Computational & Quantitative Social Sciences Grant

*** Please note: The deadline for this call has now passed. Thank you to all the applicants and for your interest. The below information is being left up for reference.***

Overview

Value and Duration
CDN $10,000 for up to 12 months
Application Deadline
This competition is currently not accepting new proposals

Purpose

The Data Sciences Institute (DSI) is a central hub and incubator for data science research, training, and partnerships at the University of Toronto. Its goal is to accelerate the impact of data sciences across disciplines to address pressing societal questions and promote positive social change.  

The DSI at the University of Toronto Scarborough, DSI@UTSC, is a tri-campus initiative to encourage research activity in Computational and Quantitative Social Science (CQSS) that includes grant support for research funding, training, and community-building. 

The social sciences are undergoing a data sciences revolution spurred on by new statistical and algorithmic techniques, rapid advances in high-performance computing, and the proliferation of large, complex, and heterogeneous data structures (e.g., spatial, relational, temporal, and textual). These developments present exciting opportunities as well as new challenges for social scientists.  

The purpose of the DSI Computational and Quantitative Social Science grant is to capitalize on these changes by providing seed funding to cutting-edge, high-impact research in the area of computational and/or quantitative social science.  

Single applicants proposing projects in the domain of computational and/or quantitative social science can apply for this grant. Funds of up to $10,000 can be used over 12 months by successful applicants. The DSI will fund at least five projects each year and will hold rolling calls until our annual funding is used.  

Ideal candidates are developing or applying statistical, mathematical, or computational methods to uncover new findings relevant to social scientists. Successful applicants should state clearly the novelty of the method and/or application as well as the expected substantive payoff of their project in a given social science field or subfield. Applicants may be from any field of study but the relevance of their project for social science research must be clearly stated. Applications will be evaluated on the novelty of their proposed method and its application to social science research. 

Eligible expenses are to be consistent with the appropriate tri-agency guidelines for NSERC Discovery grants, CIHR Project Grants or SSHRC Insight grants, with the exception of laptops which should only be included in application budgets when required for project-specific purposes (as opposed to general research). Proposals should clearly describe what role all research personnel will play in the research project. Questions on eligible expenses should be directed to awards.dsi@utoronto.ca 

Successful applicants will be required to: 

  • Present their research at a future DSI workshop or seminar (with logistics supported by the DSI@UTSC).
  • Engage with other members of the DSI community to develop a DSI Catalyst Grant application with a new Collaborative Research Team (CRT). 
  • Generate a public end product, including but not limited to one or more white papers, policy papers, contributions to conference proceedings, open-source software packages, or appropriate journal publications. 

In addition, awardees may be called upon to act as reviewers for future DSI award competitions.

The DSI is strongly committed to diversity within its community and especially welcomes applications from racialized persons / persons of colour, women, Indigenous / Aboriginal People of North America, persons with disabilities, LGBTQ2S+ persons, and others who may contribute to the further diversification of ideas.

How to Apply

The award is open to applicants who meet the following criteria:     

*Faculty budgetary appointments for the University of Toronto are continuing, full-time academic appointments with salary commitments from a University of Toronto academic unit. 

Applications are submitted via the DSI Good Grants application portal.

Register an account and select “Start Application” for “Computational & Qualitative Social Sciences.”

DSI Good Grants Dashboard

The application is divided into tabs; each tab includes a set of instructions and fields to fill out. These instructions are also highlighted below.



Applicants will need to complete the following fields.

Tab 1: Start Here

  • Project Title
Tab 2: Applicant Information You will need the following information:
  • Name
  • Email
  • Institution
  • Division (if applicable)
  • Unit (if applicable)
Tab 3: Proposal Objectives & Impact (maximum 500 words): comment on the following:
  • Project rationale and alignment with the DSI mission
  • Relevance to the DSI Thematic Programs in Reproducibility or Inequity, if applicable
  • Research objectives
  • Impact on the social sciences
Methods (maximum 500 words): comment on the following:
  • Research approach
  • Explanation of how the method or application is novel for the social sciences
EDI Statement (maximum 500 words): summarize the impact of the EDI components of this proposal. This response can focus on your integration of EDI considerations into your research question and methods and/or any EDI-related social outcomes from your research.

Figures & Supporting Material (maximum 1 page): upload a 1-page .pdf with figures and supporting material.

Unit Head Signatures: Please fill out the provided template, convert to .pdf, and upload the unit head signature for the PI.

Tab 4: CVs

Using the provided template, upload the PI's CV.

Once the applicant has submitted their component of the application on or before November 10, the following will occur:

Demographic Survey

The applicant or the person submitting on their behalf will receive a confirmation email that includes a link to a Demographic Survey. While this survey is required, when filling it out respondents have the option to select “Prefer not to answer” for all questions. The applicant has until November 17 to fill out the survey.

The DSI will form a Review Committee to lead the review of all eligible proposals received by the submission deadline. Reviewers are asked to consider the following categories:

  • Project rationale and the extent to which it aligns with the DSI mandate including, if applicable, alignment with the DSI Thematic Programs in Reproducibility or Inequity.
  • The potential impact of the proposal on social science research.
  • The extent to which the proposed project includes the development of novel methodology or the innovative application of existing approaches in the context of the social sciences.
  • The extent to which the project considers how to advance EDI in research and outcomes.

All application materials can be submitted directly onto the form. Certain fields on the form ask for uploads and require the following templates:

Past Recipients

Round 2

Angelina Grigoryeva (Department of Sociology, University of Toronto Scarborough, University of Toronto): “New Money in the New Economy: The Shift to Stock-Based Compensation and Wealth Inequality.”

Monica Ramsey (Department of Anthropology, University of Toronto Mississauga, University of Toronto): “Deep Learning in Archaeology and Paleoethnobotany: Imaging Phytolith Training Data.”

Round 1

Monica Alexander (Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto): “Deficits of migration in the age of Covid-19: A new approach to studying changing migration patterns.”

Spike W. S. Lee (Joseph L. Rotman School of Management, University of Toronto): “What Do Fake News and Biased News Look Like? A Text-Analysis and Machine-Learning Approach.”

Zahra Shakeri (Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto): “Social and Behavioural Determinants of Health in Prognostic Machine Learning Models for Patient Outcome Prediction.”

Further Information

For more information, please contact awards.dsi@utoronto.ca.