School pupils' perceptions of the police that visit schools: Not all police are ‘pigs’

This paper presents data concerning young people's perceptions of the police taking part in a police—schools liaison programme. Eighty-one 14-year-old school pupils took part in 28 semi-structured group discussions concerning their perceptions of the ‘typicality’ of police officers working in their schools. Pupils clearly differentiated between these and those ‘on the street’. Central to this differentiation was the issue of police power; the perceived atypicality of the police in schools was intimately bound up with pupils' perceptions of the qualitatively different social relations that obtain between young people and the police ‘in the school’ and ‘on the street’. The implications of these data for the literatures concerning the ‘contact hypothesis’ and police—schools liaison are discussed.     

The envious will to power

Envy, from Klein's perspective, is an inherent hatred of goodness that seeks to destroy love, creativity, and life itself. Devoid of constructive value, envy becomes an evil to be restrained or renounced, rather than a potential to be understood or developed. Confusion with evil can be avoided if envy is seen as a defence against the impact of 'otherness' and the greatness of 'others' rather than an inherent hatred of goodness. From this perspective envy emerges as a desperate attempt to preserve one's unique sense of self against the terror of non-being.     

The case against Allen's generalization of the matching law

Allen (1981) claims to have established the formal validity of a power-function generalization of the matching law. This paper argues that Allen's proof is not correct when schedules are presented in pairs and that his initial assumptions are too restrictive when all schedules are simultaneously available.     

Argument Quality and Cultural Difference

Central to argumentation theory is a concern with normativity. Argumentation theorists are concerned, among other things, with explaining why some arguments are good (or at least better than others) in the sense that a given argument provides reasons for embracing its conclusion which are such that a fair- minded appraisal of the argument yields the judgment that the conclusion ought to be accepted -- is worthy of acceptance -- by all who so appraise it.This conception of argument quality presupposes that the goodness of arguments is characterizable in terms of features of the argument itself. It makes no reference either to the attributes of the persons appraising the argument and judging its normative force, or to the context in which that appraisal is carried out. But recent work by a wide range of philosophers, argumentation theorists, and social theorists rejects such an abstract, impersonal notion of argument goodness. Instead, these theorists insist upon taking seriously, in the evaluation of arguments, the features of the evaluators themselves. In particular, such theorists emphasize the importance of cultural difference in argument appraisal. Often locating themselves under the banner of multiculturalism, they argue that the quality of an argument depends upon culturally-specific beliefs, values, and presuppositions; that an argument may be of high quality in one cultural context but of low quality in another. Consequently, they contend, no abstract, impersonal characterization of argument quality can succeed.In this paper I consider this multiculturalist approach to argument quality. I argue that while there is much merit in the general multiculturalist perspective, the multiculturalist argument against impersonal conceptions of argument quality fails. It fails for several reasons detailed below; most fundamentally, it fails because it itself presupposes just the kind of impersonal account of argument quality it seeks to reject. I call this presupposition that of transcultural normative reach. I identify this presupposition in the multiculturalist argument, and show how it undercuts the multiculturalist challenge to abstract, impersonal, transcultural conceptions of argument quality. I conclude with an evaluation of the strengths, and weaknesses, of the multiculturalist challenge to such conceptions of argument quality.     

Exploitation via labour power in Marx

Marx's account of capitalist exploitation is undermined by inter-related confusions surrounding the notion of labour power. These confusions relate to [i] what labour power is, [ii] what happens to labour power in the labour market, and [iii] what the epistemic status of labour power is (the issue of appearance and reality). The central theses of the paper are [a] that property ownership is the wrong model for understanding the exploitation of labour, and [b] that the concept of exploitation is linked more fruitfully to a conception of distributive injustice than to Marx's theory of surplus value.     

Monotonic weighted power transformations to additivity

A class of monotonic transformations which generalize the power transformation is fit to the independent and dependent variables in multiple regression so that the resulting additive relationship is optimized. This is achieved by minimizing a quadratic fitting criterion with linear inequality constraints on the parameters. A quadratic programming technique which works reliably and quickly in this application is outlined. Some examples of the analysis of artificial and real data are offered.This work was supported by National Research Council of Canada Grant APA 320 to the author.     

Gapping

Tukey's scheme for finding separations in univariate data strings is described and tested. It is found that one can use the size of a data gap coupled with its ordinal position in the distribution to determine the likelihood of its having arisen by chance. It was also shown that this scheme is relatively robust for fatter-tailed-than-Gaussian distributions and has some interesting implications in multidimensional situations.     

Comparing Computational Power

It is common practice to compare the computational power ofdifferent models of computation. For example, the recursivefunctions are strictly more powerful than the primitive recursivefunctions, because the latter are a proper subset of the former(which includes Ackermann's function). Side-by-side with this"containment" method of measuring power, it is also standardto base comparisons on "simulation". For example, one says thatthe (untyped) lambda calculus is as powerful—computationallyspeaking—as the partial recursive functions, because thelambda calculus can simulate all partial recursive functionsby encoding the natural numbers as Church numerals. The problem is that unbridled use of these two distinct waysof comparing power allows one to show that some computationalmodels (sets of partial functions) are strictly stronger thanthemselves! We argue that a better definition is that modelA is strictly stronger than B if A can simulate B via some encoding,whereas B cannot simulate A under any encoding. We show thatwith this definition, too, the recursive functions are strictlystronger than the primitive recursive. We also prove that therecursive functions, partial recursive functions, and Turingmachines are "complete", in the sense that no injective encodingcan make them equivalent to any "hypercomputational" model.¹     

A model-based approach to multivariate principal component regression: Selecting principal components and estimating standard errors for unstandardized regression coefficients

Principal component regression (PCR) is a popular technique in data analysis and machine learning. However, the technique has two limitations. First, the principal components (PCs) with the largest variances may not be relevant to the outcome variables. Second, the lack of standard error estimates for the unstandardized regression coefficients makes it hard to interpret the results. To address these two limitations, we propose a model-based approach that includes two mean and covariance structure models defined for multivariate PCR. By estimating the defined models, we can obtain inferential information that will allow us to test the explanatory power of individual PCs and compute the standard error estimates for the unstandardized regression coefficients. A real example is used to illustrate our approach, and simulation studies under normality and nonnormality conditions are presented to validate the standard error estimates for the unstandardized regression coefficients. Finally, future research topics are discussed.     

Prenatal maternal depression predicts neural maturation and negative emotion in infants

Despite widespread acceptance that prenatal symptoms of depression in mothers are detrimental to infants’ long-term emotional and cognitive development, little is known about the mechanisms that may integrate outcomes across these domains. Rooted in the integrative perspective that emotional development is grounded in developing cognitive processes, we hypothesized that prenatal symptoms of depression in mothers would be associated with delays in neural maturation that support sociocognitive function in infants, leading to more problematic behaviors. We used a prospective longitudinal study of mothers (N = 92) and their infants to test whether self-reported symptoms of depression in mothers during the second and third trimesters were associated with neural development and infant outcomes at 4 months of age. While controlling for postpartum symptoms of depression, more prenatal symptoms of depression in mothers predicted less neural maturation in the parietal region of 4-month-old infants. Less neural maturation, in turn, was associated with greater infant negativity, suggesting neural maturation as a putative mechanism linking maternal symptoms of depression with infant outcomes. Differences in neural regions and developmental timing are also discussed.