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What's the rudest part of Vancouver? Locals weigh in

Hint, it's not Mount Pleasant.
Â鶹´«Ã½Ó³»­autumn
Locals voted Downtown Â鶹´«Ã½Ó³»­the rudest part of the city.

After asking what the rudest part of Metro Vancouver was, we decided to find out what locals thought the rudest neighbourhood in the city is.

Six neighbourhoods were pitted against each other, and there was an "other" option in case none of the nominees fit for voters.

As it turns out, two neighbourhoods took more than 50 per cent of the vote.

With around 27 per cent of the vote, Downtown Â鶹´«Ã½Ó³»­was named the rudest part of Vancouver, according to locals.

Yaletown was a close second though, with around 25 per cent of the vote. In both cases out-of-towners and community votes agreed.

Three other neighbourhoods, and the "other option, all finished close to each other with around 10 or 11 per cent of the vote.

Third place goes to Kitsilano, which just beat out "other" as both finished with just above 11 per cent. Kerrisdale cracked the 10 per cent mark to take fifth, and the West End finished sixth.

For those of you who live, work, or spend time in Mount Pleasant, there's some good news. It seems few people consider it a rude neighbourhood, as it garnered under five per cent of the vote.

Â鶹´«Ã½Ó³»­ polled 878 Â鶹´«Ã½Ó³»­ readers and asked the question: What's the rudest neighbourhood in Vancouver?

The poll ran from 9/17/2023 to 9/22/2023. Of the 878 votes, we can determine that 515 are from within the community. The full results are as follows:

Downtown 26.80 % local, 28.13 % total    
Yaletown 25.44 % local, 24.60 % total    
The West End 10.10 % local, 9.00 % total    
Kitsilano 11.65 % local, 11.62 % total    
Mount Pleasant 4.47 % local, 4.44 % total    
Kerrisdale 10.10 % local, 10.93 % total    
Other 11.46 % local, 11.28 % total    
  Local   Total

Results are based on an online study of adult Â鶹´«Ã½Ó³»­ readers that are located in Vancouver. The margin of error - which measures sample variability - is +/- 3.31%, 19 times out of 20.

Â鶹´«Ã½Ó³»­ uses a variety of techniques to capture data, detect and prevent fraudulent votes, detect and prevent robots, and filter out non-local and duplicate votes.