Ethics
Research
A repository of peer-vetted white papers and editorial inquiries exploring the mechanics of algorithmic fairness within the Canadian labor market. We move beyond theory to define measurable equity in automated recruitment.
The 2026 Fairness
Index & Publications
Our research focuses on identifying disparate impact and mitigating bias within proprietary recruitment datasets. Each publication represents a rigorous audit of current industry standards.
The Canadian Fairness Index: 2026 Outlook
An exhaustive study of selection rates across protected groups in Canada’s top five recruitment categories. This paper adapts global fairness metrics (Equalized Odds) to specifically address provincial labor regulations.
Mitigating Proxy Variables in Automated Screening
Exploring how seemingly neutral data points (postal codes, graduation years) act as proxies for bias in the Canadian recruitment landscape.
Audit Methodology: Provincial Compliance
A breakdown of the Four-Fifths Rule adaptation for multi-stage hiring processes, vetted for statistical validity in Ontario and BC.
Statistical Neutrality in Model Tuning
A guide for data scientists on adjusting preference weights to reduce adverse impact without compromising the model's predictive utility for skill matching.
Full Documentation
A Framework
for Measured
Progress
Four-Fifths Rule Adaptation
We evaluate selection rates across various protected groups to identify adverse impact before it transforms into systemic bias. This benchmark is anchored in established Canadian labor standards.
Group Fairness Metrics
Our audits utilize a blend of Disparate Impact and Equalized Odds analysis, ensuring that the 'best fit' isn't just a shadow for 'same as before'.
Statistical Validity
Every finding we present is cleared through our internal peer-review process, ensuring that recommendation weights are mathematically sound.
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Briefing for Your Sector
Beyond our public archives, we provide customized research outputs for specific industrial hiring funnels—from financial services to high-growth tech firms. Ensure your internal data science teams are aligned with evolving Canadian ethics standards.