Living in the Skin That I Am: An Organizational Autoethnography of an Adult Educator's Plight to Survive the Stigma of Invisible and Episodic Disability in an Academy of Administritiva

Through the reflective lens of an adult educator with invisible and episodic disabilities, this paper has been written as an organizational autoethnography. Through a process of autoethnographical sensemaking, it is intended to illuminate important gaps in organizational theory. Feminist/relational care ethics, critical reflection, and transformative learning serve as the educational theories that comprise its framework. In telling my story, embodied writing and performance narrative are used to convey the felt existence of a body exposed through words—where my “abled” and “disabled” professional teaching and learning identities may be studied against the backdrop of organizational policies and procedures. Words used to describe unfamiliar experiences and situations shape meaning for which new meaning may emerge. At the conclusion of this paper, an alternative frame of reference—a view from the margins—may be offered to articulate authenticity in the expectancy of workplace equity for adult educators with disabilities. Taken collectively on a larger level, it is hoped that this research may provide a source of inspiration for systemic organizational change in adult learning environments.

Convocation Program 1985 - Honorary Degree to Sean O'Sullivan

A convocation program for June 1985. On 7 June 1985, Father Sean O'Sullivan gave the convocation address and was conferred an honorary degree.

Coping with a Learning Disability: A Case Study

The purpose of this qualitative case study was to understand a child’s experience with a learning disability (LD) through the way that they cope with it, and how self-esteem, self-efficacy, attribution style, and social support contribute to this process. Qualitative interviews were conducted with one child, his parents, and his teacher, accompanied by a content analysis of the child’s psychosocial assessment report. It was found that the child copes well with having a learning disability, employing a problem-focused/approach coping style by seeking help and practicing for skills he struggles with, an emotion-focused coping style by implementing strategies to alleviate frustration, and compartmentalizing his disability. Further, self-esteem, self-efficacy, attribution style, social support and sports and leisure engagement were found to contribute positively to the coping process. These findings offer useful implications for parents, teachers, and practitioners to support other students with LD.

Parent Prediction of Autism Spectrum Disorder in Infants At Risk: A Follow-up Study

Later-born siblings of children with autism spectrum disorder (ASD) are considered at biological risk for ASD and the broader autism phenotype. Early screening may detect early signs of ASD and facilitate intervention as soon as possible. This follow-up study revisits and re-examines a second-degree autism screener for children at biological risk of autism, the Parent Observation Early Markers Scale (POEMS, Feldman et al., 2012). Using available follow-up information, 110 children (the original 108 infants plus 2 infants recruited after the completion of the original study) were divided into three groups: diagnosed group (n = 13), lost diagnosis group (n = 5), and undiagnosed group (n = 92). The POEMS continued to show acceptable predictive validity. The POEMS total scores and mean number of elevated items were significantly higher in the diagnosed group than the undiagnosed group. The lost diagnosis group did not differ from the undiagnosed group on POEMS total scores and elevated items at any age, but the lost diagnosis group had significantly lower total scores and number of elevated items than the diagnosed group starting at 18 months. Both ASD core and subsidiary behaviours differentiated the diagnosed and undiagnosed groups from 9−36 months of age. Using 70 as a cut-off score, sensitivity, specificity, and positive predictive value (PPV) were .69, .84, and .38, respectively. The study provides further evidence that the POEMS may serve as a low-cost early screener for ASD in at risk children and pinpoint specific developmental and behavioural problems that may be amenable to very early intervention.

Educational Attainment of Second-Generation Immigrants in Belgium: an Estimation of the Assimilation Degree of Immigrants Based on Cross Section Analysis.

Rapport de recherche

First-Degree Discrimination in a Competitive Setting: Pricing and Quality Choice

The paper investigates competition in price schedules among vertically differentiated dupolists. First order price discrimination is the unique Nash equilibrium of a sequential game in which firms determine first whether or not to commit to a uniform price, and then simultaneously choose either a single price of a price schedule. Whether the profits earned by both firms are larger or smaller under discrimination than under uniform pricing depends on the quality gap between firms, and on the disparity of consumer preferences. Firms engaged in first degree discrimination choose quality levels that are optimal from a welfare perspective. The paper also reflects on implications of these findings for pricing policies of an incumbent threatened by entry.

Ideal timing to transfer from an acute care hospital to an interdisciplinary inpatient rehabilitation program following a stroke: an exploratory study

Affiliation: Dany Gagnon & Sylvie Nadeau: École de réadaptation, Faculté de médecine, Université de Montréal & Centre de recherche interdisciplinaire en réadaptation, Institut de réadaptation de Montréal

Does the Degree of Openness of an Economy Affect its Economic Growth.

Rapport de recherche

Geography of disability. An analysis based on the socioeconomic levels of two metropolitan areas : Monterrey, Nuevo León and Dallas, Texas.

Tesis (Doctor en Filosofía con Orientación en Trabajo Social y Políticas Comparadas de Bienestar Social) UANL, 2013.

Disability is in the Eye of the Beholder

Travail créatif / Creative Work

When Disability Rhymes with Negative Bias: A Response to Verpaelst

Commentaire / Commentary

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.

Ecotoxic Metal Records and its Degree of Geochemical Symphony in the Niche of Cochin Estuarine System- A Theraptic Perspective

The heavy metal contamination in the environment may lead to circumstances like bioaccumulation and inturn biomagnification. Hence cheaper and effective technologies are needed to protect the precious natural resources and biological lives. A suitable technique is the one which meets the technical and environmental criteria for dealing with a particular remediation problem and should be site-specific due to spatial and climatic variations and it may not economically feasible everywhere. The search for newer technologies for the environmental therapy, involving the removal of toxic metals from wastewaters has directed attention to adsorption, based on metal binding capacities of various adsorbent materials. Therefore, the present study aim to identify and evaluate the most current mathematical formulations describing sorption processes. Although vast amount of research has been carried out in the area of metal removal by adsorption process using activated carbon few specific research data are available in different scientific institutions. The present work highlights the seasonal and spatial variations in the distribution of some selected heavy metals among various geochemical phases of Cochin Estuarine system and also looked into an environmental theraptic/remedial approach by adsorption technique using activated charcoal and chitosan, to reduce and thereby controlling metallic pollution. The thesis has been addressed in seven chapters with further subdivisions. The first chapter is introductory, stating the necessity of reducing or preventing water pollution due to the hazardous impact on environment and health of living organisms and drawing it from a careful review of literature relevant to the present study. It provides a constricted description about the study area, geology, and general hydrology and also bears the major objectives and scope of the present study.