How many seats will the Conservative Party win in Canada’s April 28, 2024 parliamentary election?
Here’s what Jeremy‘s latest version of his Multi-AI Oracle says:
Obtaining outside data. Checking internet sources, using keywords: Conservative Party Canada election. Results from around the web:
{think}
Okay, let’s tackle this query about the current web results related to “Canada Conservative seats.” The user wants a summary from news sites, Wikipedia, official party websites, and prediction markets, plus any relevant tables, including time series data if possible.
First, I’ll check the provided search results. The Wikipedia pages [1] and [2] give details on the 2025 election, candidates, and party standings. Result [3] mentions the dissolution of Parliament and the standings at dissolution. The CTV News article [4] provides recent polling data showing the Conservatives at 39% nationally, which is a 14-year high. The National Post article [5] has seat distribution info: Conservatives at 120 seats before dissolution.
The user also mentioned prediction markets, but none of the provided sources include data from Kalshi, Metaculus, or Polymarket. The arXiv paper [6] discusses benchmarks but doesn’t relate to Canadian politics. So, I can’t include prediction market data, but I’ll focus on the available polls and seat counts.
I need to structure the answer with a summary, key findings, and tables. The summary should highlight the Conservative’s current standing, polling trends, and regional support. The key findings will cover the polling numbers, seat distribution, regional breakdown, leader preferences, and methodology.
For tables, I’ll present the national polling averages and regional support from the CTV article. The seat distribution from the National Post and the previous election results from Wikipedia will be another table. Time series data isn’t available in the sources, so I’ll note that it’s not present.
Citations should be correctly placed after each relevant fact. I’ll make sure to mention the sources for each piece of data, using [1], [4], [5], etc., as needed. Since there’s no prediction market data, I’ll exclude that part but clarify it’s not available in the provided sources.
Double-checking all numbers against the sources to ensure accuracy. For example, the CTV article says Conservatives are at 39%, Liberals at 44%, which aligns with the polling table. The seat counts from the National Post match the pre-dissolution numbers.
Finally, wrap up the answer with a concise summary of the Conservative Party’s position based on the available data, highlighting their strong performance but challenges in reaching a majority.
The 2025 Canadian federal election is set for April 28, with the Conservative Party of Canada (CPC) positioned as the main opposition to the incumbent Liberals. Current polling and seat projections indicate a competitive race, though the Conservatives face challenges in converting increased popular support into a parliamentary majority. Below is a synthesized analysis of available data:
—
### **Key Findings on Conservative Seats and Polling**
**1. National Polling Trends**
– The Conservatives currently poll at **39% nationally** (a 14-year high for the party in an election cycle), trailing the Liberals by 5 points (44%)[4].
– Regionally, CPC support dominates in the Prairies (60%) and is competitive in British Columbia (39%), but lags in Ontario (40%), Quebec (22%), and Atlantic Canada (33%)[4].
**2. Seat Distribution Pre-Dissolution**
*Source: House of Commons data at dissolution [3][5].*
**3. Historical Context**
– The Conservatives won 119 seats in the 2021 election[1]. Their current 120 seats reflect minor gains from defections and by-elections.
– To secure a majority, the CPC needs **172 seats** (up from 170 in 2021 due to redistricting)[1][5].
**4. Regional Breakdown of Support**
*Data from Nanos Research (April 12–14, 2025) [4].*
**5. Leadership Preference**
– Mark Carney (Liberal) leads Pierre Poilievre (CPC) by **16 points** (49% vs. 33%) as preferred Prime Minister[4].
—
### **Challenges for the Conservatives**
– **Gender Gap**: Only 27% of women support the CPC vs. 55% for Liberals[4].
– **Age Divide**: Leads among voters under 35 (1% margin) but trails by 17 points among those aged 55+[4].
– **Quebec Weakness**: CPC support in Quebec (22%) is less than half of Liberal support (44%)[4].
### **Methodological Notes**
– Polling data from Nanos Research (n=1,285, ±2.7%)[4].
– Seat projections remain speculative due to Canada’s first-past-the-post system and regional concentration of votes.
The Conservatives’ 39% national support marks their strongest position since 2011, but seat math and regional disparities suggest a minority government is the most likely outcome.
OpenAI gives a base rate of probability of Conservatives gaining more than 240 seats: Historical data suggests that despite strong overall numbers, the Conservatives may fall short of the 172 seats needed for a majority.
The question difficulty is rated 7 (0 to 10)
Sufficient news to provide a good forecast? 0 (0 or 1)
News is relevant, topical and unbiased? 1 (0 or 1)
Question classification: scenario_based_forecast
Expected time (days) until question close: 12
The following were considered in order to (fail to) produce this base rate:
Considering historical election data, the Conservatives have traditionally struggled to convert popular vote into a majority due to regional vote concentration. Their current polling at 39% suggests they are competitive but face an uphill battle for additional seats, particularly in Quebec and Atlantic Canada.
Ideally, the news feed would contain the following sorts of information for a better forecast:
Detailed regional analysis showing district-level support, more granular polling data indicating shifts in public sentiments, and any pre-election events affecting key demographics’ voting intentions would enhance forecast accuracy.
Some potential divergent considerations that might affect the base rate:
Current polling trends could shift due to unforeseen events or scandals impacting other parties. Additionally, regional issues may become more pronounced, affecting traditional voting patterns in the Conservatives’ favor. Voter turnout, particularly among demographics favoring the Conservatives, could also impact results.
The following chain of events are necessary for the question to resolve positively (Carolyn’s note: “positive” refers to the Conservative Party’s chances of winning):
–The Conservative Party of Canada gains enough popular support in key battleground provinces to achieve a majority in Parliament. Low
– Swing voters, especially in Ontario and Quebec, shift significantly towards the CPC in the days leading up to the election. Moderate
– A significant uptick in Conservative campaign effectiveness or major setbacks for the Liberal Party, influencing public opinion dramatically in favor of the Conservatives. Low
Querying Claude (AI predicts: [“less than 172”: 0.45, “between 172 and 205”: 0.35, “between 206 and 240”: 0.15, “more than 240”: 0.05] – confidence: 6)
Querying Mistral (AI predicts: [“less than 172”: 0.5, “between 172 and 205”: 0.3, “between 206 and 240”: 0.15, “more than 240”: 0.05] – confidence: 6)
Querying OpenAI (AI predicts: [“less than 172”: 0.25, “between 172 and 205”: 0.45, “between 206 and 240”: 0.2, “more than 240”: 0.1] – confidence: 6)
Question Type: Multiple Choice
Confidence: 6
MAPD: Avg: 0.083333333333333, Max: 0.16666666666667
# LLM responses: 3
Model value:
* less than 172: 45%
* between 172 and 205: 35%
* between 206 and 240: 15%
* more than 240: 5%
The Conservative Party is polling at a 14-year high of 39% nationally; however, they face challenges in translating this into a majority due to their uneven regional support. While they dominate the Prairies, they struggle in vote-rich regions like Quebec and Ontario, where the first-past-the-post system requires efficient vote distribution for success. Historical data suggests that despite strong overall numbers, the Conservatives may fall short of the 172 seats needed for a majority, with predictions placing them between 172 to 205 seats, but likely less because of regional disparities. Several factors could alter these predictions, including shifts in public opinion, unforeseen campaign developments, and changes in voter turnout. The potential of late campaign events or vote splitting among opposing parties could unexpectedly benefit the Conservatives; however, current trends point towards a minority government scenario.
Guide to Jeremy’s Bots Reports (These don’t all apply to the current version of his bot.)
MAPD: Mean Absolute Percentage Deviation calculates the average percentage difference between actual values and predicted values, providing a relative measure of error.
Median: We collect the output values from the LLMs in an array. We then take the median value. This is between 0 and 1 (i.e. 0.15 = 15%).
Base rate: Currently we take OpenAI’s value as the base rate. We are working on a better value using a different prompt that takes into account process. The base rate helps to determine if the median makes sense.
SD: The standard deviation between the median and the base rate.
Confidence: We query each of the LLMs on how confident they are of their predictions (between 0 and 10) and take a median. Because the LLMs tend to be overconfident, we take anything lower than 6 as being low confidence. This factors into the overall model.
Conf Mode: Based on the confidence value. >=9 is high confidence. Below 6 is low confidence (this is also triggered by an exceptionally high SD).
Mellers: This refers to Barbara Mellers, specifically a paper she wrote that includes a formula for moving values towards an extreme (i.e. 0 or 1).
Reverse Mellers: This uses the formula from above, but with a sub-1 coefficient to move the values closer to 50%.
Theory of Mind: We ask the LLMs what they think other LLMs would predict. We hope that this makes them consider the questions more deeply.
Beta Distribution: Currently unused, but possibly of interest. This is based on the median, the base rate and the SD.
Close Type: We noticed that the appropriate base case for some questions is closer to the extremes, while others are closer to 50%. When we have a low confidence value, this helps us to determine whether to extremize or de-extremize the value. ‘A’ implies closer to zero. ‘B’ implies closer to 50%. ‘C’ implies closer to 100%.
# LLM Responses: The count of LLMs that responded. We query 5 currently, but they have a relatively high API failure rate.
Model value: For normal confidence mode, this is the median. For high confidence, this is the Mellers value. For low confidence, this is either the Mellers or Reverse Mellers (depending on the Close Type).
