The observing ego as voyeur

A resistance to self-observation and self-reflection is discussed in which there is a perversion of the observing ego. The observing ego has been unconsciously recruited in the service of enacting an unconscious fantasy: the fantasy of being an excited observer of a primal scene who is punished for making forbidden observations. This voyeuristic observing ego is pathologically enmeshed in a love triangle with the patient's seductive superego (i.e. identification with the desired but unfaithful parent) and with the patient's punitive superego (i.e. identification with the rivalrous parent). This unconscious scenario is played out in the clinical situation as the patient unreflectively cycles through phases of denial (i.e. self-seduction) and moral masochism (i.e. self-betrayal). A case study illustrates how humor may be employed to free the observing ego from being enthralled by a perverse superego. Humor may unconsciously enable a rebellious attitude toward the omnipotent sadism of a perversely oppressive superego and thus enable the observing ego to break free from its pathological enmeshment.     

The impulse to infidelity and oedipal splitting

Freud suggested that the child perceives parental intercourse as an act of infi delity by the desired but unfaithful parent. Parental sexual infi delity is felt to be a major narcissistic injury that gives rise to fantasies of revenge. A defensive organization arises to manage this trauma and its attendant revenge fantasies. That organization involves splitting of the desired parent into faithful and unfaithful parts, displacement of hostility on to the rival parent, and identifi cation with the desired but unfaithful parent resulting in the impulse to infi delity. Romantic fantasies of escape and rescue from evil rivals provide guilt free ways of satisfying fantasies of oedipal revenge. In those fantasies the evil rival is turned into an injured third party who gets his or her just deserts as the romantic couple gets to live happily ever after. This defensive organization may embroil patients in complicated love triangles as adults for which they may seek treatment. Analyzing the repudiated narcissistic wound of parental infi delity and the disguised revenge fantasies that defend against that wound may provoke narcissistic rage towards the analyst as a moralistic, possessive, controlling, envious, and spoiling oedipal parent.     

Elements of the Oedipus complex: A Kleinian account1

The author discusses and illustrates the place in current Kleinian practice of the analysis of the Oedipus complex. He outlines the development of the concept of the Oedipus complex by Freud and by Klein and later writers in the Kleinian tradition. Because the child's exclusion from his parents' sexual relationship represents such a fundamental aspect of reality for the child, analysis of the patient's responses to the oedipal situation constitutes the central task of analysis. Despite the Oedipus complex being in this way central, it is sometimes hard to discern because what is most visible are the patient's defensive responses to the oedipal situation. The emergence of meaning in analysis is often understood unconsciously as the product of the parental intercourse, represented by the work of the patient with the analyst, or of the analyst's or the patient's mind. The analysis of the patient's characteristic reactions to moments of meaningfulness in analysis is therefore an especially fruitful focus for the analysis of the Oedipus complex. The author illustrates these ideas by three clinical examples, from a 3½‐year‐old child, a borderline psychotic patient and a more neurotic patient.     

Building an identifiable latent class model with covariate effects on underlying and measured variables

In recent years, latent class models have proven useful for analyzing relationships between measured multiple indicators and covariates of interest. Such models summarize shared features of the multiple indicators as an underlying categorical variable, and the indicators' substantive associations with predictors are built directly and indirectly in unique model parameters. In this paper, we provide a detailed study on the theory and application of building models that allow mediated relationships between primary predictors and latent class membership, but that also allow direct effects of secondary covariates on the indicators themselves. Theory for model identification is developed. We detail an Expectation-Maximization algorithm for parameter estimation, standard error calculation, and convergent properties. Comparison of the proposed model with models underlying existing latent class modeling software is provided. A detailed analysis of how visual impairments affect older persons' functioning requiring distance vision is used for illustration.This work was supported by National Institute on Aging (NIA) Program Project P01-AG-10184-03 and National Institutes of Mental Health grant R01-MH-56639-01A1. Dr. Bandeen-Roche is a Brookdale National Fellow. The authors wish to thank Drs. Gary Rubin and Sheila West for kindly making the Salisbury Eye Evaluation data available. We also thank the Editor, the Associate Editor, and three referees for their valuable comments.     

Locally dependent latent trait model and the dutch identity revisited

In this paper, we propose a class of locally dependent latent trait models for responses to psychological and educational tests. Typically, item response models treat an individual's multiple response to stimuli as conditional independent given the individual's latent trait. In this paper, instead the focus is on models based on a family of conditional distributions, or kernel, that describes joint multiple item responses as a function of student latent trait, not assuming conditional independence. Specifically, we examine a hybrid kernel which comprises a component for one-way item response functions and a component for conditional associations between items given latent traits. The class of models allows the extension of item response theory to cover some new and innovative applications in psychological and educational research. An EM algorithm for marginal maximum likelihood of the hybrid kernel model is proposed. Furthermore, we delineate the relationship of the class of locally dependent models and the log-linear model by revisiting the Dutch identity (Holland, 1990). The work is supported by a research grant from the Marshall School of Business, University of Southern California. The author thanks the anonymous referees for their suggestions.     

The 'body–container': A new perspective on the 'body–ego'

Psychoanalytic theory and practice tend to focus on metaphorical and symbolic mental representations in a way that often pushes aside the importance of a bodily 'presence' possessing qualities that can not and should not be subordinated to the representational structure. By introducing the 'body – container' model, this paper reintroduces the concrete physical body into the psychoanalytic discourse in a more direct way. This clinical – theoretical model links the 'body-ego' ( Freud, 1923 ) to the container idea ( Bion, 1962 ) aiming to creates a new integrative psyche-soma scheme. The 'body – container' experience is available as a subjective realization through a priori psycho-physical forms structured as an envelope and a central vertical axis. These forms are the outcome of our given bodily structure experienced under the 'magnetic' force of object relation. The mental envelope is already discussed in psychoanalytic theory ( Anzieu, 1989, 1990 ; Bick, 1968 ) and I wish to introduce the characteristics of the vertical axis which I call 'the frontal spine', emphasizing its constitutional reciprocity with the skin envelope. The proposed model offers new insights into the psycho-physical organization in primitive mental states and may contribute to the understanding of the complementary structural relation between embodied and represented in human experience. Two clinical examples illustrate the therapeutic work relevant to disturbances in the primal psycho-physical space organization at different developmental levels.     

Tatsuoka 矩阵理论的修正

K .K.Tatsuoka和她同事开发的规则空间模型（RSM）是一种在国内外有较大影响的认知诊断模型,但是Tatsuoka的RSM中 矩阵理论存在缺陷和错误,这些失误使得RSM中用布尔描述函数（BDF）计算被试理想项目反应模式（IRP）的方法缺乏理论依据。这里揭示了Tatsuoka的 矩阵理论的缺陷和错误并引进既不使用BDF又便于应用的计算IRP的方法;接着还介绍一种由可达阵计算简化 阵的方法,该方法显示了可达阵在构造认知诊断测验的重要性。这些结果对丰富 矩阵理论及正确使用RSM进行认知诊断有一定的意义     

A systematic review of algorithm aversion in augmented decision making

Despite abundant literature theorizing societal implications of algorithmic decision making, relatively little is known about the conditions that lead to the acceptance or rejection of algorithmically generated insights by individual users of decision aids. More specifically, recent findings of algorithm aversion—the reluctance of human forecasters to use superior but imperfect algorithms—raise questions about whether joint human-algorithm decision making is feasible in practice. In this paper, we systematically review the topic of algorithm aversion as it appears in 61 peer-reviewed articles between 1950 and 2018 and follow its conceptual trail across disciplines. We categorize and report on the proposed causes and solutions of algorithm aversion in five themes: expectations and expertise, decision autonomy, incentivization, cognitive compatibility, and divergent rationalities. Although each of the presented themes addresses distinct features of an algorithmic decision aid, human users of the decision aid, and/or the decision making environment, apparent interdependencies are highlighted. We conclude that resolving algorithm aversion requires an updated research program with an emphasis on theory integration. We provide a number of empirical questions that can be immediately carried forth by the behavioral decision making community.     

如何利用开源工具分析fMRI数据：基于多体素模式的有监督机器学习算法介绍

摘要：目前,多体素模式分析（MVPA）日渐普遍地应用于脑影像研究。近些年,机器学习的模式分类等算法在MVPA方法中被广泛应用,因其具有能够抽取高维数据模式,提高数据利用率的优点。其中一种典型的应用是利用解码的思想来解决神经表征问题,本文主要介绍了利用基于Python语言的工具库中有监督学习算法分析数据的过程。除介绍Nilearn结合Scikit-learn分析数据的步骤外,还比较不同算法的效率,为算法的选择及参数设备提供具体参考。     

Estimating latent distributions

Consider vectors of item responses obtained from a sample of subjects from a population in which ability is distributed with densityg(), where the are unknown parameters. Assuming the responses depend on through a fully specified item response model, this paper presents maximum likelihood equations for the estimation of the population parameters directly from the observed responses; i.e., without estimating an ability parameter for each subject. Also provided are asymptotic standard errors and tests of fit, computing approximations, and details of four special cases: a non-parametric approximation, a normal solution, a resolution of normal components, and a beta-binomial solution.The author would like to thank R. Darrell Bock for his comments, suggestions, and encouragement during the course of this work.