Training in community psychology at Wilfrid Laurier University: A process and outcome evaluation (Ontario)

There is to date no Canadian example of a systematic evaluation of a community psychology training programme, and the literature reveals few evaluations in the U.S. This paper describes an evaluation of the Community Psychology M.A. Programme at Wilfrid Laurier University (WLU). A utilization-focused stakeholder model was used, whereby I worked closely with faculty, students, some support staff, and a graduate of the programme throughout the entirety of the evaluation. Because community psychology is strongly committed to process, both outcome and process goals were given equal emphasis. In addition, other aspects such as student satisfaction, course effectiveness, and an exploration of students’ perceptions and feelings about the programme were examined. Both qualitative and quantitative data were collected from graduates, faculty, support staff, and students. Following feedback of the results, faculty and students identified the major issues developed their own recommendations, I provided my own recommendations, and based on this the programme embarked on the process of change. The results of the evaluation indicated that the programme is effective in meeting its outcome goals, but that there is room for improvement in how it is incorporating the values and beliefs of community psychology into the process of training. The major themes of the process results included: a lack of support for second-year students, competitiveness amongst students, a lack of resources for faculty and students, a weakness in the programme’s attention to gender and multicultural issues, and continual improvements in the programme in attending to process issues. This evaluation was provided a comprehensive and detailed view of the processes and outcomes of a community psychology training programme. This process has encouraged growth and development in the programme at WLU and hence, has hopefully provided some confirmation of the importance of community psychology’s stated commitment to self-appraisal and evaluation. What this evaluation has provided for WLU’s programme, more widespread evaluations of community psychology training programs can provide for the field as a whole. That is, more extensive, close attention to the processes and outcomes of training programmes would help the field see its strengths and weaknesses and would contribute to the development of the subdiscipline as a whole

Processus de différenciation et compétences langagières: expertise et formation dans les métiers de service en restauration

Grounded in the field of interactional linguistics applied to professional practices and training, our study is based on a two-year ethnography of communication of the table waiting vocational training in restaurant-schools at the Paul Bocuse Institute (Ecully, France). This contribution addresses the processes of differentiation that lead to distinguish an expert maître d'hôtel from a non-expert. To this end, after a short presentation of our study, we first report on educational choices related to table waiting skills training that focus on the mastery of technical gestures. Second, in comparison, we examine work expertise, crucially based on interactional competencies that are overshadowed in the training. Third, we discuss the contradictory phenomena observed and consider their consequences and stakes in terms of training and professional identity

Compétences interactionnelles et métier de service en restauration : les enjeux méthodologiques d’un corpus complexe

International audienc

Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation. Temporal data arise in these real-world applications often involves a mixture of long-term and short-term patterns, for which traditional approaches such as Autoregressive models and Gaussian Process may fail. In this paper, we proposed a novel deep learning framework, namely Long- and Short-term Time-series network (LSTNet), to address this open challenge. LSTNet uses the Convolution Neural Network (CNN) and the Recurrent Neural Network (RNN) to extract short-term local dependency patterns among variables and to discover long-term patterns for time series trends. Furthermore, we leverage traditional autoregressive model to tackle the scale insensitive problem of the neural network model. In our evaluation on real-world data with complex mixtures of repetitive patterns, LSTNet achieved significant performance improvements over that of several state-of-the-art baseline methods. All the data and experiment codes are available online.Comment: Accepted by SIGIR 201

Symbiose et circulation dans Of Mice and Men de John Steinbeck

Cet article évoque, à partir d’exemples tirés du texte, la relation symbiotique qui unit George et Lennie, les deux personnages principaux de Of Mice and Men. En s’appuyant sur les travaux de plusieurs scientifiques (Ritter, Allee, Darwin) et sur le concept d’animal politique d’Aristote, il met en avant l’aspect mutualiste de cette relation qui provient principalement de la circulation de ce couple symbiotique dans l’espace américain.Relying on the text, this essay highlights the symbiotic relationship which unites George and Lennie, the two main protagonists in Of Mice and Men. It is based on the works of several biologists and naturalists, including Ritter, Allee and Darwin, as well as on Aristotle’s political animal theory, which all participate in showing that the mutualistic aspect of this symbiotic relationship comes from the fact that Lennie and George are constantly on the move

Harnessing indigenous knowledge and practices for effective adaptation in the Sahel

The Sahel region of West Africa has experienced some of the most severe multidecadal rainfall variability over the past 50 years. Based on recollections of the past and observations of the present, local communities in the Sahel have developed extensive knowledge and understanding of their environment and climate that enables them to harness ecosystem services to support their livelihoods and survive environmental changes. Recent literature indicated that farmers’ knowledge and perceptions of changes in the local climate are largely consistent with observed meteorological data, except for the more heterogeneous precipitation change. This understanding of changes in their environment combined with their indigenous knowledge can be particularly useful in data-sparse regions such as the Sahel. This review highlights the importance of indigenous knowledge in enabling effective adaptation in the Sahel and beyond. It outlines some future research avenues for fostering indigenous knowledge-based adaptation, including addressing barriers to mainstreaming of indigenous knowledge into climate research and policy

Technologies and practices for agriculture and food system adaptation to climate change in The Gambia

Agriculture is a major source of livelihood and income in The Gambia. Despite its socioeconomic importance, the sector faces many institutional, technological, and biophysical challenges limiting its contribution to economic development. The situation is exacerbated by adverse effects of climate change, which is undermining national efforts, making The Gambia one of the most vulnerable to climate change. This report documents and synthesizes available climate-smart agriculture (CSA) options that can inform adaptation planning in The Gambian agriculture and food system. We analysed the relevance of the documented options in sustainably increasing productivity and income while building climate resilience and reducing GHGs emissions in food systems. Through a mixed approach integrating multiple sources, a total of 28 technologies and practices has been identified as relevant adaptation options for The Gambia agriculture and food system. These options are grouped into nine adaptation categories including Crop diversity use and management, Soil and nutrient management, Soil & Water Conservation and Irrigation, Agroforestry systems, Livestock-based systems, agro-climatic information services, Social network and institutional support, and Livelihood diversification. Except for post-failure coping strategies known to be ineffective and unsustainable, all the identified options have some potentials to sustainably increase agricultural productivity and income while adapting and building resilience to climate change and reducing greenhouse gas emissions. This synthesis provides evidence of potential climate-smartness of the selected adaptation options and could be important to inform adaptation planning and prioritization