology of epistemology

Psychologists and cognitive scientists interested in the nature of internal representations of human knowledge often use observable regularities or structures to infer what the innate constraints on those representations must be like. It is possible, however, that certain structures might come about only when a group of people share a knowledge domain. Furthermore, it is possible that there are analyzable constraints on knowledge structures that emerge when knowledge is being shared. Such constraints are referred to in this paper as “shareability” constraints. A number of examples of observable structures in human knowledge are discussed in terms of shareability constraints. An attempt is made to determine which sorts of structures are most shareable, and how those structures may differ from the sorts of structures that are easily represented by the individual mind but not easily shared between minds.     

Alberta's suicide prevention training programs: a retrospective comparison with Rothman's developmental research model

Developmental research is used to transform existing knowledge into applied programs. A social research and development (R&D) method, developed by Rothman for the human service professions, is compared with the method used to develop the Suicide Prevention Training Programs in Alberta, Canada. A retrospective review compares the development of these programs, which have since been implemented both nationally and internationally, with Rothman's model; discusses social R&D as a transformation methodology; and draws conclusions about the probable success of using developmental research methods in the human services. The review finds that the Alberta method closely paralleled the phases of Rothman's model. Results show that the transformation of knowledge about suicide into widely disseminated suicide prevention training programs can be attributed to the application of social R&D principles. The study concludes that the use of developmental research methods to establish human service programs should increase the probability of their success.     

Empirical indistinguishability: From the knowledge structure to the skills

Recent literature has pointed out that the basic local independence model (BLIM) when applied to some specific instances of knowledge structures presents identifiability issues. Furthermore, it has been shown that for such instances the model presents a stronger form of unidentifiability named empirical indistinguishability, which leads to the fact that the existence of certain knowledge states in such structures cannot be empirically tested. In this article the notion of indistinguishability is extended to skill maps and, more generally, to the competence-based knowledge space theory. Theoretical results are provided showing that skill maps can be empirically indistinguishable from one another. The most relevant consequence of this is that for some skills there is no empirical evidence to establish their existence. This result is strictly related to the type of probabilistic model investigated, which is essentially the BLIM. Alternative models may exist or can be developed in knowledge space theory for which this indistinguishability problem disappears.     

Direct Schmid–Leiman Transformations and Rank-Deficient Loadings Matrices

The Schmid–Leiman (S–L; Psychometrika 22: 53–61, 1957) transformation is a popular method for conducting exploratory bifactor analysis that has been used in hundreds of studies of individual differences variables. To perform a two-level S–L transformation, it is generally believed that two separate factor analyses are required: a first-level analysis in which k obliquely rotated factors are extracted from an observed-variable correlation matrix, and a second-level analysis in which a general factor is extracted from the correlations of the first-level factors. In this article, I demonstrate that the S–L loadings matrix is necessarily rank deficient. I then show how this feature of the S–L transformation can be used to obtain a direct S–L solution from an unrotated first-level factor structure. Next, I reanalyze two examples from Mansolf and Reise (Multivar Behav Res 51: 698–717, 2016) to illustrate the utility of ‘best-fitting’ S–L rotations when gauging the ability of hierarchical factor models to recover known bifactor structures. Finally, I show how to compute direct bifactor solutions for non-hierarchical bifactor structures. An online supplement includes R code to reproduce all of the analyses that are reported in the article.     

MAKING BETTER USE OE SCIENTIFIC KNOWLEDGE: Separating Truth from Justice

One major reason that scientific information is not often effectively applied in the formation of social policy is that available methods for coping with the uncertainty in scientific judgments are overlooked. Application of such methods is as necessary as reducing uncertainty through the acquisition of more knowledge for these methods result in the more effective use of knowledge already at hand. Furthermore, failure to cope with uncertainty through explicit, analytical methods results in failure to separate fact (truth) from value (Justice), which in turn results in wasted knowledge and unnecessary dispute. We present four concrete examples of how such circumstances can be avoided.     

The Holographic Principle of Mind and the Evolution of Consciousness

The Holographic Principle holds that the information in any region of space and time exists on the surface of that region. Layers of the holographic, universal “now” go from the inception of the universe to the present. Universal Consciousness is the timeless source of actuality and mentality. Information is experience, and the expansion of the “now” leads to higher and higher orders of experience in the Universe, with various levels of consciousness emerging from experience. The brain consists of a nested hierarchy of surfaces that range from the most elementary field through the neuron, neural group, and the whole brain. Evidence from the evolution and structure of the brain shows that optimal surface areas in a variety of structures are conserved with respect to underlying surfaces. Microgenesis, the becoming of the mental state through a process of recapitulation of development and evolution, is in full accord with the Holographic Principle. Evidence from a wide variety of contexts indicates the capacity on the mind for total recall of past life events and for access to universal information, indicating connection with the holographic surfaces of prior “nows” and with the Universal holographic boundary. In summation, the Holographic Principle can help us explain the unity and mechanisms of perception, experience, memory, and consciousness.     

Nonmonotonic abductive inductive learning

Inductive Logic Programming (ILP) is concerned with the task of generalising sets of positive and negative examples with respect to background knowledge expressed as logic programs. Negation as Failure (NAF) is a key feature of logic programming which provides a means for nonmonotonic commonsense reasoning under incomplete information. But, so far, most ILP research has been aimed at Horn programs which exclude NAF, and has failed to exploit the full potential of normal programs that allow NAF. By contrast, Abductive Logic Programming (ALP), a related task concerned with explaining observations with respect to a prior theory, has been well studied and applied in the context of normal logic programs. This paper shows how ALP can be used to provide a semantics and proof procedure for nonmonotonic ILP that utilises practical methods of language and search bias to reduce the search space. This is done by lifting an existing method called Hybrid Abductive Inductive Learning (HAIL) from Horn clauses to normal logic programs. To demonstrate its potential benefits, the resulting system, called XHAIL, is applied to a process modelling case study involving a nonmonotonic temporal Event Calculus (EC).     

Generalization from natural language text

Generalization and memory are part of natural language understanding. This paper describes a model of generalization that is part of a system for language understanding. the Integrated Partial Parser (IPP). The generalization process includes the retrieval of relevant examples from long-term memory so that the concepts to be created can be determined when new stories are read. Generalizations are analyzed as to their critical parts and evaluated in light of later evidence. The knowledge structures used and a number of examples of the system in operation are presented.     

Categorizing numeric information for generalization

Learning programs that generalize from real-world examples will have to deal with many different kinds of data. Continuous numeric data can cause problems for algorithms that search for examples with identical property values. These problems can be surmounted by categorizing the numeric data. However, this process has problems of its own. In this paper, we look at the need for categorizing numeric data and several methods for doing so. We concentrate on the use of generalization-based memory, a memory organization where actual examples are stored along with generalizations, which leads to a generalization-based categorization algorithm. We also consider how to use a number heuristic, looking for gaps. These methods have been implemented in the UNIMEM computer system. Examples are presented of these algorithms categorizing data about the states of the United States.     

企业管理者的任职素质研究

采用问卷法对1122名企业管理者的任职素质结构及其与绩效之间的关系进行了探索性和验证性研究。结果表明:(1)研究构建的企业管理者的任职素质结构具有合理性和稳定性(2)任职素质对企业管理者的绩效有不同预测力。变革能力、沟通能力、学习能力对高层管理者的绩效有显著预测力;领导能力、知识应用水平、成就动机、社交能力对中层管理者的绩效有显著预测力;变革能力对基层管理者的绩效有显著预测力。     

Neural blackboard architectures of combinatorial structures in cognition

Human cognition is unique in the way in which it relies on combinatorial (or compositional) structures. Language provides ample evidence for the existence of combinatorial structures, but they can also be found in visual cognition. To understand the neural basis of human cognition, it is therefore essential to understand how combinatorial structures can be instantiated in neural terms. In his recent book on the foundations of language, Jackendoff described four fundamental problems for a neural instantiation of combinatorial structures: the massiveness of the binding problem, the problem of 2, the problem of variables, and the transformation of combinatorial structures from working memory to long-term memory. This paper aims to show that these problems can be solved by means of neural "blackboard" architectures. For this purpose, a neural blackboard architecture for sentence structure is presented. In this architecture, neural structures that encode for words are temporarily bound in a manner that preserves the structure of the sentence. It is shown that the architecture solves the four problems presented by Jackendoff. The ability of the architecture to instantiate sentence structures is illustrated with examples of sentence complexity observed in human language performance. Similarities exist between the architecture for sentence structure and blackboard architectures for combinatorial structures in visual cognition, derived from the structure of the visual cortex. These architectures are briefly discussed, together with an example of a combinatorial structure in which the blackboard architectures for language and vision are combined. In this way, the architecture for language is grounded in perception. Perspectives and potential developments of the architectures are discussed.     

Explaining Emotions

Emotions and cognition are inextricably intertwined. Feelings influence thoughts and actions, which in turn can give rise to new emotional reactions. We claim that people infer emotional states in others using commonsense psychological theories of the interactions among emotions, cognition, and action. We present a situation calculus theory of emotion elicitation representing knowledge underlying commonsense causal reasoning involving emotions, and show how the theory can be used to construct explanations for emotional states. The method for constructing explanations is based on the notion of abduction. This method has been implemented in a computer program called AbMaL. The results of computational experiments using AbMaL to construct explanations of examples based on cases taken from a diary study of emotions indicate that the abductive approach to explanatory reasoning about emotions offers significant advantages. We found that the majority of the diary study examples cannot be explained using deduction alone, but they can be explained by making abjuctive inferences. These inferences provide useful information relevant to emotional states.     

Expertise-related differences in conceptual and ontological knowledge in the legal domain

Little research has been conducted on expertise-related differences in conceptual and ontological knowledge in law, even though this type of knowledge is prerequisite for correctly interpreting and reasoning about legal cases, and differences in conceptual and ontological knowledge structures between students and between students and teachers, might lead to miscommunication. This study investigated the extent and organisation of conceptual and ontological knowledge of novices, advanced students, and experts in law, using a card-sorting task and a concept-elaboration task. The results showed that novices used more everyday examples and were less accurate in their elaborations of concepts than advanced students and experts, on top of that, the organisation of their knowledge did not overlap within their group (i.e., no “shared” ontology). Experts gave more judicial examples based on the lawbook and were more accurate in their elaborations than advanced students, and their knowledge was strongly overlapping within their group (i.e., strong ontology). Incorrect conceptual knowledge seems to impede the correct understanding of cases and the correct application of precise and formal rules in law.     

Explaining default intuitions using maximum entropy

While research into default reasoning is extensive and many default intuitions are commonly held, no one system has yet captured all these intuitions nor given a formal account to motivate them. This paper argues that the extended maximum entropy approach which incorporates variable strength defaults provides a benchmark for default reasoning that is not only objectively motivated but also satisfies all the accepted default intuitions. It is shown that the behaviour of the approach coincides with a wide range of default intuitions taken from examples in the literature, and can be used to explain why some examples have led to confusion. Moreover, analysing the solutions produced by the maximum entropy approach enables clearer differentiation between the default knowledge they contain and the default inferences required of the reasoning system. This suggests that the maximum entropy approach can be used as a benchmark both for eliciting default knowledge when building a knowledge base and, by comparison, for clarifying the underlying biases of other default reasoning systems.     

再论我国心理学的分化现象

我国心理学正处于分化过程之中,其中两个明显的例证就是:基础心理学与应用及人文心理学的分化,以及对心理学研究和服务成果的评价标准摆脱SCI的束缚.这背后深层的原因在于,若以科学哲学认识论的视角,人类的知识大致可分为可靠有用的知识和无用虚幻(伪科学)的知识,可靠知识又可进一步分为科学的知识和非科学的知识.心理学从诞生之日起...     

Testimonial Knowledge from Lies

Recently, Dan O’Brien has argued that there are situations in which a hearer can gain testimonial knowledge from a speaker who is lying. In order to make his case, O’Brien presents two examples where a speaker lies to a hearer, but supposedly the hearer comes to have testimonial knowledge on the basis of the lying speaker’s testimony. O’Brien claims that his examples demonstrate that lies can be used to pass on knowledge in a non-inferential fashion. I argue that O’Brien is mistaken. More specifically, I argue that the hearer’s belief in the second example that O’Brien depicts fails to meet two plausible conditions for knowledge. First, the hearer’s belief fails to satisfy the requirements of the epistemic basing relation. Second, the hearer’s belief is not safe.     

多重样例变异性与先前知识对样例学习效果的影响述评

样例学习研究表明多重样例的学习效果好于单个样例。然而研究者关于如何有效设计多重样例得出了不同的发现。通过综述已有关于多重样例学习的实证研究,总结出两个尚未得到解决的问题：（1）多重样例之间的相似或相异程度应该如何;（2）学生的先前知识在多重样例学习中的作用如何。针对已有研究的局限性,本文指出,具有不同先前知识的学生学习时感受到不同的关键属性,多重样例应该基于学生学习时的关键属性设计特定的变易范式以帮助学生学习。     

Prevention of admission and continuity of care

An in-depth analysis of the recent reform in Italian psychiatry reveals that the relevance of these changes transcends national borders. However, these changes are, from the scientific point of view, worth much more than mere biased pragmatic interest. The reshaping of theory made possible by the transformation of Italian psychiatry in fact opens up new prospects for a scientifically founded form of psychiatric care. Thanks to the new Mental Health Act (No. 180 of 1978),² it has been possible to set up a type of administrative and institutional organization in which the psychiatric hospital no longer constitutes a functional part of the structures of psychiatric care. This reform thus provides the launching path for a real alternative where current psychiatric ideas and working methods can no longer be accepted as the gospel truth. This paper discusses how a correct problem-definition of psychiatric admission can provide a basis for a correct approach to psychopathological behaviour in a setting where the psychiatric hospital has no role to play and for the consolidation of this new practice.