This paper extends the Markov Riding Position Sampler (MaRiPoSa) algorithm to analyze fairness across multiple Canadian federal elections (2011–2025). While previous work demonstrated that alternative allowable boundary configurations could yield different governments from the same vote distribution in a single election (Cochrane & Cowan, 2026), this analysis examines whether such boundary-dependent outcomes reflect systematic patterns or isolated anomalies.

We find that there are alternative, allowable configurations of electoral district boundaries that would return different party outcomes and different governments for Canadians, without changing the votes or locations of any voters across each election. We highlight specific boundaries of these alternative districts in locales across Canada. We conclude by discussing what computational analysis of district boundaries can contribute to Canadian political science and the democratic process at both the federal and provincial levels.