Toward a More Credible Understanding of Post-Traumatic Growth

Traditional research on post-traumatic growth has utilized methodologically flawed cross-sectional designs that involve retrospective assessments of post-traumatic growth. This has resulted in a majority of research in this field suffering from a lack of credibility and reliability. In this special issue, we present nine articles that seek to make innovative conceptual and methodological contributions with the goal of promoting better research practices on post-traumatic growth. In the introduction to this special issue, we provide an overview of these contributions, and discuss the implications of these articles both to improving future scholarship and to encouraging personality scientists to examine this important phenomenon in the years and decades to come.     

CHRISTIANITY,SCIENCE, AND THREE PHASES OF BEING HUMAN

The alleged conflict between religion and science most pointedly focuses on what it is to be human. Western philosophical thought regarding this has progressed through three broad stages: mind/body dualism, Neo‐Darwinism, and most recently strong artificial intelligence (AI). I trace these views with respect to their relation to Christian views of humans, suggesting that while the first two might be compatible with Christian thought, strong AI presents serious challenges to a Christian understanding of personhood, including our freedom to choose, moral choice itself, self‐consciousness, and the relevance of God to our beginning, being, and ending.     

Creation and humanity: Veli-Matti Kärkäinen's answer to the ultimate question

This article focuses on the third volume of Vel-Matti Kärkkäinen's systematic theology, titled Creation and Humanity. After a brief overview of the volume the article offers some clarification on the tenth chapter, especially on its interaction with paleontology. After that, two constructive observations follow. The first is related to Kärkkäinen's notion of the embeddedness of human nature, and the second is to further employ systems thinking in his constructive work on creation and human evolution.     

The return of the repressed. On Robert N. Bellah,Norman O. Brown,and religion in human evolution

As much as Robert Bellah’s final work, Religion in Human Evolution, has been studied and dissected, no critic underlined the importance of psychoanalysis for its main argument and its theoretical framework. The paper shows the influence exerted by a controversial interpreter of Freud, Norman O. Brown, on Bellah’s ideas, intellectual profile, and writing style in the late-1960s and early 1970s. While in search for a new intellectual voice, Bellah was struck by Brown’s work and began to make intensive use of his book, Love’s Body, both in his teaching and in his research of the early 1970s, during his so-called “symbolic realism” period. While Bellah abandoned Brown’s ideas and style in the mid-1970s, some of the basic intuitions he had during that period still survived as one of the major theoretical intuitions of Religion and Human Evolution.     

Quantifying the Interplay of Semantics and Phonology During Failures of Word Retrieval by People With Aphasia Using a Multiplex Lexical Network

Investigating instances where lexical selection fails can lead to deeper insights into the cognitive machinery and architecture supporting successful word retrieval and speech production. In this paper, we used a multiplex lexical network approach that combines semantic and phonological similarities among words to model the structure of the mental lexicon. Network measures at different levels of analysis (degree, network distance, and closeness centrality) were used to investigate the influence of network structure on picture naming accuracy and errors by people with Anomic, Broca's, Conduction, and Wernicke's aphasia. Our results reveal that word retrieval is influenced by the multiplex lexical network structure in at least two ways—(a) the accuracy of production and error type on incorrect productions were influenced by the degree and closeness centrality of the target word, and (b) error type also varied in terms of network distance between the target word and produced error word. Taken together, the analyses demonstrate that network science techniques, particularly the use of the multiplex lexical network to simultaneously represent semantic and phonological relationships among words, reveal how the structure of the mental lexicon influences language processes beyond traditionally examined psycholinguistic variables. We propose a framework for how the multiplex lexical network approach allows for understanding the influence of mental lexicon structure on word retrieval processes, with an eye toward a better understanding of the nature of clinical impairments, like aphasia.     

关于胚胎干细胞研究的一场伦理之争

关于“人兔细胞融合”的伦理之争,主要围绕“人兔细胞融合”实验是否违背伦理,要不要经过知情同意,以及科学技术与伦理道德的关系等问题而进行。这场讨论是正常的,健康的,有益的,倘能加以认真总结,将有助于推进学术争鸣。     

Longing for Life Extension: Science Fiction and Late Life

Rejuvenescence has long been a topic of legend and medicine. As the body became the property of medical science, speculative fiction asked how fantastic experiments with bodies would affect the life course. In science fiction, medical breakthroughs promise or threaten to forestall or even reverse the decline from midlife through old age to senility and decrepitude. Responding to debates over evolution, eugenics, and scientific experimentation with human and animal subjects, rejuvenescence novels such as Bruce Sterling's Holy Fire (1996) ask readers whether they desire long life or heightened quality of life; the consolations of age or the hungers of youth; short-lived intensity or perpetual ennui.     

Conflicts of interest in science in Armenia

The author describes problems facing Armenia in reorganization of the structure of science in the post-socialist era with the aim of utilizing limited state resources more efficiently by reducing the number of separate scientific institutes, concentrating on essential core subjects required by the nation and encouraging all other projects to compete in the international arena for grant sponsorship. An earlier version of this paper was presented at an International Conference on “Conflict of Interest and its Significance in Science and Medicine” held in Warsaw, Poland on 5–6 April, 2002.     

The continuing need for disinterested research

For scientific knowledge to be trustworthy, it needs to be dissociated from material interests. Disinterested research also performs other important non-instrumental roles. In particular, academic science has traditionally provided society with reliable, imaginative public knowledge and independent, self-critical expertise. But this type of science is not compatible with the practice of instrumental research, which is typically proprietary, prosaic, pragmatic and partisan. With ever-increasing dependence on commercial or state funding, all modes of knowledge production are merging into a new, ‘post-academic’ research culture which is dominated by utilitarian goals. Growing concern about conflicts of interest is thus a symptom of deep-seated malaise in science and medicine. An expanded version of this paper was presented at an International Conference on “Conflict of Interest and its Significance in Science and Medicine” held in Warsaw, Poland on 5–6 April, 2002.     

Getting the Big Picture in Community Science: Methods That Capture Context

Community science has a rich tradition of using theories and research designs that are consistent with its core value of contextualism. However, a survey of empirical articles published in the American Journal of Community Psychology shows that community scientists utilize a narrow range of statistical tools that are not well suited to assess contextual data. Multilevel modeling, geographic information systems (GIS), social network analysis, and cluster analysis are recommended as useful tools to address contextual questions in community science. An argument for increased methodological consilience is presented, where community scientists are encouraged to adopt statistical methodology that is capable of modeling a greater proportion of the data than is typical with traditional methods.