Scales, networks and uncertainty : an examination of environmental policy-making in Ontario

Through a case-study analysis of Ontario's ethanol policy, this thesis addresses a number of themes that are consequential to policy and policy-making: spatiality, democracy and uncertainty. First, I address the 'spatial debate' in Geography pertaining to the relevance and affordances of a 'scalar' versus a 'flat' ontoepistemology. I argue that policy is guided by prior arrangements, but is by no means inevitable or predetermined. As such, scale and network are pragmatic geographical concepts that can effectively address the issue of the spatiality of policy and policy-making. Second, I discuss the democratic nature of policy-making in Ontario through an examination of the spaces of engagement that facilitate deliberative democracy. I analyze to what extent these spaces fit into Ontario's environmental policy-making process, and to what extent they were used by various stakeholders. Last, I take seriously the fact that uncertainty and unavoidable injustice are central to policy, and examine the ways in which this uncertainty shaped the specifics of Ontario's ethanol policy. Ultimately, this thesis is an exercise in understanding sub-national environmental policy-making in Canada, with an emphasis on how policy-makers tackle the issues they are faced with in the context of environmental change, political-economic integration, local priorities, individual goals, and irreducible uncertainty.

Social competence following mild head injury and moderate traumatic brain injury: Investigating the neuropsychological relationships between arousal, social decision-making and depression

Client-directed long-term rehabilitative goals and life satisfaction following head injury emphasize the importance of social inclusion, rather than cognitive or physical, outcomes. However, very little research has explored the socio-emotional factors that pose as barriers to social reintegration following injury. This study investigates social barriers following head injury (i.e., decision-making - Iowa Gambling Task [IGT] and mood – depression) and possible amelioration of those challenges (through treatment) in both highly functioning university students with and without mild head injury (MHI) and in individuals with moderate traumatic brain injury (TBI). An arousal manipulation using emotionally evocative stimuli was introduced to manipulate the subject’s physiological arousal state. Seventy-five university students (37.6% reporting a MHI) and 11 patients with documented moderate TBI were recruited to participate in this quasi-experimental study. Those with head injury were found to be physiologically underaroused (on measures of electrodermal activation [EDA] and pulse) and were less sensitive to the negative effects of punishment (i.e., losses) in the gambling task than those without head injury, with greater impairment being observed for the moderate TBI group. The arousal manipulation, while effective, was not able to maintain a higher state of arousal in the injury groups across trials (i.e., their arousal state returned to pre-manipulation levels more quickly than their non-injured cohort), and, subsequently, a performance improvement was not observed on the IGT. Lastly, head injury was found to contribute to the relationship between IGT performance and depressive symptom acknowledgment and mood status in persons with head injury. This study indicates the possible important role of physiological arousal on socio- emotional behaviours (decision-making, mood) in persons with even mild, non-complicated head injuries and across the injury severity continuum.

Computation and Analysis of Multiple Structural-Change Models

In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2) for any number of breaks. Our method can be applied to both pure and partial structural-change models. Secondly, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. We present simulation results pertaining to the behavior of the estimators and tests in finite samples. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program available upon request for non-profit academic use.

The Efficiency of Collective Bargaining in Public Schools.

This paper develops a bargaining model of wage and employment determination for the public sector. the solution to the model generates structural wage and employment equations that are estimated using data from New York State teacher-school district collective bargaining agreements.

Analogy in Decision-Making

In the context of decision making under uncertainty, we formalize the concept of analogy: an analogy between two decision problems is a mapping that transforms one problem into the other while preserving the problem's structure. We identify the basic structure of a decision problem, and provide a representation of the mappings that pre- serve this structure. We then consider decision makers who use multiple analogies. Our main results are a representation theorem for "aggregators" of analogies satisfying certain minimal requirements, and the identification of preferences emerging from analogical reasoning. We show that a large variety of multiple-prior preferences can be thought of as emerging from analogical reasoning.

Barriers of evidence based policy making in iran's health system

La formation des sociétés fondées sur la connaissance, le progrès de la technologie de communications et un meilleur échange d'informations au niveau mondial permet une meilleure utilisation des connaissances produites lors des décisions prises dans le système de santé. Dans des pays en voie de développement, quelques études sont menées sur des obstacles qui empêchent la prise des décisions fondées sur des preuves (PDFDP) alors que des études similaires dans le monde développé sont vraiment rares. L'Iran est le pays qui a connu la plus forte croissance dans les publications scientifiques au cours de ces dernières années, mais la question qui se pose est la suivante : quels sont les obstacles qui empêchent l'utilisation de ces connaissances de même que celle des données mondiales? Cette étude embrasse trois articles consécutifs. Le but du premier article a été de trouver un modèle pour évaluer l'état de l'utilisation des connaissances dans ces circonstances en Iran à l’aide d'un examen vaste et systématique des sources suivie par une étude qualitative basée sur la méthode de la Grounded Theory. Ensuite au cours du deuxième et troisième article, les obstacles aux décisions fondées sur des preuves en Iran, sont étudiés en interrogeant les directeurs, les décideurs du secteur de la santé et les chercheurs qui travaillent à produire des preuves scientifiques pour la PDFDP en Iran. Après avoir examiné les modèles disponibles existants et la réalisation d'une étude qualitative, le premier article est sorti sous le titre de «Conception d'un modèle d'application des connaissances». Ce premier article sert de cadre pour les deux autres articles qui évaluent les obstacles à «pull» et «push» pour des PDFDP dans le pays. En Iran, en tant que pays en développement, les problèmes se situent dans toutes les étapes du processus de production, de partage et d’utilisation de la preuve dans la prise de décision du système de santé. Les obstacles qui existent à la prise de décision fondée sur des preuves sont divers et cela aux différents niveaux; les solutions multi-dimensionnelles sont nécessaires pour renforcer l'impact de preuves scientifiques sur les prises de décision. Ces solutions devraient entraîner des changements dans la culture et le milieu de la prise de décision afin de valoriser la prise de décisions fondées sur des preuves. Les critères de sélection des gestionnaires et leur nomination inappropriée ainsi que leurs remplaçants rapides et les différences de paiement dans les secteurs public et privé peuvent affaiblir la PDFDP de deux façons : d’une part en influant sur la motivation des décideurs et d'autre part en détruisant la continuité du programme. De même, tandis que la sélection et le remplacement des chercheurs n'est pas comme ceux des gestionnaires, il n'y a aucun critère pour encourager ces deux groupes à soutenir le processus décisionnel fondés sur des preuves dans le secteur de la santé et les changements ultérieurs. La sélection et la promotion des décideurs politiques devraient être basées sur leur performance en matière de la PDFDP et les efforts des universitaires doivent être comptés lors de leurs promotions personnelles et celles du rang de leur institution. Les attitudes et les capacités des décideurs et des chercheurs devraient être encouragés en leur donnant assez de pouvoir et d’habiliter dans les différentes étapes du cycle de décision. Cette étude a révélé que les gestionnaires n'ont pas suffisamment accès à la fois aux preuves nationales et internationales. Réduire l’écart qui sépare les chercheurs des décideurs est une étape cruciale qui doit être réalisée en favorisant la communication réciproque. Cette question est très importante étant donné que l'utilisation des connaissances ne peut être renforcée que par l'étroite collaboration entre les décideurs politiques et le secteur de la recherche. Dans ce but des programmes à long terme doivent être conçus ; la création des réseaux de chercheurs et de décideurs pour le choix du sujet de recherche, le classement des priorités, et le fait de renforcer la confiance réciproque entre les chercheurs et les décideurs politiques semblent être efficace.

Contextualizing discretion : micro-dynamics of Canada’s refugee determination system

À une époque où l'immigration internationale est de plus en plus difficile et sélective, le statut de réfugié constitue un bien public précieux qui permet à certains non-citoyens l'accès et l'appartenance au pays hôte. Reposant sur le jugement discrétionnaire du décideur, le statut de réfugié n’est accordé qu’aux demandeurs qui établissent une crainte bien fondée de persécution en cas de retour dans leur pays d'origine. Au Canada, le plus important tribunal administratif indépendant, la Commission de l'immigration et du statut de réfugié du Canada (CISR), est chargé d’entendre les demandeurs d'asile et de rendre des décisions de statut de réfugié. Cette thèse cherche à comprendre les disparités dans le taux d’octroi du statut de réfugié entre les décideurs de la CISR qui sont politiquement nommés. Au regard du manque de recherches empiriques sur la manière avec laquelle le Canada alloue les possibilités d’entrée et le statut juridique pour les non-citoyens, il était nécessaire de lever le voile sur le fonctionnement de l’administration sur cette question. En explorant la prise de décision relative aux réfugiés à partir d'une perspective de Street Level Bureaucracy Theory (SLBT) et une méthodologie ethnographique qui combine l'observation directe, les entretiens semi-structurés et l'analyse de documents, l'étude a d'abord cherché à comprendre si la variation dans le taux d’octroi du statut était le résultat de différences dans les pratiques et le raisonnement discrétionnaires du décideur et ensuite à retracer les facteurs organisationnels qui alimentent les différences. Dans la lignée des travaux de SLBT qui documentent la façon dont la situation de travail structure la discrétion et l’importance des perceptions individuelles dans la prise de décision, cette étude met en exergue les différences de fond parmi les décideurs concernant les routines de travail, la conception des demandeurs d’asile, et la meilleure façon de mener leur travail. L’analyse montre comment les décideurs appliquent différentes approches lors des audiences, allant de l’interrogatoire rigide à l’entrevue plus flexible. En dépit des contraintes organisationnelles qui pèsent sur les décideurs pour accroître la cohérence et l’efficacité, l’importance de l’évaluation de la crédibilité ainsi que l’invisibilité de l’espace de décision laissent suffisamment de marge pour l’exercice d’un pouvoir discrétionnaire. Même dans les environnements comme les tribunaux administratifs où la surabondance des règles limite fortement la discrétion, la prise de décision est loin d’être synonyme d’adhésion aux principes de neutralité et hiérarchie. La discrétion est plutôt imbriquée dans le contexte de routines d'interaction, de la situation de travail, de l’adhésion aux règles et du droit. Même dans les organisations qui institutionnalisent et uniformisent la formation et communiquent de façon claire leurs demandes aux décideurs, le caractère discrétionnaire de la décision est par la nature difficile, voire impossible, à contrôler et discipliner. Lorsqu'ils sont confrontés à l'ambiguïté des objectifs et aux exigences qui s’opposent à leur pouvoir discrétionnaire, les décideurs réinterprètent la définition de leur travail et banalisent leurs pratiques. Ils formulent une routine de rencontre qui est acceptable sur le plan organisationnel pour évaluer les demandeurs face à eux. Cette thèse montre comment les demandeurs, leurs témoignages et leurs preuves sont traités d’une manière inégale et comment ces traitements se répercutent sur la décision des réfugiés.

An Analysis of Work Related Stress Factor in Selected Industries in Kerala ,India

Occupational stress is becoming a major issue in both corporate and social agenda .In industrialized countries, there have been quite dramatic changes in the conditions at work, during the last decade ,caused by economic, social and technical development. As a consequence, the people today at work are exposed to high quantitative and qualitative demands as well as hard competition caused by global economy. A recent report says that ailments due to work related stress is likely to cost India’s exchequer around 72000 crores between 2009 and 2015. Though India is a fast developing country, it is yet to create facilities to mitigate the adverse effects of work stress, more over only little efforts have been made to assess the work related stress.In the absence of well defined standards to assess the work related stress in India, an attempt is made in this direction to develop the factors for the evaluation of work stress. Accordingly, with the help of existing literature and in consultation with the safety experts, seven factors for the evaluation of work stress is developed. An instrument ( Questionnaire) was developed using these seven factors for the evaluation of work stress .The validity , and unidimensionality of the questionnaire was ensured by confirmatory factor analysis. The reliability of the questionnaire was ensured before administration. While analyzing the relation ship between the variables, it is noted that no relationship exists between them, and hence the above factors are treated as independent factors/ variables for the purpose of research .Initially five profit making manufacturing industries, under public sector in the state of Kerala, were selected for the study. The influence of factors responsible for work stress is analyzed in these industries. These industries were classified in to two types, namely chemical and heavy engineering ,based on the product manufactured and work environment and the analysis is further carried out for these two categories.The variation of work stress with different age , designation and experience of the employees are analyzed by means of one-way ANOVA. Further three different type of modelling of work stress, namely factor modelling, structural equation modelling and multinomial logistic regression modelling was done to analyze the association of factors responsible for work stress. All these models are found equally good in predicting the work stress.The present study indicates that work stress exists among the employees in public sector industries in Kerala. Employees belonging to age group 40-45yrs and experience groups 15-20yrs had relatively higher work demand ,low job control, and low support at work. Low job control was noted among lower designation levels, particularly at the worker level in these industries. Hence the instrument developed using the seven factors namely demand, control, manager support, peer support, relationship, role and change can be effectively used for the evaluation of work stress in industries.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

Some concepts and models usefulninthe analysis of discrete life time data

This thesis entitled Reliability Modelling and Analysis in Discrete time Some Concepts and Models Useful in the Analysis of discrete life time data.The present study consists of five chapters. In Chapter II we take up the derivation of some general results useful in reliability modelling that involves two component mixtures. Expression for the failure rate, mean residual life and second moment of residual life of the mixture distributions in terms of the corresponding quantities in the component distributions are investigated. Some applications of these results are also pointed out. The role of the geometric,Waring and negative hypergeometric distributions as models of life lengths in the discrete time domain has been discussed already. While describing various reliability characteristics, it was found that they can be often considered as a class. The applicability of these models in single populations naturally extends to the case of populations composed of sub-populations making mixtures of these distributions worth investigating. Accordingly the general properties, various reliability characteristics and characterizations of these models are discussed in chapter III. Inference of parameters in mixture distribution is usually a difficult problem because the mass function of the mixture is a linear function of the component masses that makes manipulation of the likelihood equations, leastsquare function etc and the resulting computations.very difficult. We show that one of our characterizations help in inferring the parameters of the geometric mixture without involving computational hazards. As mentioned in the review of results in the previous sections, partial moments were not studied extensively in literature especially in the case of discrete distributions. Chapters IV and V deal with descending and ascending partial factorial moments. Apart from studying their properties, we prove characterizations of distributions by functional forms of partial moments and establish recurrence relations between successive moments for some well known families. It is further demonstrated that partial moments are equally efficient and convenient compared to many of the conventional tools to resolve practical problems in reliability modelling and analysis. The study concludes by indicating some new problems that surfaced during the course of the present investigation which could be the subject for a future work in this area.

Managerial Performance – An Analysis of Selected Antecedents and Mediators

The primary focus of this study was to asses the impact of selected antecedent variables namely Psychological Empowerment at Work (PEW), Psychological Contract Violation (PCV), Work Life Balance (WLB), Job Satisfaction (JS) and Affective Organisational Commitment (AOC) on Managerial Performance (MP) of middle level managers of private sector manufacturing and service sector organisations in Kerala.The study brings out the significance of Job Attitudes namely Job Satisfaction and Affective Organisational Commitment in meaningfully explaining the linkage between the rest of the antecedent variables in the study and Managerial Performance. The study interestingly revealed that Job Attitudes play a mediating role in explaining performance of managers unlike visualised in the initial conceptual framework. The study points to the importance of taking care of job attitudes in the work place to ensure performance of managers. The result of the study also brings out the significance of maintaining work-life balance especially in service sector organisations because it will have a direct impact on the level of performance of managers than most of the other contextual factors. Hence, it is the responsibility of HR department to initiate activities which are customised to the collective aspirations of the members of respective organisations to ensure positive job attitudes. HR departments should advice and convince the top management to provide resource support and endorsement to such initiatives.

An analysis of household farm investment decisions under varying land tenure arrangements in Ghana

Land tenure insecurity is widely perceived as a disincentive for long-term land improvement investment hence the objective of this paper is to evaluate how tenure (in)security associated with different land use arrangements in Ghana influenced households’ plot level investment decisions and choices. The paper uses data from the Farmer-Based Organisations (FBO) survey. The FBO survey collected information from 2,928 households across three ecological zones of Ghana using multistaged cluster sampling. Probit and Tobit models tested the effects of land tenancy and ownership arrangements on households’ investment behaviour while controlling other factors. It was found that marginal farm size was inversely related to tenure insecurity while tenure insecurity correlate positively with value of farm land and not farm size. Individual ownership and documentation of land significantly reduced the probability of households losing uncultivated lands. Individual land ownership increased both the probability of investing and level of investments made in land improvement and irrigation probably due to increasing importance households place on land ownership. Two possible explanations for this finding are: First, that land markets and land relations have changed significantly over the last two decades with increasing money transaction and fixed agreements propelled by population growth and increasing value of land. Secondly, inclusion of irrigation investment as a long term investment in land raises the value of household investment and the time period required to reap the returns on the investments. Households take land ownership and duration of tenancy into consideration if the resource implications of land investments are relatively huge and the time dimension for harvesting returns to investments is relatively long.

An Analysis of the Effect of Gaussian Error in Object Recognition

Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

Compositional analysis of archaeological glasses

At CoDaWork'03 we presented work on the analysis of archaeological glass composi- tional data. Such data typically consist of geochemical compositions involving 10-12 variables and approximates completely compositional data if the main component, sil- ica, is included. We suggested that what has been termed `crude' principal component analysis (PCA) of standardized data often identi ed interpretable pattern in the data more readily than analyses based on log-ratio transformed data (LRA). The funda- mental problem is that, in LRA, minor oxides with high relative variation, that may not be structure carrying, can dominate an analysis and obscure pattern associated with variables present at higher absolute levels. We investigate this further using sub- compositional data relating to archaeological glasses found on Israeli sites. A simple model for glass-making is that it is based on a `recipe' consisting of two `ingredients', sand and a source of soda. Our analysis focuses on the sub-composition of components associated with the sand source. A `crude' PCA of standardized data shows two clear compositional groups that can be interpreted in terms of di erent recipes being used at di erent periods, re ected in absolute di erences in the composition. LRA analysis can be undertaken either by normalizing the data or de ning a `residual'. In either case, after some `tuning', these groups are recovered. The results from the normalized LRA are di erently interpreted as showing that the source of sand used to make the glass di ered. These results are complementary. One relates to the recipe used. The other relates to the composition (and presumed sources) of one of the ingredients. It seems to be axiomatic in some expositions of LRA that statistical analysis of compositional data should focus on relative variation via the use of ratios. Our analysis suggests that absolute di erences can also be informative

Searching for consensus in ahp-group decision making. A bayesian perspective

This paper sets out to identify the initial positions of the different decision makers who intervene in a group decision making process with a reduced number of actors, and to establish possible consensus paths between these actors. As a methodological support, it employs one of the most widely-known multicriteria decision techniques, namely, the Analytic Hierarchy Process (AHP). Assuming that the judgements elicited by the decision makers follow the so-called multiplicative model (Crawford and Williams, 1985; Altuzarra et al., 1997; Laininen and Hämäläinen, 2003) with log-normal errors and unknown variance, a Bayesian approach is used in the estimation of the relative priorities of the alternatives being compared. These priorities, estimated by way of the median of the posterior distribution and normalised in a distributive manner (priorities add up to one), are a clear example of compositional data that will be used in the search for consensus between the actors involved in the resolution of the problem through the use of Multidimensional Scaling tools