Assertion,Complexity, and Sincerity

The target of this paper is the ‘simple’ knowledge account of assertion, according to which assertion is constituted by a single epistemic rule of the form ‘One must: assert p only if one knows p’ (where p is a proposition). My aim is to argue that those who are attracted to a knowledge account of assertion should prefer what I call the ‘complex’ knowledge account, according to which assertion is constituted by a system of rules all of which are, taken together, constitutive of assertion. One of those rules—which, following John Searle, I call the ‘preparatory condition’—is of the form ‘One must: assert p only if one knows p.’ All else being equal, simple accounts are preferable to complex accounts. I argue in this paper that all else isn't equal. While the simple knowledge account provides an elegant explanation of certain data, it is hard to see how to integrate the simple knowledge account into a more general theory of illocutionary acts. Because the complex knowledge account avoids this objection while explaining the same data as the simple knowledge account does, I conclude that the complex knowledge account is superior to the simple knowledge account.     

节律在听觉言语理解中的作用

言语理解是听者接受外部语音输入并且获得意义的心理过程。日常交流中,听觉言语理解受多尺度节律信息的影响,常见有韵律结构节律、语境节律、和说话者身体语言节律三方面外部节律。它们改变听者在言语理解中的音素判别、词汇感知以及言语可懂度等过程。内部节律表现为大脑内神经振荡,其能够表征外部言语输入在不同时间尺度下的层级特征。外部节律性刺激与内部神经活动的神经夹带能够优化大脑对言语刺激的处理,并受到听者自上而下的认知过程的调节进一步增强目标言语的内在表征。我们认为它可能是实现内外节律相互联系并共同影响言语理解的关键机制。对内外节律及其联系机制的揭示能够为理解言语这种在多层级时间尺度上具有结构规律的复杂序列提供了一个研究窗口。     

In search of a learning model

While the four commentaries reflect a range of different perspectives on my target paper (Vihman, 2017), all basically accept the overall approach, which has been central to my research for 30 years. Each commentary proposes ways of deepening aspects of the ideas expressed or points out limitations and potential areas in which elaboration would be useful. This response takes up each commentary in turn.     

Disruption of writing by background speech: Does sound source location and number of voices matter?

It is not unusual that people have to write in an environment where background speech is present. Background speech can vary in both speech intelligibility and location of the sound source. Earlier research has shown disruptive effects of background speech on writing performance. To expand and reinforce this knowledge, the present study investigated the role of number of voices and sound source location in the relation between background speech and writing performance. Participants wrote texts in quiet or in background speech consisting of one or seven voices talking simultaneously located in front of or behind them. Overall, one voice was more disruptive than seven voices talking simultaneously. Self‐reports showed that sound from the front was more disruptive compared with sound from behind. Results are in line with theory of interference‐by‐process, attentional capture, and the cross‐modal theory of attention. The relevance of the results for open‐office environments is discussed.     

Teaching mands for information using speech generating devices: A replication and extension

Approximately 30% of individuals diagnosed with autism spectrum disorder (ASD) fail to develop vocal communication and, therefore, use some form of augmentative or alternative communication system. The current study replicates and extends previous research on teaching “Who?” and “Which?” mands for information to 3 young children diagnosed with ASD using a speech generating device. Procedures were evaluated using a multiple baseline across participants design. All participants learned to mand for information and, subsequently, used the information to access preferred items.     

人声加工的神经机制

人声是人类听觉环境中最熟知和重要的声音, 传递着大量社会相关信息。与视觉人脸加工类似, 大脑对人声也有着特异性加工。研究者使用电生理、脑成像等手段找到了对人声有特异性反应的脑区, 即颞叶人声加工区(TVA), 并发现非人类动物也有类似的特异性加工区域。人声加工主要涉及言语、情绪和身份信息的加工, 分别对应于三条既相互独立又相互作用的神经通路。研究者提出了双通路模型、多阶段模型和整合模型分别对人声的言语、情绪和身份加工进行解释。未来研究需要进一步讨论人声加工的特异性能否由特定声学特征的选择性加工来解释, 并深入探究特殊人群(如自闭症和精神分裂症患者)的人声加工的神经机制。     

Thoughts about the internalised speaking object: psychoanalytic psychotherapy with children of delayed verbal development

This paper discusses the meaningful effects of intensive psychoanalytic psychotherapy on language development in children with verbal delay or disorder. Three clinical cases of children aged five to seven are presented; two of these display significant verbal delay and one exhibits unusually high verbal abilities. Following Meltzer, the author explores the concept of the ‘internalised speaking object’ – a good object speaking to the child, which has been internalised. This internal model is essential for the child’s development of language and speech. At times, these children experience this internal object as a persecutory object which must be warded off and avoided. Even more so, when the external object addresses the children verbally, language itself becomes a persecutor and they experience a fear of disintegration. During such times, the therapist must find new and creative ways for communication. The author describes his therapeutic efforts in dealing with these difficulties which stem both from the lack of a reciprocal verbal communication and from the therapist becoming a persecutory object to the child, and demonstrates the manner in which he facilitated gradual shifts in the patient, from an anxious and defensive position into a more relaxed one. These efforts set in motion a process of internalisation of a speaking object by the child and the development of internal language, that is, thinking along with expressive verbal language. The article furnishes some evidence to support the idea that verbal development relies significantly on establishing good, strong and healthy early object relations.     

Robust Methods for Moderation Analysis with a Two-Level Regression Model

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.