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Copyright of Canadian Journal of Information & Library Sciences is the property of Canadian Association for Information Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This article delves into the issues of equity, diversity, and inclusiveness (EDI) in the engineering disciplines in Canada and Spain and presents the challenges faced by underrepresented individuals and ways to promote an inclusive and diverse environment. Two strategic lines are identified: (a) facilitating university education access to underrepresented and minority groups and (b) guiding such students during university training to set them up for successful future careers. Accordingly, this article shows how the strategies mentioned above are implemented in some selected Canadian and Spanish universities, clearly distinguishing the approach taken in the two countries. In Canada, there is a more decentralized approach to addressing EDI issues, wherein the universities devise their agendas independently. In Spain, on the other hand, there is a stronger and more direct involvement of the government to ensure a comprehensive, system-wide approach to tackling EDI issues in academia. This article helps education policymakers to devise and implement pragmatic strategies for achieving EDI and the relevant UN-defined sustainable development goals. [ABSTRACT FROM AUTHOR]

Purpose Expanding networks of data portals and repositories linked to electronic patient record systems, along with advances in information technology, have created both new opportunities in improving public health and new challenges in protecting patient privacy. The purpose of this paper is to review stakeholder perspectives and provide a framework for promoting implementation of current privacy protection improvement recommendations.Design/methodology/approach This paper summarizes a workshop session discussion stemming from the 2017 Information Technology and Communication in Health (ITCH) biennial international conference in Victoria, British Columbia, Canada. The perspectives within health service research, journalism, informatics and privacy protection were represented.Findings Problems underlying gaps in privacy protection in the USA and Canada, along with then-current changes recommended by public health leaders as well as Information and Privacy Commissioners, were identified in a session of the 2015 ITCH conference. During the 2017 conference, a workshop outlined the current situation, identifying ongoing challenges and a lack of significant progress. This paper summarizes that 2017 discussion identifying political climate as the major impediment to progress on this issue. It concludes with a framework to guide the path forward.Originality/value This paper provides an international perspective to problems, resources and solution pathways with links useful to readers in all countries. [ABSTRACT FROM AUTHOR]

Studies of clinical populations that combine MRI data generated at multiple sites are increasingly common. The Canadian Biomarker Integration Network in Depression (CAN-BIND; www.canbind.ca) is a national depression research program that includes multimodal neuroimaging collected at several sites across Canada. The purpose of the current paper is to provide detailed information on the imaging protocols used in a number of CAN-BIND studies. The CAN-BIND program implemented a series of platform-specific MRI protocols, including a suite of prescribed structural and functional MRI sequences supported by real-time monitoring for adherence and quality control. The imaging data are retained in an established informatics and databasing platform. Approximately 1300 participants are being recruited, including almost 1000 with depression. These include participants treated with antidepressant medications, transcranial magnetic stimulation, cognitive behavioural therapy and cognitive remediation therapy. Our ability to analyze the large number of imaging variables available may be limited by the sample size of the substudies. The CAN-BIND program includes a multimodal imaging database supported by extensive clinical, demographic, neuropsychological and biological data from people with major depression. It is a resource for Canadian investigators who are interested in understanding whether aspects of neuroimaging — alone or in combination with other variables — can predict the outcomes of various treatment modalities. [ABSTRACT FROM AUTHOR]

This article expands understanding of gender and advancement in academic science by going into a new dimension of inquiry: Focusing on women associate professors in computing, it assesses the relationship between perceived chances for promotion to full professor and indicators of entrepreneurship, as part of key sets of individual and departmental independent variables that are also addressed. Data from a national survey of women in academic computing indicate that time spent in entrepreneurial activity does not predict excellent/good (compared to fair/poor) chances for promotion perceived by these women faculty, nor does the quantity/quality of entrepreneurial activity that they report for their home units. Departmental reward structures reported as favoring entrepreneurial activity negatively predict perceived chances for promotion. Other key individual and departmental characteristics also predict chances for promotion: faculty members' age, collaboration, family characteristics, departmental climate, and US (compared to Canadian) location. Findings from interviews with a small subset of respondents to the survey illuminate the survey findings on the role of entrepreneurial factors in perceived chances for advancement. [ABSTRACT FROM AUTHOR]

In 1965, four undergraduates at the University of Waterloo wrote Watfor, a fast student-oriented Fortran compiler for the school's IBM 7040, largely because the available Fortran compiler was slow and offered weak diagnostic and debugging tools. This article describes the birth and evolution of the Watfor family and explores how it fits into the University of Waterloo's unique-within-Canada cooperative education program and pedagogical philosophy. [ABSTRACT FROM PUBLISHER]

Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada's land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative-or 'exemplar'-from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada's ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada's forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach. [ABSTRACT FROM AUTHOR]

Biological data sets are increasingly becoming information-dense, making it effective to use a computer science-based analysis. We used convolution neural networks (CNN) and the specific CNN architecture Unet to study sponge behavior over time. We analyzed a large time series of hourly high-resolution still images of a marine sponge, Suberites concinnus (Demospongiae, Suberitidae) captured between 2012 and 2015 using the NEPTUNE seafloor cabled observatory, off the west coast of Vancouver Island, Canada. We applied semantic segmentation with the Unet architecture with some modifications, including adapting parts of the architecture to be more applicable to three-channel images (RGB). Some alterations that made this model successful were the use of a dice-loss coefficient, Adam optimizer and a dropout function after each convolutional layer which provided losses, accuracies and dice scores of up to 0.03, 0.98 and 0.97, respectively. The model was tested with five-fold cross-validation. This study is a first step towards analyzing trends in the behavior of a demosponge in an environment that experiences severe seasonal and inter-annual changes in climate. The end objective is to correlate changes in sponge size (activity) over seasons and years with environmental variables collected from the same observatory platform. Our work provides a roadmap for others who seek to cross the interdisciplinary boundaries between biology and computer science. [ABSTRACT FROM AUTHOR]