46 /Canada province evidence profile
Canada province evidence profile
Manitoba: a public-data profile for digital planning
Manitoba is one of 13 reviewed Canadian province profiles. Its April 2026 population estimate is 1,503,865, -0.28% from April 2025. The 2025 geography snapshot contains 23 census divisions and 241 census subdivisions linked to this province. These fields establish scale, recency and hierarchy; they do not establish buyer intent, search volume or a Mosalio location.
01 / Data snapshot
What the two reviewed Statistics Canada sources record
02 / Evidence interpretation
Three distinct readings, kept within their source limits
Population scale
Manitoba ranks 5 of 13 by April 2026 estimated population and represents +3.63% of the national estimate. That places population scale in the middle half of the reviewed set. For a public website, this is a reason to test whether broad navigation labels and search tools remain understandable across a large information space—not a reason to manufacture location pages.
One-year trajectory
The estimate changed by -4,166 people between April 2025 and April 2026, or -0.28%. This is a comparatively stable one-year population estimate and ranks 11 of 13 on the same measure. Because the 2026 estimate is preliminary postcensal data, the appropriate response is dated copy, clear source periods and a planned review cycle rather than a permanent growth claim.
Statistical geography
Statistics Canada's 2025 hierarchy records 241 census subdivisions across 23 census divisions for Manitoba, or 10.5 subdivisions per division. The subdivision count sits at the 50.0th percentile of this finite cohort. Census divisions and subdivisions are statistical geography; they are not interchangeable with cities, service areas or legal municipal status.
03 / Portfolio distinction
The three readings furthest from the 13-profile midpoint
2025 census-division count: 23
This value sits at the 73.1th percentile in the middle half of the 13-profile Canada set. Its 23.1-point distance from the portfolio midpoint makes it one of this profile's three strongest distinguishing signals; it is evidence for a design question, not proof of search demand or commercial opportunity.
one-year population change: -0.28%
This value sits at the 26.9th percentile in the middle half of the 13-profile Canada set. Its 23.1-point distance from the portfolio midpoint makes it one of this profile's three strongest distinguishing signals; it is evidence for a design question, not proof of search demand or commercial opportunity.
share of Canada's April 2026 estimate: +3.63%
This value sits at the 65.4th percentile in the middle half of the 13-profile Canada set. Its 15.4-point distance from the portfolio midpoint makes it one of this profile's three strongest distinguishing signals; it is evidence for a design question, not proof of search demand or commercial opportunity.
Complete evidence order
Read from the lowest to the highest percentile in the fixed 13-profile benchmark, Manitoba's complete evidence order is one-year population change (middle half); subdivisions per census division (middle half); 2025 census-subdivision count (middle half); distinct subdivision type codes (middle half); leading subdivision type-code share (middle half); April 2026 population estimate (middle half); share of Canada's April 2026 estimate (middle half); 2025 census-division count (middle half). Keeping this eight-measure sequence visible prevents one population, change or hierarchy value from being promoted as a market conclusion without its neighbouring evidence.
04 / Source structure
Subdivision type-code mix
The source contains 9 distinct subdivision type codes for Manitoba. Code IRI is most frequent at 90 records (+37.3%), followed by RM (62) and MU (37). The mix is distributed across several source type codes. Codes are preserved exactly and are not expanded into unverified legal labels.
- Statistics Canada code IRI
- 90 records · +37.3%
- Statistics Canada code RM
- 62 records · +25.7%
- Statistics Canada code MU
- 37 records · +15.4%
- Statistics Canada code T
- 25 records · +10.4%
- Statistics Canada code CY
- 10 records · +4.1%
- Statistics Canada code NO
- 10 records · +4.1%
- Statistics Canada code S-É
- 3 records · +1.2%
- Statistics Canada code LGD
- 2 records · +0.8%
- Statistics Canada code VL
- 2 records · +0.8%
05 / Controlled comparison
Different peers for different questions
Saskatchewan is the closest reviewed population-scale comparator. Manitoba differs by 237,773 people in the April 2026 estimates; that comparison controls for scale before teams compare navigation depth or publishing capacity.
New Brunswick is the nearest match across the 2025 division, subdivision and type-diversity fields. The difference is 132 subdivisions and 11 census divisions, so it is a practical control for testing directory depth without treating either hierarchy as a sales territory.
Newfoundland and Labrador has the closest remaining one-year population-change rate. Manitoba's rate differs by 0.0%, a narrow temporal comparison that can inform update cadence but cannot explain demand, intent or individual behaviour.
06 / Falsifiable question set
Questions to validate before changing a website
- 01
Does a 5-of-13 population position require more than one primary path to high-frequency tasks?
Test this with task completion and search-log evidence; the 1,503,865 estimate alone cannot identify user intent.
- 02
Can users understand a hierarchy spanning 23 divisions and 241 subdivisions without learning source-specific geography codes?
Prototype labels and search facets against real content. Preserve the statistical hierarchy in data, but translate it into plain interface language only after factual review.
- 03
Which claims need a visible reference date when the one-year estimate moved -0.28%?
Audit every population-dependent statement for a source period, owner and update trigger; do not turn a preliminary estimate into an evergreen trend.
- 04
Does the +37.3% leading-code share support one directory pattern or several?
Compare findability for the leading code with the remaining 8 codes. A source distribution is a test input, not a navigation decision.
07 / Practical brief
Evidence-led website planning recommendations
- 01
Keep dates attached to population statements
Label April 2025 and April 2026 explicitly, retain the preliminary-status note, and schedule review when Statistics Canada revises table 17-10-0009-01.
- 02
Model hierarchy before adding routes
Represent the 23-by-241 source structure in a content model first. Create a public URL only when it answers a distinct, validated user need.
- 03
Test against three controlled peers
Use Saskatchewan, New Brunswick, Newfoundland and Labrador as transparent comparators for scale, geographic structure and change rate. Keep each comparison tied to its stated metric.
- 04
Measure usefulness, not URL volume
Track successful task completion, qualified enquiries and content maintenance. Consolidate any route that duplicates another page or attracts no distinct user need.
08 / Method and limits
What this profile can—and cannot—support
This profile combines two Statistics Canada products with explicit dates: April 2025 and April 2026 province/territory population estimates, and the January 1, 2025 census-subdivision hierarchy. It does not reproduce boundary geometry, infer municipal status from type codes, measure search demand, predict rankings, describe individuals, or claim a Mosalio office, employee, client, partner or physical service presence in Manitoba.
Q2 estimates refer to April 1. The April 2026 values are preliminary postcensal estimates; April 2025 values are updated postcensal estimates.
Adapted from Statistics Canada, Census Subdivision Boundary File, 2025, January 1, 2025, and Table 17-10-0009-01, Population estimates, quarterly. This does not constitute an endorsement by Statistics Canada of this product.
This deterministic profile was published and reviewed on . Its calculations are reproducible from a pinned 28-row population subset and the reviewed 2025 geography snapshot. Search engines independently decide whether and when to crawl, index or rank the page.
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