In Search of Convergence: A Co-citation Analysis of Three Sport Management Journals

Responding to a series of articles in sport management literature calling for more diversity in terms of areas of interest or methods, this study warns against the danger of excessively fragmenting this field of research. The works of Kuhn (1962) and Pfeffer (1993) are taken as the basis of an argument that connects convergence with scientific strength. However, being aware of the large number of counterarguments directed at this line of reasoning, a new model of convergence, which focuses on clusters of research contributions with similar areas of interest, methods, and concepts, is proposed. The existence of these clusters is determined with the help of a bibliometric analysis of publications in three sport management journals. This examination determines that there are justified reasons to be concerned about the level of convergence in the field, pointing out to a reduced ability to create large clusters of contributions in similar areas of interest.

'To do justice and judgement' : the place of passion in public life

Please consult the paper edition of this thesis to read. It is available on the 5th Floor of the Library at Call Number: Z 9999 P65 F47 2003

Sofia Gubaidulina's violin concerto Offertorium : theology and music in dialogue

L’objectif de ce mémoire est de comprendre comment une certaine vision du monde, basée sur des croyances théologiques, a contribué à la composition du concerto pour violon Offertorium de Sofia Gubaïdulina. C’est par le biais de cette œuvre qu’est explorée l’idée du dialogue musicothéologique, en proposant des façons par lesquelles la pièce musicale en question peut servir de porteuse ou d’interprète d’une pensée théologique. Afin d’appuyer cette idée, la démarche intertextuelle employée par Heidi Epstein est utilisée. Cette méthode permet de faciliter non seulement le travail interdisciplinaire, mais aussi la lecture théologique de l’œuvre musicale. Le premier chapitre explore les sources, les questions et la problématique qui entoure le dialogue musicothéologique. La conclusion tirée est que l’étude d’Offertorium nécessite une approche équilibrée. Nous entendons par cela, une approche qui prend en ligne de compte la réflexion théologique autant que la recherche musicologique tout en respectant les contributions théologiques que l’œuvre musicale peut apporter en soi. Dans le deuxième chapitre, une analyse thématique d’Offertorium a été tentée ainsi qu’une étude du discours théologique et spirituel de la compositrice. Il a été conclu que l’arrière-plan russe orthodoxe de Gubaidulina a beaucoup influencé sa vision du monde et son approche artistique. Le concerto est porteur d’idées et de symboles liturgiques ou théologiques de l’Orthodoxie dans sa structure et dans sa construction thématique. Le troisième chapitre explore les parallèles entre la pensée de Gubaidulina et les écritures de plusieurs théologiens russes orthodoxes du 20e siècle. La conclusion de ce chapitre démontre que, même s’il est improbable que la compositrice connaisse bien ces auteurs, sa compréhension théologique et spirituelle sort du climat religieux de l’Église Orthodoxe. Cette idée explique les complémentarités et les similarités entre son discours, son œuvre et les propos des théologiens discutés. Le quatrième chapitre évalue la validité d’Offertorium comme moyen d’expression théologique ainsi que de générateur de réflexion théologique. La conclusion de la recherche est qu’Offertorium peut bel et bien être un espace théologique. Ce qui veut dire que des idées théologiques peuvent être communiquées par le biais de l’expérience sonore que ce soit par la mélodie ou l’ambiance générale. Également, cela implique que la musique devient un partenaire égal, quoique différent des méthodes de réflexion traditionnelles au sein de la conversation théologique.

"The fertility transition in Kenya : patterns and determinants"

Thèse diffusée initialement dans le cadre d'un projet pilote des Presses de l'Université de Montréal/Centre d'édition numérique UdeM (1997-2008) avec l'autorisation de l'auteur.

Improving sampling, optimization and feature extraction in Boltzmann machines

L’apprentissage supervisé de réseaux hiérarchiques à grande échelle connaît présentement un succès fulgurant. Malgré cette effervescence, l’apprentissage non-supervisé représente toujours, selon plusieurs chercheurs, un élément clé de l’Intelligence Artificielle, où les agents doivent apprendre à partir d’un nombre potentiellement limité de données. Cette thèse s’inscrit dans cette pensée et aborde divers sujets de recherche liés au problème d’estimation de densité par l’entremise des machines de Boltzmann (BM), modèles graphiques probabilistes au coeur de l’apprentissage profond. Nos contributions touchent les domaines de l’échantillonnage, l’estimation de fonctions de partition, l’optimisation ainsi que l’apprentissage de représentations invariantes. Cette thèse débute par l’exposition d’un nouvel algorithme d'échantillonnage adaptatif, qui ajuste (de fa ̧con automatique) la température des chaînes de Markov sous simulation, afin de maintenir une vitesse de convergence élevée tout au long de l’apprentissage. Lorsqu’utilisé dans le contexte de l’apprentissage par maximum de vraisemblance stochastique (SML), notre algorithme engendre une robustesse accrue face à la sélection du taux d’apprentissage, ainsi qu’une meilleure vitesse de convergence. Nos résultats sont présent ́es dans le domaine des BMs, mais la méthode est générale et applicable à l’apprentissage de tout modèle probabiliste exploitant l’échantillonnage par chaînes de Markov. Tandis que le gradient du maximum de vraisemblance peut-être approximé par échantillonnage, l’évaluation de la log-vraisemblance nécessite un estimé de la fonction de partition. Contrairement aux approches traditionnelles qui considèrent un modèle donné comme une boîte noire, nous proposons plutôt d’exploiter la dynamique de l’apprentissage en estimant les changements successifs de log-partition encourus à chaque mise à jour des paramètres. Le problème d’estimation est reformulé comme un problème d’inf��rence similaire au filtre de Kalman, mais sur un graphe bi-dimensionnel, où les dimensions correspondent aux axes du temps et au paramètre de température. Sur le thème de l’optimisation, nous présentons également un algorithme permettant d’appliquer, de manière efficace, le gradient naturel à des machines de Boltzmann comportant des milliers d’unités. Jusqu’à présent, son adoption était limitée par son haut coût computationel ainsi que sa demande en mémoire. Notre algorithme, Metric-Free Natural Gradient (MFNG), permet d’éviter le calcul explicite de la matrice d’information de Fisher (et son inverse) en exploitant un solveur linéaire combiné à un produit matrice-vecteur efficace. L’algorithme est prometteur: en terme du nombre d’évaluations de fonctions, MFNG converge plus rapidement que SML. Son implémentation demeure malheureusement inefficace en temps de calcul. Ces travaux explorent également les mécanismes sous-jacents à l’apprentissage de représentations invariantes. À cette fin, nous utilisons la famille de machines de Boltzmann restreintes “spike & slab” (ssRBM), que nous modifions afin de pouvoir modéliser des distributions binaires et parcimonieuses. Les variables latentes binaires de la ssRBM peuvent être rendues invariantes à un sous-espace vectoriel, en associant à chacune d’elles, un vecteur de variables latentes continues (dénommées “slabs”). Ceci se traduit par une invariance accrue au niveau de la représentation et un meilleur taux de classification lorsque peu de données étiquetées sont disponibles. Nous terminons cette thèse sur un sujet ambitieux: l’apprentissage de représentations pouvant séparer les facteurs de variations présents dans le signal d’entrée. Nous proposons une solution à base de ssRBM bilinéaire (avec deux groupes de facteurs latents) et formulons le problème comme l’un de “pooling” dans des sous-espaces vectoriels complémentaires.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Two complementary molecular energy decomposition schemes: the Mayer and Ziegler-Rauk methods in comparison

In the present paper we discuss and compare two different energy decomposition schemes: Mayer's Hartree-Fock energy decomposition into diatomic and monoatomic contributions [Chem. Phys. Lett. 382, 265 (2003)], and the Ziegler-Rauk dissociation energy decomposition [Inorg. Chem. 18, 1558 (1979)]. The Ziegler-Rauk scheme is based on a separation of a molecule into fragments, while Mayer's scheme can be used in the cases where a fragmentation of the system in clearly separable parts is not possible. In the Mayer scheme, the density of a free atom is deformed to give the one-atom Mulliken density that subsequently interacts to give rise to the diatomic interaction energy. We give a detailed analysis of the diatomic energy contributions in the Mayer scheme and a close look onto the one-atom Mulliken densities. The Mulliken density ρA has a single large maximum around the nuclear position of the atom A, but exhibits slightly negative values in the vicinity of neighboring atoms. The main connecting point between both analysis schemes is the electrostatic energy. Both decomposition schemes utilize the same electrostatic energy expression, but differ in how fragment densities are defined. In the Mayer scheme, the electrostatic component originates from the interaction of the Mulliken densities, while in the Ziegler-Rauk scheme, the undisturbed fragment densities interact. The values of the electrostatic energy resulting from the two schemes differ significantly but typically have the same order of magnitude. Both methods are useful and complementary since Mayer's decomposition focuses on the energy of the finally formed molecule, whereas the Ziegler-Rauk scheme describes the bond formation starting from undeformed fragment densities

Transnationalism personified: young returning Trinidadians 'in their own words'

In this paper we consider the nexus existing between returning transnational migrants to Trinidad and Tobago's adaptation experiences, matters pertaining to their transnational life-paths, family and community experiences and their views on transnationalism and return. The research is based on an analysis of the detailed narratives provided by forty informants by means of semi-structured interviews. The informants consisted of nine 'second-generation', seven 'one-and-a-half-generation' and twenty-four 'prolonged sojourner' returning transnational migrants to Trinidad and Tobago. The main conceptual themes that characterise Caribbean transnationalism are presented at the beginning of the paper. Addressing these in the context of Trinidad and Tobago, we present our narrative-based findings under the following headings derived from analysis of our informant's experiences and views: transnational family and life-course issues; transnational community relationships; keeping in touch; transnational mobility and 'home as fixed anchor'; transnational identity; transnational economic and commercial interests; and strategic flexibility.

"Racism in a Melting Pot...?" Trinidadian mid-life transnational migrants' views on race and colour-class on return to their homes of descent

This paper deals with second-generation, one-and-a-half generation and ‘‘prolonged sojourner” Trinidadian transnational migrants, who have decided to ‘return’ to the birthplace of their parents. Based on 40 in-depth interviews, the paper considers both the positive and critical things that these youthful transnational migrants report about returning to, and living in, this multi-ethnic plural society and the salience of racial and colour-class stratification as part of their return migration experiences. Our qualitative analysis is based on the narratives provided by these youthful returnees, as relayed ‘‘in their own words”, presenting critical reflections on racism, racial identities and experiences as transnational Trinidadians. It is clear that it is contexts such as contemporary working environments, family and community that act as the reference points for the adaptation ‘‘back home” of this strongly middle-class cohort. We accordingly encounter a diverse, sometimes contesting set of racial issues that emerge as salient concerns for these returnees. The consensus is that matters racial remain as formidable legacies in the hierarchical stratification of Trinidadian society for a sizeable number. Many of our respondents reported the positive aspects of racial affirmation on return. But for another sub-set, the fact that multi-ethnic and multi-cultural mixing are proudly embraced in Trinidad meant that it was felt that return experiences were not overly hindered, or blighted by obstacles of race and colour-class. For these returnees, Trinidad and Tobago is seen as representing a 21st century ‘‘Melting Pot”. But for others the continued existence of racial divisions within society – between ethnic groups and among those of different skin shades – was lamented. In the views of these respondents, too much racial power is still ascribed to ‘near-whiteness’. But for the most part, the returnees felt that where race played a part in their new lives, this generally served to advantage them. However, although the situation in Trinidad appears to have been moderated by assumptions that it remains a racial ‘Melting Pot’, the analysis strongly suggests that the colour-class system of stratification is still playing an essential role, along with racial stereotyping in society at large.

An assessment of observed vertical flux divergence in long-term eddy-covariance measurements over two Midwestern forest ecosystems

Vertical divergence of CO2 fluxes is observed over two Midwestern AmeriFlux forest sites. The differences in ensemble averaged hourly CO2 fluxes measured at two heights above canopy are relatively small (0.2–0.5 μmol m−2 s−1), but they are the major contributors to differences (76–256 g C m−2 or 41.8–50.6%) in estimated annual net ecosystem exchange (NEE) in 2001. A friction velocity criterion is used in these estimates but mean flow advection is not accounted for. This study examines the effects of coordinate rotation, averaging time period, sampling frequency and co-spectral correction on CO2 fluxes measured at a single height, and on vertical flux differences measured between two heights. Both the offset in measured vertical velocity and the downflow/upflow caused by supporting tower structures in upwind directions lead to systematic over- or under-estimates of fluxes measured at a single height. An offset of 1 cm s−1 and an upflow/downflow of 1° lead to 1% and 5.6% differences in momentum fluxes and nighttime sensible heat and CO2 fluxes, respectively, but only 0.5% and 2.8% differences in daytime sensible heat and CO2 fluxes. The sign and magnitude of both offset and upflow/downflow angle vary between sonic anemometers at two measurement heights. This introduces a systematic and large bias in vertical flux differences if these effects are not corrected in the coordinate rotation. A 1 h averaging time period is shown to be appropriate for the two sites. In the daytime, the absolute magnitudes of co-spectra decrease with height in the natural frequencies of 0.02–0.1 Hz but increase in the lower frequencies (<0.01 Hz). Thus, air motions in these two frequency ranges counteract each other in determining vertical flux differences, whose magnitude and sign vary with averaging time period. At night, co-spectral densities of CO2 are more positive at the higher levels of both sites in the frequency range of 0.03–0.4 Hz and this vertical increase is also shown at most frequencies lower than 0.03 Hz. Differences in co-spectral corrections at the two heights lead to a positive shift in vertical CO2 flux differences throughout the day at both sites. At night, the vertical CO2 flux differences between two measurement heights are 20–30% and 40–60% of co-spectral corrected CO2 fluxes measured at the lower levels of the two sites, respectively. Vertical differences of CO2 flux are relatively small in the daytime. Vertical differences in estimated mean vertical advection of CO2 between the two measurement heights generally do not improve the closure of the 1D (vertical) CO2 budget in the air layer between the two measurement heights. This may imply the significance of horizontal advection. However, a reliable assessment of mean advection contributions in annual NEE estimate at these two AmeriFlux sites is currently an unsolved problem.

How large is congressional dependence in agriculture. Bayesian inference about ‘scale’ and ‘scope’ in measuring a spatial externality

The political economy literature on agriculture emphasizes influence over political outcomes via lobbying conduits in general, political action committee contributions in particular and the pervasive view that political preferences with respect to agricultural issues are inherently geographic. In this context, ‘interdependence’ in Congressional vote behaviour manifests itself in two dimensions. One dimension is the intensity by which neighboring vote propensities influence one another and the second is the geographic extent of voter influence. We estimate these facets of dependence using data on a Congressional vote on the 2001 Farm Bill using routine Markov chain Monte Carlo procedures and Bayesian model averaging, in particular. In so doing, we develop a novel procedure to examine both the reliability and the consequences of different model representations for measuring both the ‘scale’ and the ‘scope’ of spatial (geographic) co-relations in voting behaviour.