负面评价恐惧对社交焦虑的影响:基于社交焦虑的认知行为模型

在社交焦虑认知行为模型的理论视角下，本研究拟探讨负面评价恐惧、不确定性容忍度和依赖型自我构念对社交焦虑的影响及其作用机制。以424名大学生为被试，使用问卷调查法的研究结果表明：（1）负面评价恐惧对社交焦虑有显著预测作用，且不确定性容忍度在这一关系中的中介作用显著；（2）不确定性容忍度的间接效应受到依赖型自我构念的调节。具体而言，该中介效应在高依赖型自我构念群体中更为显著。本研究结果不仅有助于揭示负面评价恐惧对社交焦虑的影响及其作用机制，而且对社交焦虑的预防和干预也有一定的理论和实践指导价值。     

Psychoanalysis and evaluation: a stratified model focused on the uniqueness of the case

ABSTRACT

Objectives: This article addresses the methodological controversies surrounding the issue of how to evaluate the psychotherapies. It proposes to identify the principles of an integrative and stratified model in order to report the results of analytical therapy (its efficacy) based on the very effectiveness of its processes. Thus, the uniqueness of the case is put at the center of the evaluation setting.

Methods: Drawing on science studies, the authors engage in a reflexive exercise on the problem of psychoanalysis’ evaluation based on methodological questions raised in the field over time and current issues related to practice.

Results: First, the regularly asserted opposition between the norms of analytical practice and those governing standard evaluation procedures is reinterpreted as the effect of a lack of intermediate epistemic patterns.

Second, the fundamental principles of an integrative model are considered so as to translate and articulate a set of heterogeneous requirements into distinct strata.

Discussion: Since psychoanalysis is fundamentally a case-by-case practice characterized by inequivalence and unexpectedness, its utmost aim is to use a type of effectiveness based on the singularity of the case. However, this does not prevent it from being evaluable provided that the epistemic levels of the evaluation are clearly differentiated.     

Analysis of meteorological conditions in Spain by means of clustering techniques

A comprehensive analysis of clustering techniques is presented in this paper through their application to data on meteorological conditions. Six partitional and hierarchical clustering techniques (k-means, k-medoids, SOM k-means, Agglomerative Hierarchical Clustering, and Clustering based on Gaussian Mixture Models) with different distance criteria, together with some clustering evaluation measures (Calinski–Harabasz, Davies–Bouldin, Gap and Silhouette criterion clustering evaluation object), present various analyses of the main climatic zones in Spain. Real-life data sets, recorded by AEMET (Spanish Meteorological Agency) at four of its weather stations, are analyzed in order to characterize the actual weather conditions at each location. The clustering techniques process the data on some of the main daily meteorological variables collected at these stations over six years between 2004 and 2010.     

Research about the university teaching performance evaluation under the data envelopment method

How to take active and effective measures to evaluate the university scientifically and rationally has been an eternal topic that the educational circles are constantly exploring. Based on the principle of index construction, the current educational performance evaluation index system is improved and a more reasonable evaluation index system is formed. On this basis, taking the sample data in 2017 as an example, the principal component analysis method is used to reduce the dimension of input and output indicators and eliminate the correlation between indicators, and three principal components of input and three principal components of output are obtained. Secondly, data envelopment analysis model is established, and the data processed are analyzed with the help of MATLAB and DEAP2.1 operation software. The efficiency of these 24 colleges and universities is compared to understand the efficiency and differences of each college. Moreover, projection analysis of non-DEA effective DMU is completed and the direction of improvement and the specific adjustment value are pointed out.     

Updating a progic

This paper presents a progic, or probabilistic logic, in the sense of Haenni et al. [8]. The progic presented here is based on Bayesianism, as the progic discussed by Williamson [15]. However, the underlying generalised Bayesianism differs from the objective Bayesianism used by Williamson, in the calibration norm, and the liberalisation and interpretation of the reference probability in the norm of equivocation. As a consequence, the updating dynamics of both Bayesianisms differ essentially. Whereas objective Bayesianism is based on a probabilistic re-evaluation, orthodox Bayesianism is based on a probabilistic revision. I formulate a generalised and iterable orthodox Bayesian revision dynamics. This allows to define an updating procedure for the generalised Bayesian progic. The paper compares the generalised Bayesian progic and Williamson's objective Bayesian progic in strength, update dynamics and with respect to language (in)sensitivity.     

How unexpected observations lead to new beliefs: A Peircean pathway

People acquire new beliefs in various ways. One of the most important of these is that new beliefs are acquired as a response to experiencing events that one did not expect. This involves a form of inference distinct from both deductive and inductive inference: abductive inference. The concept of abduction is due to the American pragmatist philosopher C. S. Peirce. Davies and Coltheart (in press) elucidated what Peirce meant by abduction, and identified two problems in his otherwise promising account requiring solution if that account were to become fully workable. Here we propose solutions to these problems and offer an explicit cognitive model of how people derive new beliefs from observations of unexpected events, based on Peirce’s work and Sokolov’s ideas about prediction error triggering new beliefs. We consider that this model casts light not only upon normal processes of belief formation but also upon the formation of delusional beliefs.     

The moderating role of interviewer's regulatory focus in the effectiveness of impression management tactics: Regulatory fit as a source of subjective value

Based on the recently explored regulatory fit effect in social contexts, the present research is the first to investigate the interaction between interviewer's regulatory focus and interviewee's impression management (IM) tactics. We hypothesized that assertive and defensive IM tactics would fit with interviewer's promotion and prevention focus, respectively, and that interviewer's experience of this regulatory fit would lead to enhanced interview evaluation. We conducted four studies in which the participants were asked to rate an interviewee after reading a list of the interviewee's IM-related behaviours or watching a videotaped interview. Additionally, the participant's regulatory focus was operationalized as both an induced situational state and a measured chronic trait. The results supported our hypotheses by showing a significant interaction of the interviewer's regulatory focus and the IM tactics on interview evaluation: the promotion-assertive and the prevention-defensive ratings were more positive than the prevention-assertive and the promotion-defensive ratings. Moreover, mediation analysis revealed that the interaction exerts its effects on interview evaluation by providing interviewers with an intrapersonal regulatory fit experience.