A parametric procedure for ultrametric tree estimation from conditional rank order proximity data

The psychometric and classification literatures have illustrated the fact that a wide class of discrete or network models (e.g., hierarchical or ultrametric trees) for the analysis of ordinal proximity data are plagued by potential degenerate solutions if estimated using traditional nonmetric procedures (i.e., procedures which optimize a STRESS-based criteria of fit and whose solutions are invariant under a monotone transformation of the input data). This paper proposes a new parametric, maximum likelihood based procedure for estimating ultrametric trees for the analysis of conditional rank order proximity data. We present the technical aspects of the model and the estimation algorithm. Some preliminary Monte Carlo results are discussed. A consumer psychology application is provided examining the similarity of fifteen types of snack/breakfast items. Finally, some directions for future research are provided.     

Ordinal network representation: Representing proximities by graphs

Ordinal network representations are graph-theoretic representations of proximity data. They seek to provide parsimonious representations of the ordinal (nonmetric) information in observed proximity data by means of the minimum-path-length distance of a connected and weighted graph. In contrast to traditional tree-based graph-theoretic approaches, ordinal network representation is not limited to but includes the representation by trees. Asymmetry in the proximity data and violations of zero-minimality are allowed for. The paper explores fundamental representation and uniqueness results and discusses a method of constructing ordinal network representations. A simple strategy for handling the problem of errors in the data is described and illustrated.This work was supported by grant Fe 75/20-2 of the Deutsche Forschungsgemeinschaft. The author is indebted to Hubert Feger for many inspiring discussions.     

创造性思维中语义搜索过程：基于答案累积时间函数和语义相似性的量化分析

通过描绘发散性思维测验(物品多用途, AUT)中答案生成在累积函数和语义相似性等一系列参数上的量化特征, 揭示创造性思维的语义搜索过程。结果发现：(1)新颖AUT条件中, 语义搜索呈现与自由联想类似的负加速特点, 但搜索速度较寻常AUT条件更慢。(2)新颖AUT条件中所生成的答案与题目(即物品)均具有较低的语义相似性, 且显著小于寻常AUT条件。(3)新颖AUT条件中生成的答案比寻常AUT条件表现出显著更低的聚类程度, 其中可聚类答案和未聚类答案与题目的语义相似度均较低, 且不存在显著差异, 二者在新颖性上也不存在显著差异。以上结果说明了创造性思维的语义信息搜索过程具有与自由联想类似的激活扩散特征, 但总体搜索速度较慢。新颖性要求使得个体在最初搜索时便开始摆脱题目的语义限制而进行远距离搜索(避免就近搜索), 并倾向于在每个语义场中只生成一个答案(避免局部搜索), 但也可能会在远离题目的语义场中生成多个同类别答案。     

Fuzzy Identities for an Inclusive Anglohispanic Dialogue

When constructed in linear terms, cultures and identities misrepresent other people, constructing crisp boundaries that separate groups as if completely different. To demonstrate the negative impact of such views, I analyze cultural texts such as songs, films, and Web pages, showing the intercultural complexity existing in different constructions of Mexicanness as part of the dialogue arising in the political, social, and cultural interaction between Mexico and the United States. I emphasize the contrast between examples that reinforce identities that can be interpreted as fuzzy and inclusive, against those promoting and generating discrimination and exclusion.     

Music Training and Semantic Clustering in College Students

College students with 5 or more years of music training recalled significantly more words from a 16-item word list than did students with 0-4 years of training. The superior recall of the extensively trained students linked to better application of a semantic-clustering strategy across a series of 3 test trials. Music education and language experience may have similar influences on the development of verbal memory.     

CLASSI: A classification model for the study of sequential processes and individual differences therein

In psychological research, one often aims at explaining individual differences in S-R profiles, that is, individual differences in the responses (R) with which people react to specific stimuli (S). To this end, researchers often postulate an underlying sequential process, which boils down to the specification of a set of mediating variables (M) and the processes that link these mediating variables to the stimuli and responses under study. Obviously, a crucial task is to chart how the individual differences in the S-R profiles are caused by individual differences in the S-M link and/or by individual differences in the M-R link. In this paper we propose a new model, called CLASSI, which was explicitly designed for this task. In particular, the key principle of CLASSI consists of reducing the S, M, and R nodes of a sequential process to a few mutually exclusive types and inducing an S-M and an M-R person typology from the data, with the S-M person types being characterized in terms of if S type then M type rules and the M-R person types in terms of if M type then R type rules. As such, the S-M and M-R person types and their associated if–then rules represent the important individual differences in the S-M and M-R links of the sequential process under study. An algorithm to fit the CLASSI model is described and evaluated in a simulation study. An application of CLASSI to data from the behavioral domain of anger and sadness is discussed. Finally, we relate CLASSI to other methods and discuss possible extensions. The first author is a post-doctoral fellow of the Fund for Scientific Research—Flanders (Belgium). The research reported in this paper was partially supported by the Research Council of K.U. Leuven (GOA/05/04).     

A Note on Prototypes,Convexity and Fuzzy Sets

The work on prototypes in ontologies pioneered by Rosch [10] and elaborated by Lakoff [8] and Freund [3] is related to vagueness in the sense that the more remote an instance is from a prototype the fewer people agree that it is an example of that prototype. An intuitive example is the prototypical “mother”, and it is observed that more specific instances like ”single mother”, “adoptive mother”, “surrogate mother”, etc., are less and less likely to be classified as “mothers” by experimental subjects. From a different direction Gärdenfors [4] provided a persuasive account of natural predicates to resolve paradoxes of induction like Goodman’s “Grue” predicate [5]. Gärdenfors proposed that “quality dimensions” arising from human cognition and perception impose topologies on concepts such that the ones that appear “natural” to us are convex in these topologies. We show that these two cognitive principles — prototypes and predicate convexity — are equivalent to unimodal (convex) fuzzy characteristic functions for sets. Then we examine the case when the fuzzy set characteristic function is not convex, in particular when it is multi-modal. We argue that this is an indication that the fuzzy concept should really be regarded as a super concept in which the decomposed components are subconcepts in an ontological taxonomy.     

刻板印象的自动激活实验研究

本研究应用模糊主次评判方法配合语义启动技术进行实验。结果表明;在年龄刻板印象上存在自动激活,而且没有性别差异;用不同性质的启动词来激活与年龄有关的刻板印象,激活后的刻板印象对年龄的判断有不同的影响,而且被试没有一个人意识到这点,表明内隐刻板印象的存在;人的判断具有模糊性,模糊主次评判方法有助于社会认知领域的量化研究,这是一个全新的尝试。     

模糊分组的时间层次网络结构研究

本研究通过两个实验来对连续性的时间顺序标码的层次网络结构的性质进行了探讨。研究结果表明,连续性的时间顺序标码是按照层次网络的结构组织起来的,若干项目组成一个小组,若干小组组成更大的组。连续性的时间标码层次网络的形成具有自动性、内隐性的特点。连续性的时间顺序标码的层次网络结构是主观的、模糊的。两个相邻的小组的项目之间出现了距离效应,而两个相邻的大组的项目之间则出现了越界效应,由于两个大组的项目的平均距离大于两个小组的项目的平均距离,越界效应大于距离效应。