Employee Diversity Data Centre
“By choosing to participate in the employee self-ID, you’re choosing to stand-up and be counted as a member of your community, and by that very act you’re reminding leaders within the university that our community has specific needs, including the paramount need for safety and connection.”
6,790+ current employees completed the Diversity Self-ID
91% response rate for full-time faculty and staff
The 2020 data provides an update, while also communicating changes since 2016. The data includes information about the recruitment, representation and retention of employees from five equity groups: women, racialized people, First Nations, Métis and Inuit Peoples, persons with disabilities and 2SLGBTQ+ people. Following the 2020 release of the Anti-Black Racism Campus Climate Review Report, Black employees have also been presented as a distinct equity group so that the university can track its progress on commitments made to confront anti-Black racism and enhance Black inclusion at the university.
The data presented invites community members to explore what is working and what isn’t, to sustain and build on successes and make adjustments where necessary. In short, the data centre is a tool for university leaders, committees and decision makers to advance equity, diversity and inclusion at the university. The data does not however tell the full story of progress, or barriers that prevent progress. Therefore, diversity self-ID data should be seen as an indicator of patterns and trends in representation, recruitment and retention. These indicators suggest areas for further discussion and exploration.
The following line graph shows the representation of employees from the six equity groups at the university from 2016 to 2020, with comparison data from the GTA or Ontario and student diversity self-ID data.
- The X axis (horizontal) shows the years and the Y axis (vertical) shows the percentages.
- One line shows the employee representation and whether it went up or down over the past five years.
- The other lines show the student and community representation. Any space between the employee representation and community lines, where the where the employee representation line is below either of these lines, indicates a gap in representation.
- Employees include faculty, staff (includes full time career and long term contract employees), lecturers, student employees, research employees and casual, part-time and short term contract employees.
The data shows that representation for all equity groups has increased, in varying amounts, from 2016 to 2020. However, this high level data masks the uneven representation in different types and areas of work. To learn more about where gaps in representation exist, explore the additional sections in this diversity data centre.
Based on the university’s aspirational goal of reflecting the diversity of the broader community in our student and employee population, the data presented is compared to the diversity data of the GTA or Ontario, depending on the group. Student data by program and faculty is available in the student data visualizations.
Please note that there is no data specific to the Lincoln Alexander School of Law, which opened in fall 2020. Data about employee diversity in the law school will be included in the 2022 updates on the Diversity Self-ID website, which should be available in 2023.
The graphical illustrations facilitate an interactive experience – users can see the data that corresponds to the visual by hovering or clicking over portions of the illustration. The data can also be explored using keyboard shortcuts, external link.
To explore the data further or in a different format, the aggregated data can be downloaded and saved in a variety of formats such as Google Sheets, MS Excel, CSV and more, using the link provided at the bottom end of the graph or chart. Downloads are provided for the data in a graph or chart based on user selections. For example, for this line graph, the data provided would be for the equity group selected in the drop down menu.
This visualzation is best viewed in desktop mode.
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