校会合作:推进本土非公募基金会项目管理和人才培养的专业化

随着后条例时代的来临,我国非公募基金会的数量逐年增多,但大多数非公募基金会在项目管理的专业化方面,尚存在严重的滞后现象。非公募基金会应正视目前所处的困境,并积极寻求突破,可尝试从校会合作的角度,通过积极推进与科研院校、科研机构的交流合作,探索一条优化项目管理、培养专业人才的路径,以推进本土非公募基金会项目管理的专业化。     

校会合作:推进本土非公募基金会项目管理和人才培养的专业化

随着后"条例"时代的来临,我国非公募基金会的数量逐年增多,但大多数非公募基金会在项目管理的专业化方面,尚存在严重的滞后现象。非公募基金会应正视目前所处的困境,并积极寻求突破,可尝试从校会合作的角度,通过积极推进与科研院校、科研机构的交流合作,探索一条优化项目管理、培养专业人才的路径,以推进本土非公募基金会项目管理的专业化。     

Probability weighting and the ‘level’ and ‘spacing’ of outcomes: An experimental study over losses

The main goal of the experimental study described in this paper is to investigate the sensitivity of probability weighting to the payoff structure of the gambling situation—namely the level of consequences at stake and the spacing between them—in the loss domain. For that purpose, three kinds of gambles are introduced: two kinds of homogeneous gambles (involving either small or large losses), and heterogeneous gambles involving both large and small losses. The findings suggest that at least for moderate/high probability of loss do both ‘level’ and ‘spacing’ effects reach significance, with the impact of ‘spacing’ being both opposite to and stronger than the impact of ‘level’. As compared to small-loss gambles, large-loss gambles appear to enhance probabilistic optimism, while heterogeneous gambles tend to increase pessimism.

Semantic Analysis of the Theoretical Foundations of Biology

生物学理论作为科学哲学研究中的一个另类一直受到关注。它与传统科学模式间的差异是造成这种现象的原因之一。解读这种差异的根源,需要对生物学的理论基础以及理论结构给予充分的关注。生物学特有理论结构所表现出的多元语境与语义结构的复杂性,决定了对生物学理论基础的研究应当重视语义分析的方法,尤其是对理论本身进行语义分解并研究其中的语义关联问题,从而解读生物学模式作为一种不同于理化科学的特殊科学解释观的合理性。     

Semantic Analysis of the Theoretical Foundations of Biology

生物学理论作为科学哲学研究中的一个另类一直受到关注。它与传统科学模式间 的差异是造成这种现象的原因之一。解读这种差异的根源,需要对生物学的理论基础 以及理论结构给予充分的关注。生物学特有理论结构所表现出的多元语境与语义结构 的复杂性,决定了对生物学理论基础的研究应当重视语义分析的方法,尤其是对理论 本身进行语义分解并研究其中的语义关联问题,从而解读生物学模式作为一种不同于 理化科学的特殊科学解释观的合理性。

关键词: 生物学理论?语义分析?语义结构

As a different type of research in the philosophy of science, biological theory has always attracted scholarly attention. One reason for this phenomenon is that it differs from the traditional scientific paradigm. To explore the root of this difference, we need to examine closely the theoretical foundations and structure of biology. The complexity of the multiple contexts and semantic structures expressed in the theoretical structure specific to biology requires that research on the theoretical foundation of biology incorporate semantic analysis. It is particularly necessary to conduct semantic decomposition of the theories themselves and study their semantic correlations. In doing so, we can discern the rationality of the biological model as a special form of scientific explanation distinct from that of physics and chemistry.     

Theoretical Foundations for Digital Text Analysis

Much of social life now takes place online, and records of online social interactions are available for social science research in the form of massive digital text archives. But cultural social science has contributed little to the development of machine‐assisted text analysis methods. As a result few text analysis methods have been developed that link digital text data to theories about culture and discourse. This paper attempts to lay the groundwork for development of such methods by proposing metatheoretical and theoretical foundations suitable for machine‐assisted semantic text analysis. Metatheoretically I draw on the work of Elder‐Vass (2012), Kaidesoja (2013) and others to argue that digital text analysis methods ought to be (and in practice implicitly are) based on a realist constructionist ontology that treats discourses as ontologically real emergent social entities that have causal relationships with non‐discursive social and cognitive processes. Theoretically I follow Feldman (2006) and many others in arguing that language is fundamentally shaped by processes of embodied cognition. Researchers developing digital text analysis techniques must theoretically account for such processes if they wish to produce algorithms that can interpret texts in ways that supplement, and not only amplify, human interpretation. I critically survey contemporary text analysis methods that implicitly share these metatheoretical and theoretical positions and discuss some ways these can be further developed with newly available software.     

Amos Tversky and the Ascent of Behavioral Economics

Amos Tversky investigated and explained a wide range of phenomena that lead to anomalous human decisions. His two most significant contributions, both written with Daniel Kahneman, are the decision-making heuristics—representativeness, availability, and anchoring—and prospect theory. Tversky's concepts have broadly influenced the social sciences. In economics, they gave rise to the burgeoning field of behavioral economics. This field, skeptical of perfect rationality, emphasizes validation of modeling assumptions, integration of micro-level data on decisions (including experimental evidence), and adoption of lessons from psychology. Tversky's contributions are reviewed, assessed using citation analysis, and placed in historical context. Fertile areas for behavioral economics research are identified.     

Asymmetries in Information Processing in a Decision Theory Framework

Research in psychology suggests that some individuals are more sensitive to positive than to negative information while others are more sensitive to negative rather than positive information. I take these cognitive positive–negative asymmetries in information processing to a Bayesian decision-theory model and explore its consequences in terms of decisions and payoffs. I show that in monotone decision problems economic agents with more positive-responsive information structures are always better off, ex ante, when they face problems where payoffs are relatively more sensitive to the action chosen when the state of nature is favorable.      

Prospect theory for continuous distributions

We extend the original form of prospect theory by Kahneman and Tversky from finite lotteries to arbitrary probability distributions, using an approximation method based on weak-⋆ convergence. The resulting formula is computationally easier than the corresponding formula for cumulative prospect theory and makes it possible to use prospect theory in future applications in economics and finance. Moreover, we suggest a method how to incorporate a crucial step of the “editing phase” into prospect theory and to remove in this way the discontinuity of the original model.

De Finetti was Right: Probability Does Not Exist

De Finetti's treatise on the theory of probability begins with the provocative statement PROBABILITY DOES NOT EXIST, meaning that probability does not exist in an objective sense. Rather, probability exists only subjectively within the minds of individuals. De Finetti defined subjective probabilities in terms of the rates at which individuals are willing to bet money on events, even though, in principle, such betting rates could depend on state-dependent marginal utility for money as well as on beliefs. Most later authors, from Savage onward, have attempted to disentangle beliefs from values by introducing hypothetical bets whose payoffs are abstract consequences that are assumed to have state-independent utility. In this paper, I argue that de Finetti was right all along: PROBABILITY, considered as a numerical measure of pure belief uncontaminated by attitudes toward money, does not exist. Rather, what exist are de Finetti's `previsions', or betting rates for money, otherwise known in the literature as `risk neutral probabilities'. But the fact that previsions are not measures of pure belief turns out not to be problematic for statistical inference, decision analysis, or economic modeling. This revised version was published online in June 2006 with corrections to the Cover Date.     

Is Probability Weighting Sensitive to the Magnitude of Consequences? An Experimental Investigation on Losses

Experimental investigations of the probability weighting function over losses are scarce and all involve small payoffs. The paper aims to give new insight into the probability weighting function for losses, by eliciting it through a simple two-stage semi-parametric procedure over more realistic losses, and by investigating its sensitivity to the magnitude of the payoffs. Current data confirm previous evidence of convex utility functions and inverse-S-shaped weighting functions. Still, at least for small probabilities, probability weighting appears to be affected by the size of consequences: the larger the losses, the more aversive the gambles and the more pessimistic the subjects are.     

Does television terrify tourists? Effects of US television news on demand for tourism in Israel

We analyze the impact on US tourist flows to Israel of variations in both the actual intensity of the Israeli-Palestinian conflict and the intensity implicit in US television news coverage. Conditional on actual events, changes in reported conflict intensity could influence tourists because alternative sources of information are costly; this explanation is consistent with a rational choice model. However, television news could influence tourist behavior because of its emotional impact, or because it causes the conflict to be brought to mind more readily, increasing the subjective probability of conflict events. We find that tourists respond to variations in actual Israeli casualties and reported Palestinian casualties; both effects are large. Reports of Israeli casualties and unreported Palestinian casualties have no significant impact on tourist flows. These asymmetries are consistent with asymmetric information costs within a rational choice framework, but are more difficult to square with the alternative explanations for media influence.

Interpersonal dependency of preferences

Standard decision theoretic models disregard the phenomenon of interpersonal dependency of preferences. In this paper it is argued that interpersonal dependency of preferences is a serious challenge for standard utility theory. First we sketch the more philosophical aspects of the problem and then, using a simple, formal model for the two-person case, we show that interpersonal dependency of preferences generally results in indeterminacy of preferences (resp. of subjective utility).     

The Causal Impact of Resistance: Mediating between Resistance and Internal Conversation about Resistance

Current literature on resistance focuses on the elements of action and opposition as its main components. However, when we use the term resistance we are not necessarily referring exclusively to the active expression of opposition, but could also be referring to discussions about such events or to stimuli that may cause these acts. Thus resistance, for the purposes of this study, is perceived in terms of action, external conversation and stimuli, and it is argued that these external characteristics may be further processed through deliberation and internal conversations about resistance. An exploratory empirical study revealed inner aspects of resistance, and examined whether internal conversations about resistance could actually be experienced by agents. This article further supports the argument that, as individuals produce internal conversations about resistance, they may end by following one of the suggested options: they may keep their internal conversations unspoken, or produce a course of action related to resistance (and identified as such), or they may produce external conversations about resistance, or they may end by producing resistance that is not recognisable (to others) as such. In all these cases, internal conversations about resistance are involved and it is therefore argued that the causal impact of resistance may derive from agential processes and powers as well as from action, stimuli or external conversations related to resistance.     

The geometry of legal principles

We discuss several possible legal principles from the standpoint of Bayesian decision theory. In particular, we show that a compelling legal principle implies compatibility with decisions based on maximizing the expected utility.     

Better May be Worse: Some Monotonicity Results and Paradoxes in Discrete Choice Under Uncertainty

It is not unusual in real-life that one has to choose among finitely many alternatives when the merit of each alternative is not perfectly known. Instead of observing the actual utilities of the alternatives at hand, one typically observes more or less precise signals that are positively correlated with these utilities. In addition, the decision-maker may, at some cost or disutility of effort, choose to increase the precision of these signals, for example by way of a careful study or the hiring of expertise. We here develop a model of such decision problems. We begin by showing that a version of the monotone likelihood-ratio property is sufficient, and also essentially necessary, for the optimality of the heuristic decision rule to always choose the alternative with the highest signal. Second, we show that it is not always advantageous to face alternatives with higher utilities, a non-monotonicity result that holds even if the decision-maker optimally chooses the signal precision. We finally establish an operational first-order condition for the optimal precision level in a canonical class of decision-problems, and we show that the optimal precision level may be discontinuous in the precision cost.     

The undecidability of the spatialized prisoner's dilemma

In the spatialized Prisoner's Dilemma, players compete against their immediate neighbors and adopt a neighbor's strategy should it prove locally superior. Fields of strategies evolve in the manner of cellular automata (Nowak and May, 1993; Mar and St. Denis, 1993a,b; Grim 1995, 1996). Often a question arises as to what the eventual outcome of an initial spatial configuration of strategies will be: Will a single strategy prove triumphant in the sense of progressively conquering more and more territory without opposition, or will an equilibrium of some small number of strategies emerge? Here it is shown, for finite configurations of Prisoner's Dilemma strategies embedded in a given infinite background, that such questions are formally undecidable: there is no algorithm or effective procedure which, given a specification of a finite configuration, will in all cases tell us whether that configuration will or will not result in progressive conquest by a single strategy when embedded in the given field. The proof introduces undecidability into decision theory in three steps: by (1) outlining a class of abstract machines with familiar undecidability results, by (2) modelling these machines within a particular family of cellular automata, carrying over undecidability results for these, and finally by (3) showing that spatial configurations of Prisoner's Dilemma strategies will take the form of such cellular automata.