Le leadership authentique : validation d’une mesure et étude de ses effets sur le climat de travail et le bien-être des personnes

La santé au travail a été reconnue comme un élément important du développement économique mondial à long terme. Cependant, les projections statistiques laissent poindre des préoccupations sur deux plans : la main d’œuvre vieillit et leur bien-être psychologique se détériore. Pour pallier ses problématiques, des leaders forts sont recherchés pour cultiver des climats de confiance de même que veiller au bien-être de leurs collaborateurs. Cette thèse a pour objet d’étudier les liens entre le leadership authentique (LA), le climat de travail et le bien-être des personnes. Pour y parvenir, deux recherches ont été réalisées. La première étude visait à se doter d’un instrument de mesure de LA en français. Le « Authentic Leadership Questionnaire » a été traduit et validé. Les résultats des analyses factorielles confirmatoires effectuées sur deux échantillons de travailleurs québécois (N = 365, N = 859) ont montré que c’est une structure de deuxième ordre avec les quatre facteurs associés au LA qui offre le meilleur ajustement aux données. Le LA a ensuite été mis en lien avec des corrélats (authenticité du leader, bien-être psychologique du leader, bien-être psychologique des subordonnés, confiance et justice interpersonnelle). Toutes les hypothèses ont été soutenues à l’exception d’une, soit celle liant le LA autorapporté par le leader et son bien-être psychologique. La deuxième étude a testé un modèle de médiation où le climat de travail a été postulé comme médiateur de la relation entre le LA et le bien-être des travailleurs. Un devis non expérimental avec six mois entre les passations a été utilisé. Quatre cent six (406) infirmières et infirmiers ont rempli des questionnaires mesurant le LA et le climat perçus au travail, et six mois plus tard, une mesure de bien-être psychologique au travail. Les résultats découlant d’une analyse de médiation par la technique de « boostrapping » ont révélé que le LA est associé au bien-être des subordonnés par l’entremise d’un climat de travail positif qu’il contribue à favoriser. Au terme de cette recherche doctorale, on commente les résultats, expose les principaux apports, présente des retombées pratiques, discute des limites et propose des pistes de recherche future.

A pilot investigation of the relationship between climate variability and milk compounds under the bootstrap technique

This study analyzes the linear relationship between climate variables and milk components in Iran by applying bootstrapping to include and assess the uncertainty. The climate parameters, Temperature Humidity Index (THI) and Equivalent Temperature Index (ETI) are computed from the NASA-Modern Era Retrospective-Analysis for Research and Applications (NASA-MERRA) reanalysis (2002–2010). Milk data for fat, protein (measured on fresh matter bases), and milk yield are taken from 936,227 milk records for the same period, using cows fed by natural pasture from April to September. Confidence intervals for the regression model are calculated using the bootstrap technique. This method is applied to the original times series, generating statistically equivalent surrogate samples. As a result, despite the short time data and the related uncertainties, an interesting behavior of the relationships between milk compound and the climate parameters is visible. During spring only, a weak dependency of milk yield and climate variations is obvious, while fat and protein concentrations show reasonable correlations. In summer, milk yield shows a similar level of relationship with ETI, but not with temperature and THI. We suggest this methodology for studies in the field of the impacts of climate change and agriculture, also environment and food with short-term data.

Using Analogy to Acquire Commonsense Knowledge from Human Contributors

The goal of the work reported here is to capture the commonsense knowledge of non-expert human contributors. Achieving this goal will enable more intelligent human-computer interfaces and pave the way for computers to reason about our world. In the domain of natural language processing, it will provide the world knowledge much needed for semantic processing of natural language. To acquire knowledge from contributors not trained in knowledge engineering, I take the following four steps: (i) develop a knowledge representation (KR) model for simple assertions in natural language, (ii) introduce cumulative analogy, a class of nearest-neighbor based analogical reasoning algorithms over this representation, (iii) argue that cumulative analogy is well suited for knowledge acquisition (KA) based on a theoretical analysis of effectiveness of KA with this approach, and (iv) test the KR model and the effectiveness of the cumulative analogy algorithms empirically. To investigate effectiveness of cumulative analogy for KA empirically, Learner, an open source system for KA by cumulative analogy has been implemented, deployed, and evaluated. (The site "1001 Questions," is available at http://teach-computers.org/learner.html). Learner acquires assertion-level knowledge by constructing shallow semantic analogies between a KA topic and its nearest neighbors and posing these analogies as natural language questions to human contributors. Suppose, for example, that based on the knowledge about "newspapers" already present in the knowledge base, Learner judges "newspaper" to be similar to "book" and "magazine." Further suppose that assertions "books contain information" and "magazines contain information" are also already in the knowledge base. Then Learner will use cumulative analogy from the similar topics to ask humans whether "newspapers contain information." Because similarity between topics is computed based on what is already known about them, Learner exhibits bootstrapping behavior --- the quality of its questions improves as it gathers more knowledge. By summing evidence for and against posing any given question, Learner also exhibits noise tolerance, limiting the effect of incorrect similarities. The KA power of shallow semantic analogy from nearest neighbors is one of the main findings of this thesis. I perform an analysis of commonsense knowledge collected by another research effort that did not rely on analogical reasoning and demonstrate that indeed there is sufficient amount of correlation in the knowledge base to motivate using cumulative analogy from nearest neighbors as a KA method. Empirically, evaluating the percentages of questions answered affirmatively, negatively and judged to be nonsensical in the cumulative analogy case compares favorably with the baseline, no-similarity case that relies on random objects rather than nearest neighbors. Of the questions generated by cumulative analogy, contributors answered 45% affirmatively, 28% negatively and marked 13% as nonsensical; in the control, no-similarity case 8% of questions were answered affirmatively, 60% negatively and 26% were marked as nonsensical.

Investigación perfil en competencias y habilidades del empresario bogotano: trabajo de campo

Este documento corresponde al trabajo de campo para la investigación doctoral de Luis Alberto Estrada titulado “Perfil en competencias del empresario bogotano”. El objetivo que el equipo de investigación definió fue concretar las habilidades y competencias que acompañan a los emprendedores y fundadores de empresa en la primera década del siglo XXI. Para ello, se tomó una base de datos de la Cámara de Comercio de Bogotá, la cual contiene la información comercial de las empresas de la ciudad con matrícula mercantil vigente creadas en el periodo de 2000 a 2011 con un mínimo de 5 años de ventas registradas. Mediante el análisis de la información se seleccionó a las cincuenta empresas de mayor crecimiento en ventas, de las cuales ocho fueron encuestadas y entrevistadas junto a sus fundadores. Los hallazgos que se encontraron en este estudio muestran un perfil del grupo de encuestados con respecto a su formación, su relación, su gestión, sus aspiraciones, su compostura, su visión y su trascendencia.

Minimalist perspectives for psycholinguistic research

A particular approach to the study of psycholinguistic processes is presented, which is based on a minimalist conception of language. A procedural model of language acquisition is sketched, which reconciles infants speech processing and the idea of innately guided learning with a minimalist view of the initial state of language acquisition in an account of the bootstrapping problem. Language acquisition is viewed as proceeding with the progressive specification of formal features of the functional categories of the lexicon. The possibility of a minimalist derivation to be incorporated in a sentence production and/or comprehension model is discussed. Possible sources of language impairment, as manifested in SLI (Specific Language Impairment) syndrome, are considered in the light of this integrative approach. Reference is made to experimental work carried out in Brazilian Portuguese, with some extension to European Portuguese and River-Plate Spanish.

The use of bootstrapped Malmquist indices to reassess productivity change findings: an application to a sample of Polish farms

This article assesses the extent to which sampling variation affects findings about Malmquist productivity change derived using data envelopment analysis (DEA), in the first stage by calculating productivity indices and in the second stage by investigating the farm-specific change in productivity. Confidence intervals for Malmquist indices are constructed using Simar and Wilson's (1999) bootstrapping procedure. The main contribution of this article is to account in the second stage for the information in the second stage provided by the first-stage bootstrap. The DEA SEs of the Malmquist indices given by bootstrapping are employed in an innovative heteroscedastic panel regression, using a maximum likelihood procedure. The application is to a sample of 250 Polish farms over the period 1996 to 2000. The confidence intervals' results suggest that the second half of 1990s for Polish farms was characterized not so much by productivity regress but rather by stagnation. As for the determinants of farm productivity change, we find that the integration of the DEA SEs in the second-stage regression is significant in explaining a proportion of the variance in the error term. Although our heteroscedastic regression results differ with those from the standard OLS, in terms of significance and sign, they are consistent with theory and previous research.

Testing symmetry and homogeneity in the almost ideal demand system with co-integrated data using fully modified estimation and the bootstrap

Conventional seemingly unrelated estimation of the almost ideal demand system is shown to lead to small sample bias and distortions in the size of a Wald test for symmetry and homogeneity when the data are co-integrated. A fully modified estimator is developed in an attempt to remedy these problems. It is shown that this estimator reduces the small sample bias but fails to eliminate the size distortion.. Bootstrapping is shown to be ineffective as a method of removing small sample bias in both the conventional and fully modified estimators. Bootstrapping is effective, however, as a method of removing. size distortion and performs equally well in this respect with both estimators.

MPJ express: Towards thread safe Java HPC

MPJ Express is a thread-safe Java messaging library that provides a full implementation of the mpiJava 1.2 API specification. This specification defines a MPI-like bindings for the Java language. We have implemented two communication devices as part of our library, the first, called niodev is based on the Java New I/O package and the second, called mxdev is based on the Myrinet eXpress library MPJ Express comes with an experimental runtitne, which allows portable bootstrapping of Java Virtual Machines across a cluster or network of computers. In this paper we describe the implementation of MPJ Express. Also, we present a performance comparison against various other C and Java messaging systems. A beta version of MPJ Express was released in September 2005.

A comparison of extreme value theory approaches for determining value at risk

This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto distribution, and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that, for a holdout sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.

The performance of football club managers: skill or luck?

This paper evaluates the extent to which the performance of English Premier League football club managers can be attributed to skill or luck when measured separately from the characteristics of the team. We first use a specification that models managerial skill as a fixed effect and we examine the relationship between the number of points earned in league matches and the club’s wage bill, transfer spending, and the extent to which they were hit by absent players through injuries, suspensions or unavailability. We next implement a bootstrapping approach to generate a simulated distribution of average points that could have taken place after the impact of the manager has been removed. The findings suggest that there are a considerable number of highly skilled managers but also several who perform below expectations. The paper proceeds to illustrate how the approach adopted could be used to determine the optimal time for a club to part company with its manager. We are able to identify in advance several managers who the analysis suggests could have been fired earlier and others whose sackings were hard to justify based on their performances.

Centennial-scale climate change in Ireland during the Holocene

We examine mid- to late Holocene centennial-scale climate variability in Ireland using proxy data from peatlands, lakes and a speleothem. A high degree of between-record variability is apparent in the proxy data and significant chronological uncertainties are present. However, tephra layers provide a robust tool for correlation and improve the chronological precision of the records. Although we can find no statistically significant coherence in the dataset as a whole, a selection of high-quality peatland water table reconstructions co-vary more than would be expected by chance alone. A locally weighted regression model with bootstrapping can be used to construct a ‘best-estimate’ palaeoclimatic reconstruction from these datasets. Visual comparison and cross-wavelet analysis of peatland water table compilations from Ireland and Northern Britain show that there are some periods of coherence between these records. Some terrestrial palaeoclimatic changes in Ireland appear to coincide with changes in the North Atlantic thermohaline circulation and solar activity. However, these relationships are inconsistent and may be obscured by chronological uncertainties. We conclude by suggesting an agenda for future Holocene climate research in Ireland.

Top single nucleotide polymorphisms affecting carbohydrate metabolism in Metabolic Syndrome: from the LIPGENE study

Rationale:Metabolic Syndrome (MetS) is a high prevalence condition characterized by altered energy metabolism, insulin resistance and elevated cardiovascular risk.Objectives:Although many individual single nucleotide polymorphisms (SNPs) have been linked to certain MetS features, there are few studies analyzing the influence of SNPs on carbohydrate metabolism in MetS.Methods:904 SNPs (tag SNPs and functional SNPs) were tested for influence in eight fasting and dynamic markers of carbohydrate metabolism, performing an intravenous glucose tolerance test in 450 participants of the LIPGENE study.Findings:From 382 initial gene-phenotype associations between SNPs and any phenotypic variables, 61 (a 16 % of the pre-selected) remained significant after Bootstrapping. Top SNPs affecting glucose metabolism variables were as follows: fasting glucose: rs26125 (PPARGC1B); fasting insulin: rs4759277 (LRP1); C peptide: rs4759277 (LRP1); HOMA-IR: rs4759277 (LRP1); QUICKI: rs184003 (AGER); SI: rs7301876 (ABCC9), AIRg: rs290481 (TCF7L2) and DI: rs12691 (CEBPA).Conclusions:We describe here the top SNPs linked to phenotypic features in carbohydrate metabolism among aproximately 1000 candidate gene variations in fasting and postprandial samples of 450 patients with MetS from the LIPGENE study.

A measure of persistence in daily pound exchange rates

An alternative procedure to that of Lo is proposed for assessing whether there is significant evidence of persistence in time series. The technique estimates the Hurst exponent itself, and significance testing is based on an application of bootstrapping using surrogate data. The method is applied to a set of 10 daily pound exchange rates. A general lack of long-term memory is found to characterize all the series tested, in sympathy with the findings of a number of other recent papers which have used Lo's techniques.

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

Dynamics of the viscous Cahn-Hilliard equation

We study generalized viscous Cahn-Hilliard problems with nonlinearities satisfying critical growth conditions in W-0(1,p)(Omega), where Omega is a bounded smooth domain in R-n, n >= 3. In the critical growth case, we prove that the problems are locally well posed and obtain a bootstrapping procedure showing that the solutions are classical. For p = 2 and almost critical dissipative nonlinearities we prove global well posedness, existence of global attractors in H-0(1)(Omega) and, uniformly with respect to the viscosity parameter, L-infinity(Omega) bounds for the attractors. Finally, we obtain a result on continuity of regular attractors which shows that, if n = 3, 4, the attractor of the Cahn-Hilliard problem coincides (in a sense to be specified) with the attractor for the corresponding semilinear heat equation. (C) 2008 Elsevier Inc. All rights reserved.