This course will emphasize the molecular biology principles and mechanisms underlying the toxicity of drugs and foreign agents. A journal club format is used to examine and critically evaluate the current hypotheses that explain the events at the molecular level which determine and affect toxicity. This course is suitable for graduate students of pharmacy, toxicology, pharmacology, biochemistry, environmental science, pathology, neuroscience, and medical biophysics. A weekly journal club will also be held after the lectures.

This course provides an introduction to quantitative methods of inquiry and a foundation for more advanced courses in applied statistics for students in education and social sciences. The course covers univariate and bivariate descriptive statistics; an introduction to sampling, experimental design and statistical inference; contingency tables and Chi-square; t-test, analysis of variance, and regression. Students will learn to use SPSS software. At the end of the course, students should be able to define and use the descriptive and inferential statistics taught in this course to analyze real data and to interpret the analytical results.

This course will cover: survey sampling, experimental design, and power analysis; analysis of variance for one-way and multi-way data with fixed, mixed, and random effects models; linear and multiple regression; multiple correlation; analysis of covariance.

An exploration of the history and current use of survey research in educational leadership and policy. Topics will include an assessment of the strengths and limitations of the method survey, the selection of samples, questionnaire design, standard measurement instruments used in the field, methods of data analysis (with a focus on using SPSS), the drawing of causal inferences, and presentation of results in a clear and effective manner.

This is an intermediate applied statistics course designed for students who have already taken one course in elementary concepts (e.g., sampling and statistical inference). The course covers the use, interpretation, and presentation of bivariate and multivariate linear regression models, curvilinear regression functions, dummy and categorical variables, and interactions; as well as model selection, assumptions, and diagnostics. Examples and assignments will draw from commonly-used large-scale educational datasets. Students are encouraged to use Stata; the course will also serve as an introduction to this software package (students may instead choose to use SPSS or other software they are familiar with). The objective of the course is to equip students with the skills to use, interpret and write about regression models in their own research.

This is an advanced applied statistics course designed for doctoral or advanced master’s students and serving as a comprehensive introduction to multilevel modelling, also known as “hierarchical linear modelling (HLM)” or “mixed effects modelling.” These powerful models have become very common in educational research, both for the analysis of data with a multilevel structure (e.g., students nested in schools, school boards, provinces or countries) and for the study of educational change (e.g., student learning/growth, school improvement or organizational change). The course covers two-level and three-level cross-sectional and growth curve models, as well as model selection, assumptions and diagnostics. Examples and assignments will draw on data from large-scale national and international datasets; the course will also serve as an introduction to the HLM7 software package. The objective of the course is to equip students with the skills to use, interpret and write about multilevel models in their own research. Pre-requisite: An intermediate statistics course such as JOI3048H, JOI1288H or equivalent

This course will prepare students to conduct quantitative data analysis for a thesis, dissertation, journal article, or policy report. Students should enter it with 2 pre-requisites: an introductory statistics course, and an intermediate statistics course. They will require knowledge of descriptive statistics, inference and basic regression techniques. This course has 2 broad learning goals. First, it will expose students to 3 advanced statistical techniques and procedures: categorical data analysis, with a focus on logistic regression; causal inference, with a focus on propensity score matching, and missing data analysis, with a focus on multiple imputation. Please note course topics will lean towards sociologically-oriented educational research, and will not cover detailed issues in psychometrics or econometrics. Second, students will receive guidance in the management and analysis of large data sets, including administrative and survey data, and will become acquainted with STATA statistical software. The major assignments will be cumulative in nature, with the final assignment consisting of original data analysis written in the format of a journal article, dissertation/thesis chapter, or technical report that applies each of the above-mentioned statistical techniques. Students can use their own data if they wish, but can also get access to several educational data sets that will be available through the Data, Equity and Policy in Education [DEPE] Lab (www.oise.utoronto.ca/depelab/).

Mixed methods research is increasingly being used as an alternative to the traditional mono-method ways of conceiving and implementing inquiries in education and social sciences. In conceptualizing mixed methods studies, various paradigmatic assumptions are still being debated. However, many researchers have stated that the paradigmatic differences have been overdrawn and that paradigmatic incompatibility makes dialogue among researchers less productive. Researchers further acknowledge that philosophical differences are reconcilable through new guiding paradigms that actively embrace and promote mixing methods. Mixed methods researchers reject traditional dualism and prefer action to philosophizing by privileging inquiry questions over assumptive worlds. In this course, students will be introduced to various mixed methods design alternatives that allow researchers to link the purpose of the research to methodologies and integrate findings from mixed methods. This course covers various phases of mixed methods research, including theoretical frameworks of mixed methods research designs, strategic mixed methods sampling, data collection methods, integrative data analysis strategies, and a mixed methods research proposal. This is a doctoral level course designed to serve students who plan to conduct independent research. I anticipate that students will have had prior research experience or course work in research methods.

This course is designed to provide students with a working knowledge of the concepts related to systematic review and meta-analysis and develop their skills in this research methodology. Specifically, this course covers the topics of formulating the research questions that can be answered with systematic reviews, perform the literature search, select the studies and critically evaluate them using the quality, inclusion and exclusion criteria, extract data on key elements of the studies, outcomes and relevant statistics, compute and convert various effect size indices, synthesize the results of the studies with meta-analysis techniques, and present the results. The focus of the course is both methodological and practical.

Special topics courses designed to permit the study (in a formal class setting) of advanced quantitative research methods.

A critical reading of Don Quixote, with particular attention to the text's engagement with the thought and institutions of Renaissance humanism. Class discussion will focus first on Cervantes's response to the ethical critique of imaginative literature, and proceed to his treatment of such topics as the theory of war and peace, the education of princes, and the duties of the good governor. Selected episodes from Don Quixote will be studied in conjunction with readings from influential Renaissance authors (Castiglione, Erasmus, Vitoria, Machiavelli).

Books and readers are constant preoccupations in Cervantine fiction. This seminar will examine such issues in detail, with a specific focus on Don Quixote. Our point of departure will be a sequential reading of key episodes from both parts of the novel, centering on the literary genres that inform and shape Cervantes’s writing (chivalric and Greek romance, pastoral, epic, picaresque fiction, Renaissance lyric) and on the representation of readers and the reading process in the text. Attention will also be given to literary techniques closely associated with Cervantes: generic mixing, the interplay of narratives and narrative voices, literary parody, the various kinds and uses of irony. Some readings will be drawn from other works of Cervantes, particularly the Exemplary Stories. The interrelated practices of reading and storytelling will be central to our scrutiny of Cervantes's fiction. Students will be encouraged to consider modern authors as readers of Cervantes and as contributors to the novelistic tradition that he initiates.

This is a unique course that consists of three components. In the first month, students attend a half dozen didactic lectures introducing the surgical environment, basic instruments, and principles of asepsis. These lectures are given by surgeons and instructors at the Surgical Skills Centre and will include a group observation of a live surgery with play by play commentary. In the second part of the course, students will attend a handful of observerships of live surgeries, at different participating hospitals. These observerships typically range from 4 to 8 hours. Students will be required to document a subset of surgeries, focusing particularly on technologies deployed, underlying scientific principles, their limitations, surgical workflow, and ideas/designs for improvement. The final part of the course consists of a project where each student will write a short paper on an engineering topic related to surgery. At the end of the course, students present their projects before an interdisciplinary panel of academic clinical engineers and surgeons.

Current geophysical surface and borehole methodologies (gravity, magnetics, electrical, electromagnetic, nuclear) and their theoretical basis for investigating Earth's interior to depths ranging from several metres to tens of kilometres.

This course starts with an introduction to strain and stress, and derives the seismic wave equation. Ray theory is then covered to explain travel times and amplitudes of seismic arrivals leading to the concept of seismic tomography methods for mapping earth's internal structure. Finally the seismic source theory and earthquake source mechanisms are discussed. Subjects such as exploration reflection and refraction seismic methods, digital seismic data processing will also be covered by the course.

This is an advanced seismology course that covers a range of theoretical and computational topics related to seismic wave propagation, seismic tomography, full-waveform inversion, earthquake sources and fault dynamics, as well as exploration seismology. Detailed topics may vary based on instructors.

With over half of the population on this planet being urban, the significance of improving our understanding of cities in a global context has never been greater. This course is designed to improve awareness of cities as approached by different disciplines and in different international contexts.

The core issues confronting city leaders across the globe are examined in comparative perspective and in a context of shifting global agendas. The study of cities of Latin America, Asia, and Africa, are brought together in comparative context with the study of cities of Europe and North America.

This course supports students in attaining rigorous qualitative research skills that will complement their research interests, assist in developing dissertation/thesis proposals, and contribute to preparing for a career as educators and scholars in academia and beyond. The course aims to develop a deep understanding of a range of qualitative research methods and their epistemological foundations. Readings and discussions will be oriented to probing the epistemology and ontology of knowledge in support of the formulation of robust research design. Readings reflect an understanding that doctoral planning and geography students commonly conduct ethnographic research in transnational and multicultural settings, which requires an ability to read and interpret complex meanings, as well as attend to the politics of knowledge production. Debates surrounding the production of ethnographic data will also be emphasized, including those concerning researcher positionality, reflexivity, ethics, and writing.

This course will train students to analyze qualitative data and write up findings from their research. It is designed for students who have already taken a qualitative methods course that provides training on data collection, such as interviewing, ethnographic observation, conducting focus groups, or discourse analysis. Our course will focus exclusively on the data analysis and writing phase and will help students to work with and interpret their data.

This course will introduce qualitative data analysis as a collaborative process that happens through intensive engagement, sharing, and revising of one's ideas and arguments. Thus, the class will involve a series of workshop and writing activities. Students will comment on each other’s work in class and through written peer-review exercises. Conceptualizing qualitative research as a community effort, we will spend significant time learning how to provide and receive helpful feedback and build peer support networks while in grad school.

This course aims to provide a comprehensive understanding of statistical methods for graduate students required to i) quantify relations and dependencies between variables and ii) conduct statistical tests in a variety of applications related to the Canadian urban system. The topics of the course include probability distributions, statistical testing and inference, as well as linear and some non-linear, simple and multiple regression and correlation techniques. The application of these methods through the use of statistical software (primarily SPSS) — both menu- and code-based — will also be part of the course. Students are required to have some background knowledge of research design, basic descriptive statistics, testing and regression analysis at the undergraduate level.

Spatial Analysis consists of set of techniques used for statistical modeling and problem solving in Geography. As such, it plays an integral role in the detection of spatial processes and the identification of their causal factors. It is therefore a key component in one’s preparation for applied or theoretical quantitative work in GIScience, Geography, and other cognate disciplines. Space, of course, is treated explicitly in spatial analytical techniques, and the goal of many methods is to quantify the substantive impact of location and proximity on human and environmental processes in space.

This course is concerned with the ways in which natural resource policies governing use, access, and control of resources are imbued with and reproduce conflict. Through a variety of case studies and theoretical engagements (feminist, postcolonial, anti-racist, Marxist, post-humanist), this course examines how natural resource conflicts are shaped by multiple kinds of power. In this course we discuss how such contests are more than political economic struggles. Through attention to the entanglements of environment, difference and struggle, a core aim of this seminar is to interrogate what is given and taken-for-granted within dominant narratives, instruments, and institutions shaping land and territorial demarcation, water access and distribution, livelihood (in)security, oil and mineral extraction, biodiversity conservation, and struggles over urban citizenship. While this course looks to make visible how states and elites shape space through natural resource control, simultaneously, it attends to how people and their communities work to defend and remake their lives and livelihoods in the face of displacement and dispossession.

This course focuses on the recent efforts to 'green the city' by integrating green infrastructure into the built environment, including emerging research supporting such initiatives. The course begins by examining greening goals associated with ecosystem service provisioning, individual and community well-being, environmental justice, and urban resiliency in light of climate change. The role of urban planners, municipal policy, private property owners, and other key actors will be examined in-depth. Throughout the course, issues associated with bridging knowledge gaps between the social and natural sciences, unique characteristics of urban ecosystems, and the role of specific decision-makers will be considered.

Agrifood systems, connecting production and consumption, markets and various types of agrarian labour, are undergoing profound social and ecological change. In trying to make sense of these changes, and the various social movements that have e merged in their wake, this course deploys the related paradigms of agrarian political economy and political ecology to analyze the forces and social relations that define land-based and food-focused transformations, both historically and in the contemporary moment. The course examines the often forgotten roots of contemporary debates in political ecology and food, that is, the enduring agrarian question. The agrarian question examines the extent to which capital has transformed agricultural production and the degrees to which producers have been able to resist dispossession and the industrialization and capitalization of agriculture. The course starts with foundational perspectives on the agrarian question, the renaissance of these debates in the 1970s and 1980s and the emergence during this time of political ecology as a critical approach to the study of food and land- based practices. The course also tackles a number of defining contemporary developments that are reshaping the meaning and character of land and food.