论胡塞尔现象学明见性概念的问题情境及其基本特征

"明见性"概念在胡塞尔的现象学研究中具有十分关键的地位,但他本人对这个作为其哲学最初入口的关键性问题却始终采取一种含糊其辞的态度。不遗余力地确立绝对认识与自我负责的生活规范以及在自身意识中寻找知识的确然性是明见性概念最切身的两大问题情境,而直观性、相对于意识的直接显现、意向与充实的统一可以说是这一概念的最基本特征。这既体现出他对明见性概念的前身即确然性概念的独特理解与持续改造和发展,在更深层次的意义上也显示出作为一个立志成为开启性哲学家的胡塞尔同他之前各种思想特有的关联及其自身理论的特点。     

“古史辨”派、“二重证据法”及其相关问题——裘锡圭先生访谈录

裘锡圭先生在古文字、古文献、上古史等领域均有很高的成就,为学界所公认。2007年3月,应文史哲编辑部之约,裘先生接受了本刊特约记者的采访。在访谈中,裘先生回顾了自己的学习和研究的历程,就"古史辨"派、上古史、出土文献研究及"二重证据法"、"五帝时代"等问题畅谈了自己的看法。他认为,"古史辨"派在对上古史认识的大方向上是正确的,在古书辨伪方面则有许多地方需要纠正;我们今天对于疑古思想和学说应持继承与批判相结合的态度。20世纪70年代以后虽然涌现了大批出土文献,但就出土文献研究而言,传世典籍以及历代学者对传世典籍的研究仍然是基础。目前中国古典学,包括出土文献研究领域存在的问题主要不在缺乏理论或方法,而在研究者往往缺乏科学的态度。必须大力提倡一切以学术为依归的、实事求是的研究态度,提倡学术道德、学术良心。     

民事证据限制契约论

民事诉讼由辩论主义所支配,当事人对诉讼享有处分权,因此证据限制契约应当具备诉讼上的效力。但是,当证据限制契约与自由心证以及法官的职权证据调查相冲突时,证据限制契约则不合法。我国存在认可证据限制契约的条件,但在具体适用上必须注意缔结时限、缔结种类及范围问题。     

辩护人妨害作证罪之证明

辩护人妨害作证罪的认定多是依靠作为＂受害人＂的控方收集的言词性证据。辩护人妨害作证罪的证明需要保护被告人的质证权,控方证人需要出庭作证,警察需要出庭作证。辩护律师的真实义务标准相对较低,对证据的认识不同于司法机关。辩护人妨害作证的判断应该以律师执业标准为准绳,律师向被告人披露相关证据不构成妨害作证。     

Decision Making Under Uncertainty—An Example for Seismic Risk Management

Decision-making techniques are used to select the "best" alternatives under multiple and often conflicting criteria. Multicriteria decision making (MCDM) necessitates to incorporate uncertainties in the decision-making process. The major thrust of this article is to extend the framework proposed by Yager^{( 1 )} for multiple decisionmakers and fuzzy utilities (payoffs). In addition, the concept of expert credibility factor is introduced. The proposed approach is demonstrated for an example of seismic risk management using a heuristic hierarchical structure. A step-by-step formulation of the proposed approach is illustrated using a hypothetical example and a three-story reinforced concrete building.     

A Cascaded Inference Model for Evaluation of the Internal Audit Report*

This paper provides a normative framework for how external auditors should evaluate internal audit (IA) work, with a view to assessing the risk of material misstatement. The central issue facing the external auditor when evaluating IA work is the reliability of IA work. Reliability assessments are structured using the cascaded inference framework from behavioral decision theory, in which attributes of source reliability are explicitly modeled and combined using Bayes' rule in order to determine the inferential value of IA work. Results suggest that the inferential value of an IA report is highly sensitive to internal auditor reporting bias, but relatively insensitive to reporting veracity. Veracity refers to internal auditors' propensity to report truthfully, whereas bias refers to the propensity to misreport findings. Results also indicate that this sensitivity to reporting bias is conditional on the level of internal auditor competence, thus suggesting significant interaction effects between the objectivity and competence factors. Collectively, these findings suggest that the impact of source reliability attributes may be more complex than portrayed in the auditing standards and that recognizing these subtleties may lead to greater efficiency and effectiveness.     

Editorial Collaborators

Abstract

The present note explores sources of misplaced criticisms of P-values, such as conflicting definitions of “significance levels” and “P-values” in authoritative sources, and the consequent misinterpretation of P-values as error probabilities. It then discusses several properties of P-values that have been presented as fatal flaws: That P-values exhibit extreme variation across samples (and thus are “unreliable”), confound effect size with sample size, are sensitive to sample size, and depend on investigator sampling intentions. These properties are often criticized from a likelihood or Bayesian framework, yet they are exactly the properties P-values should exhibit when they are constructed and interpreted correctly within their originating framework. Other common criticisms are that P-values force users to focus on irrelevant hypotheses and overstate evidence against those hypotheses. These problems are not however properties of P-values but are faults of researchers who focus on null hypotheses and overstate evidence based on misperceptions that p?=?0.05 represents enough evidence to reject hypotheses. Those problems are easily seen without use of Bayesian concepts by translating the observed P-value p into the Shannon information (S-value or surprisal) –log₂(p).     

Bias, racism and evidence-based practice: The case for more focused development of the child welfare evidence base

In spite of continuing concerns about disproportionate representation of African Americans, American Indians, and selected other groups in foster care, development of the practice and policy evidence base has paid scant attention to incorporating the specific concerns of these communities in intervention research. The authors review the current foundation of evidence-based practice and identify gaps in the knowledge base with specific reference to race/ethnicity/culture and class. They recognize the current concerns regarding disproportionality in child welfare services; and summarize the current research on bias and racism to establish potential mechanisms contributing to racially disproportionate outcomes. Addressing these literatures in concert with one another gives new meaning to the phrase, culturally competent evidence-based practice. Culturally competent practice goes beyond admonishing practitioners and policy makers to be more sensitive or to undertake such training. It is a pathway to the development of a more targeted and relevant evidence base: 1) rigorous intervention research with diverse populations could be more intentionally developed and 2) existing rigorous research on successfully addressing bias could be more broadly applied and tested in child welfare. A model for evaluating the validity of the evidence base with respect to diverse populations is proposed.     

Bias modelling in evidence synthesis

Summary.  Policy decisions often require synthesis of evidence from multiple sources, and the source studies typically vary in rigour and in relevance to the target question. We present simple methods of allowing for differences in rigour (or lack of internal bias) and relevance (or lack of external bias) in evidence synthesis. The methods are developed in the context of reanalysing a UK National Institute for Clinical Excellence technology appraisal in antenatal care, which includes eight comparative studies. Many were historically controlled, only one was a randomized trial and doses, populations and outcomes varied between studies and differed from the target UK setting. Using elicited opinion, we construct prior distributions to represent the biases in each study and perform a bias-adjusted meta-analysis. Adjustment had the effect of shifting the combined estimate away from the null by approximately 10%, and the variance of the combined estimate was almost tripled. Our generic bias modelling approach allows decisions to be based on all available evidence, with less rigorous or less relevant studies downweighted by using computationally simple methods.