An Alternative Solution to Lifting the Ban on Doping: Breaking the Payoff Matrix of Professional Sport by Shifting Liability Away from Athletes

The persistence of doping in professional sports—either by individuals on an isolated basis and by whole teams as part of a systematic doping programme—means that professional sport today is rarely if ever untainted. There are financial incentives in place that incentivise doping and there are data that show that doping is often a systematic, organised enterprise (either at team-level, or at state-level). The main question to be answered today in professional sports is whether doping’s repressive anti-doping policies do not have greater negative consequences for society. Whilst some have suggested legitimising safe doping under medical control, in this paper, I argue that doing so will do little to prevent clandestine use of dangerous performance-enhancing substances, and suggest an alternative solution to lifting the ban on doping, i.e. starting from extending liability for doping in sport beyond athletes to those holding power and authority over athletes, to changing winning incentives for doping, to making sport sustainable in the longer time by devising ways of providing athletes with a steady income which is not linked to record breaking or sponsorships.     

How to get really smart: Modeling retest and training effects in ability testing using computer-generated figural matrix items

The interpretation of retest scores is problematic because they are potentially affected by measurement and predictive bias, which impact construct validity, and because their size differs as a function of various factors. This paper investigates the construct stability of scores on a figural matrices test and models retest effects at the level of the individual test taker as a function of covariates (simple retest vs. training, use of identical vs. parallel retest forms, and general mental ability). A total of N = 189 subjects took two tests of matrix items that were automatically generated according to a strict construction rationale. Between test administrations, participants in the intervention groups received training, while controls did not. The Rasch model fit the data at both time points, but there was a lack of item difficulty parameter invariance across time. Training increased test performance beyond simple retesting, but there was no large difference between the identical and parallel retest forms at the individual level. Individuals varied greatly in how they profited from retest experience, training, and the use of identical vs. parallel retest forms. The results suggest that even with carefully designed tasks, it is problematic to directly compare scores from initial tests and retests. Test administrators should emphasize learning potential instead of state level assessment, and inter-individual differences with regard to test experience should be taken into account when interpreting test results.     

Unconscious phantasy as a structural principle and organizer of mental life: The evolution of a concept from Freud to Klein and some of her successors

Starting with Freud's discovery of unconscious phantasy as a means of accessing his patients’ internal world, the author discusses the evolution of the concept in the work of Melanie Klein and some of her successors. Whereas Freud sees phantasy as a wish fulfilling imagination, dominated by primary process functioning and kept apart from reality testing, Klein understands phantasies as a structural function and organizer of mental life. From their very beginnings they involve object relations and gradually evolve from primitive body‐near experiences to images and symbolic representations. With her concept of projective identification in particular, Klein anticipates the communicative function of unconscious phantasies. They are at the basis of processes of symbolization, but may also be put into the service of complex defensive operations. The author traces the further evolution of the concept from the contributions of S. Isaacs, the theories of thinking proposed by W.R. Bion and R. Money‐Kyrle, Hanna Segal's ideas on symbolization and reparation all the way to the latest approaches by R. Britton, J. Steiner and others, including the understanding of transference and counter‐transference as a ‘total situation’. Points of contact with Freud are to be found particularly in connection with his concept of ‘primal phantasies’. In the author's view, the idea of the transmission and communicative potential of unconscious phantasies enabled these authors to overcome the solipsistic origins of drive theory in favour of a notion in which unconscious phantasies both set down the coordinates of the inner world and form and reflect the matrix of inter‐subjective relations.     

On the Closure Properties of the Class of Full G-models of a Deductive System

In this paper we consider the structure of the class FGModS of full generalized models of a deductive system S from a universal-algebraic point of view, and the structure of the set of all the full generalized models of S on a fixed algebra A from the lattice-theoretical point of view; this set is represented by the lattice FACS_s A of all algebraic closed-set systems C on A such that (A, C) ε FGModS. We relate some properties of these structures with tipically logical properties of the sentential logic S. The main algebraic properties we consider are the closure of FGModS under substructures and under reduced products, and the property that for any A the lattice FACS_s A is a complete sublattice of the lattice of all algebraic closed-set systems over A. The logical properties are the existence of a fully adequate Gentzen system for S, the Local Deduction Theorem and the Deduction Theorem for S. Some of the results are established for arbitrary deductive systems, while some are found to hold only for deductive systems in more restricted classes like the protoalgebraic or the weakly algebraizable ones. The paper ends with a section on examples and counterexamples. Dedicated to the memory of Willem Johannes Blok     

Selfextensional Logics with a Conjunction

A logic is selfextensional if its interderivability (or mutual consequence) relation is a congruence relation on the algebra of formulas. In the paper we characterize the selfextensional logics with a conjunction as the logics that can be defined using the semilattice order induced by the interpretation of the conjunction in the algebras of their algebraic counterpart. Using the charactrization we provide simpler proofs of several results on selfextensional logics with a conjunction obtained in [13] using Gentzen systems. We also obtain some results on Fregean logics with conjunction.This paper is a version of the invited talk at the conference Trends in Logic III, dedicated to the memory of A. MOSTOWSKI, H. RASIOWA and C. RRAUSZER, and held in Warsaw and Ruciane-Nida from 23rd to 25th September 2005.     

Goodness-of-fit and confidence intervals of approximate models

If the model for the data are strictly speaking incorrect, then how can one test whether the model fits? Standard goodness-of-fit (GOF) tests rely on strictly correct or incorrect models. But in practice the correct model is not assumed to be available. It would still be of interest to determine how good or how bad the approximation is. But how can this be achieved? If it is determined that a model is a good approximation and hence a good explanation of the data, how can reliable confidence intervals be constructed? In this paper, an attempt is made to answer the above questions. Several GOF tests and methods of constructing confidence intervals are evaluated both in a simulation and with real data from the internet-based daily news memory test.     

Nonparametric Estimation of Standard Errors in Covariance Analysis Using the Infinitesimal Jackknife

The infinitesimal jackknife provides a simple general method for estimating standard errors in covariance structure analysis. Beyond its simplicity and generality what makes the infinitesimal jackknife method attractive is that essentially no assumptions are required to produce consistent standard error estimates, not even the requirement that the population sampled has the covariance structure assumed. Commonly used covariance structure analysis software uses parametric methods for estimating parameters and standard errors. When the population sampled has the covariance structure assumed, but fails to have the distributional form assumed, the parameter estimates usually remain consistent, but the standard error estimates do not. This has motivated the introduction of a variety of nonparametric standard error estimates that are consistent when the population sampled fails to have the distributional form assumed. The only distributional assumption these require is that the covariance structure be correctly specified. As noted, even this assumption is not required for the infinitesimal jackknife. The relation between the infinitesimal jackknife and other nonparametric standard error estimators is discussed. An advantage of the infinitesimal jackknife over the jackknife and the bootstrap is that it requires only one analysis to produce standard error estimates rather than one for every jackknife or bootstrap sample.     

Heuristic Implementation of Dynamic Programming for Matrix Permutation Problems in Combinatorial Data Analysis

Dynamic programming methods for matrix permutation problems in combinatorial data analysis can produce globally-optimal solutions for matrices up to size 30×30, but are computationally infeasible for larger matrices because of enormous computer memory requirements. Branch-and-bound methods also guarantee globally-optimal solutions, but computation time considerations generally limit their applicability to matrix sizes no greater than 35×35. Accordingly, a variety of heuristic methods have been proposed for larger matrices, including iterative quadratic assignment, tabu search, simulated annealing, and variable neighborhood search. Although these heuristics can produce exceptional results, they are prone to converge to local optima where the permutation is difficult to dislodge via traditional neighborhood moves (e.g., pairwise interchanges, object-block relocations, object-block reversals, etc.). We show that a heuristic implementation of dynamic programming yields an efficient procedure for escaping local optima. Specifically, we propose applying dynamic programming to reasonably-sized subsequences of consecutive objects in the locally-optimal permutation, identified by simulated annealing, to further improve the value of the objective function. Experimental results are provided for three classic matrix permutation problems in the combinatorial data analysis literature: (a) maximizing a dominance index for an asymmetric proximity matrix; (b) least-squares unidimensional scaling of a symmetric dissimilarity matrix; and (c) approximating an anti-Robinson structure for a symmetric dissimilarity matrix. We are extremely grateful to the Associate Editor and two anonymous reviewers for helpful suggestions and corrections.     

认知诊断评价中测验结构的优化设计

Q矩阵是认知诊断评价的基础和核心要素, 它反映了测验的构念和内容设计, 直接影响着测验诊断分类的效果。本文采用Monte Carlo模拟, 研究了6种属性层级关系下, 不同的Q矩阵设计对于认知诊断效果的影响。用模式判准率的均值和标准差分别从分类准确性和稳定性的角度来评价诊断效果。实验结果表明：(1) 不同属性层级关系下, 分类准确性会随着测验长度的增加而提高, 但当测验长度增加到一定程度时, 会出现“天花板效应”; (2) Q矩阵中R*的个数(NR*)会影响测验的分类准确性及稳定性：NR*越大, 测验的分类稳定性越高, 当测验长度为属性个数的整数倍, 且NR*为测验长度相对属性个数的最大奇数倍时分类准确性最高; (3) Q矩阵中除R*以外的项目考察的属性个数会随着属性层级关系的不同对测验的分类准确性和稳定性产生不同的影响。根据实验结果, 本研究提出了进行诊断评价时Q矩阵优化设计的一些建议。     

多级评分聚类诊断法的影响因素

从测验和被试两个层面探讨了属性数目、属性层级关系、被试知识状态分布、属性层级误设和Q矩阵误设等因素对GRCDM的影响, 以进一步考察GRCDM的特性。研究发现：(1)GRCDM对属性数目无依赖, 随属性数目的增多判准率反而增高; (2)被试知识状态分布对GRCDM判准率高低无影响; (3)属性层级误设对GRCDM的影响与属性层级类型有关, 当属性层级为无结构型和发散型时, “属性层级关系错乱”的判准率降幅最大; (4)Q矩阵误设对GRCDM的影响因层级关系而异, 收敛型和发散型受影响较小, 无结构型和线型的判准率在属性既冗余又缺失时降幅最大。