Récits du vieillir « actif » et de la citoyenneté au quotidien : l’expérience des femmes aînées au Québec

Taken as a policy framework, active aging ranks high on most supranational bodies’ agenda. The new political economy of aging portrays “active” citizenship amongst seniors as a key challenge for the years to come. Our research focuses on, first, elderly women’s everyday ‘active’ practices, their meaning and purpose, in the context of Quebec’s active aging policy framework; and second, their day-to-day practical citizenship experiences. Informed by discourse analysis and a narrative approach, the life stories of women 60 to 70 years of age allowed for the identification of a plethora of distinctive old age activity figures. More specifically, four activity figures were identified by which respondents materialize their routine active practices, namely: (1) paid work; (2) voluntary and civic engagement; (3) physical activity; and (4) caregiving. Set against Quebec’s active aging policy framework, these patterns and set of practices that underpin them are clearly in tune with government’s dominant perspectives. Respondents’ narratives also show that active aging connotes a range of ‘ordinary’ activities of daily living, accomplished within people’s private worlds and places of proximity. Despite nuances, tensions and opposition found in dominant public discourse, as well as in active aging practices, a form of counter-discourse does not emerge from respondents’ narratives. To be active is normally the antithesis of immobility and dependence. Thus, to see oneself as active in old age draws on normative, positive assumptions about old age quite difficult to refute; nevertheless, discourses also raise identity and relational issues. In this respect, social inclusion issues cut across all active aging practices described by respondents. Moreover, a range of individual aims and quests underpin activity pattern. Such quests express respondents’ subjective interactions with their social environment; including their actions’ meaning and sense of social inclusiveness in old age. A first quest relates to personal identity and social integration to the world; a second one concerns giving; a third centers on the search for authenticity; whereas the fourth one is connected to a desire for freedom. It is through the objectivising of active practices and related existential pursuits that elderly woman recognize themselves as active citizens, rooted in the community, and variously contributing to society. Accordingly, ‘active’ citizenship experiences are articulated in a dialogic manner between the dimensions of ‘doing’, ‘active’ social practices, and ‘being’ in relation to others, within a context of interdependence. A proposed typology allows for the modeling of four ‘active’ citizenship figures. Overall, despite the role played by power relations and social inequality in structuring aging experiences, in everyday life ‘old age citizenship’ appears as a relational process, embedded in a set of social relations and practices involving individuals, families and communities, whereby elderly women are able to express a sense of agency within their social world.

Being Relational With Underserved Youth: A Reflective Process

When working with under-served youth, possibly the most important, yet often times the most difficult, thing for practitioners to do is to build positive, trusting, open relationships. This study aims to address this challenge. Two groups of under-served youth were examined, one being teens deemed “at-risk” and one being youth with Autism Spectrum Disorder (ASD). This study was novel in its approach as all efforts were made to ensure the youth's opinions on how to be relational with them were heard. Two youths with ASD were nonverbal and a special picture interview procedure was developed to allow their participation. Three thematic statements emerged from the data collected: 1. Youth need low anxiety relationships. 2. Youth need novel forms of engagement. 3. Youth need us to understand that their actions reflect their histories. The analyses that lead to these statements are described as well as the reasoning and implications of these statements.

A Process Model of Complementarity and Substitution of Contractual and Relational Governance in IS Outsourcing

This paper develops a process model of how and why complementarity and substitution form over time between contractual and relational governance in the context of information systems outsourcing. Our analysis identifies four distinct process patterns that explain this formation as the outcome of interaction processes between key elements of both contractual and relational governance. These patterns unveil the dynamic nature of complementarity and substitution. In particular, we show that the relationship between contractual and relational governance oscillates between complementarity and substitution. Those oscillations are triggered mainly by three types of contextual events (goal fuzziness, goal conflict, and goal misalignment). Surprisingly, substitution of informal control did not occur as an immediate reaction to external events but emerged as a consequence of preceding complementarity. Thus, our study challenges the prevailing view of an either/or dichotomy of complementarity and substitution by showing that they are causally connected over time.

Using relational algebra on the specification of real world ETL processes

Modeling Extract-Transform-Load (ETL) processes of a Data Warehousing System has always been a challenge. The heterogeneity of the sources, the quality of the data obtained and the conciliation process are some of the issues that must be addressed in the design phase of this critical component. Commercial ETL tools often provide proprietary diagrammatic components and modeling languages that are not standard, thus not providing the ideal separation between a modeling platform and an execution platform. This separation in conjunction with the use of standard notations and languages is critical in a system that tends to evolve through time and which cannot be undermined by a normally expensive tool that becomes an unsatisfactory component. In this paper we demonstrate the application of Relational Algebra as a modeling language of an ETL system as an effort to standardize operations and provide a basis for uncommon ETL execution platforms.

A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process

Relationships and knowledge in the firm internationalization process

Based on the variables relationship and knowledge, this article aimed at analyzing how a multinational enterprise selects an entry mode to operate in a particular international market and how this initial choice evolves over time. We devised a rather new theoretical framework to address it by combining three theoretical approaches that have dealt with the firm internationalization: the Uppsala model, the relational approach, and the subsidiary development literature. We constructed a qualitative backward-looking longitudinal case study of the internationalization process of a North-American multinational enterprise in the Brazilian market. Results show that four types of relationships and three types of knowledge played the role in the events that characterized the internationalization of this firm. Based on these results, five new hypotheses concerning the interplay between relationships and knowledge in the internationalization process of the firm are suggested for future empirical tests.

Determinants of acquisition completion: a relational perspective

The strategic literature on relatedness in the context of mergers and acquisitions (M&As) is extensive, yet we know little about whether or how relatedness has an influence on the announcement to completion stage of the M&A process. Drawing on research on intra-industry competition and relational capabilities, we seek to shed light on the relatedness debate by examining the strategic forces that affect the completion of an announced related M&A, accounting for financial and organizational factors. We also explore additional strategic forces that might amplify or attenuate the negative effect of relatedness on deal completion. We test and find support for our hypotheses using longitudinal data from a sample of the largest M&A announcements in the world from 1991 to 2001.

Soil infiltration based on bp neural network and grey relational analysis

Soil infiltration is a key link of the natural water cycle process. Studies on soil permeability are conducive for water resources assessment and estimation, runoff regulation and management, soil erosion modeling, nonpoint and point source pollution of farmland, among other aspects. The unequal influence of rainfall duration, rainfall intensity, antecedent soil moisture, vegetation cover, vegetation type, and slope gradient on soil cumulative infiltration was studied under simulated rainfall and different underlying surfaces. We established a six factor-model of soil cumulative infiltration by the improved back propagation (BP)-based artificial neural network algorithm with a momentum term and self-adjusting learning rate. Compared to the multiple nonlinear regression method, the stability and accuracy of the improved BP algorithm was better. Based on the improved BP model, the sensitive index of these six factors on soil cumulative infiltration was investigated. Secondly, the grey relational analysis method was used to individually study grey correlations among these six factors and soil cumulative infiltration. The results of the two methods were very similar. Rainfall duration was the most influential factor, followed by vegetation cover, vegetation type, rainfall intensity and antecedent soil moisture. The effect of slope gradient on soil cumulative infiltration was not significant.

Managing induced tourism image : relational patterns and the life cycle

The tourism image is an element that conditions the competitiveness of tourism destinations by making them stand out in the minds of tourists. In this context, marketers of tourism destinations endeavour to create an induced image based on their identity and distinctive characteristics.A number of authors have also recognized the complexity of tourism destinations and the need for coordination and cooperation among all tourism agents, in order to supply a satisfactory tourist product and be competitive in the tourism market. Therefore, tourism agents at the destination need to develop and integrate strategic marketing plans.The aim of this paper is to determine how cities of similar cultures use their resources with the purpose of developing a distinctive induced tourism image to attract tourists and the extent of coordination and cooperation among the various tourism agents of a destination in the process of induced image creation.In order to accomplish these aims, a comparative analysis of the induced image of two cultural cities is presented, Girona (Spain) and Perpignan (France). The induced image is assessed through the content analysis of promotional brochures and the extent of cooperation with in-depth interviews of the main tourism agents of these destinations.Despite the similarities of both cities in terms of tourism resources, results show the use of different attributes to configure the induced image of each destination, as well as a different configuration of the network of tourism agents that participate in the process of induced image creation

Improving reporting management with relational database management system

Data management consists of collecting, storing, and processing the data into the format which provides value-adding information for decision-making process. The development of data management has enabled of designing increasingly effective database management systems to support business needs. Therefore as well as advanced systems are designed for reporting purposes, also operational systems allow reporting and data analyzing. The used research method in the theory part is qualitative research and the research type in the empirical part is case study. Objective of this paper is to examine database management system requirements from reporting managements and data managements perspectives. In the theory part these requirements are identified and the appropriateness of the relational data model is evaluated. In addition key performance indicators applied to the operational monitoring of production are studied. The study has revealed that the appropriate operational key performance indicators of production takes into account time, quality, flexibility and cost aspects. Especially manufacturing efficiency has been highlighted. In this paper, reporting management is defined as a continuous monitoring of given performance measures. According to the literature review, the data management tool should cover performance, usability, reliability, scalability, and data privacy aspects in order to fulfill reporting managements demands. A framework is created for the system development phase based on requirements, and is used in the empirical part of the thesis where such a system is designed and created for reporting management purposes for a company which operates in the manufacturing industry. Relational data modeling and database architectures are utilized when the system is built for relational database platform.

A Homogeneous Set-Theoretical Frame for Clustering Fuzzy Relational Data

Our purpose is to provide a set-theoretical frame to clustering fuzzy relational data basically based on cardinality of the fuzzy subsets that represent objects and their complementaries, without applying any crisp property. From this perspective we define a family of fuzzy similarity indexes which includes a set of fuzzy indexes introduced by Tolias et al, and we analyze under which conditions it is defined a fuzzy proximity relation. Following an original idea due to S. Miyamoto we evaluate the similarity between objects and features by means the same mathematical procedure. Joining these concepts and methods we establish an algorithm to clustering fuzzy relational data. Finally, we present an example to make clear all the process

Relational architecture and relational capability: organisational levers to support strategic supplier relationships

The resource based view of strategy suggests that competitiveness in part derives from a firms ability to collaborate with a subset of its supply network to co-create highly valued products and services. This relational capability relies on a foundational intra and inter-organisational architecture, the manifestation of strategic, people, and process decisions facilitating the interface between the firm and its strategic suppliers. Using covariance-based structural equation modelling we examine the relationships between internal and external features of relational architecture, and their relationship with relational capability and relational quality. This is undertaken on data collected by mail survey. We find significant relationships between both internal and external relational architecture and relational capability and between relational capability and relational quality. Novel constructs for internal and external elements of relational architecture are specified to demonstrate their positive influence on relational capability and relationship quality.

Multi-relational algorithm for mining association rules in large databases

Multi-relational data mining enables pattern mining from multiple tables. The existing multi-relational mining association rules algorithms are not able to process large volumes of data, because the amount of memory required exceeds the amount available. The proposed algorithm MRRadix presents a framework that promotes the optimization of memory usage. It also uses the concept of partitioning to handle large volumes of data. The original contribution of this proposal is enable a superior performance when compared to other related algorithms and moreover successfully concludes the task of mining association rules in large databases, bypass the problem of available memory. One of the tests showed that the MR-Radix presents fourteen times less memory usage than the GFP-growth. © 2011 IEEE.

MR-Radix: a multi-relational data mining algorithm

Background: Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods: Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results: This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion: The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.