Canadian city labour-market divergence intelligence (monthly)
Monthly labour-market intelligence for Canada's 41 census metropolitan areas from Statistics Canada's Labour Force Survey (table 14-10-0459-01, three-month moving average, seasonally adjusted): the unemployment, participation and employment rates with 3-month changes, trailing 12-month z-scores for unemployment and employment, the cross-city unemployment-rate dispersion, deteriorating/improving flags, and a documented 0-100 labour-market strength score ranked per month (s1 tight .. s4 weak). Trailing 36 complete months. Statistics Canada Open Licence (commercial reuse allowed); source: Statistics Canada.
- Rows
- 1,476
- Columns
- 21
- Source cadence
- Monthly
- Last refreshed
- Sep 27, 2026
- Theme
- economy
| Column | Type | Description |
|---|---|---|
| cma_name | string | English census metropolitan area name (41 CMAs). |
| cma_code | string | 3-digit Standard Geographical Classification (SGC) code for the CMA (e.g. Toronto 535, Montreal 462, Vancouver 933), derived from the table DGUIDs. |
| country_code | string | ISO alpha-3 country code (CAN for all rows). |
| month | string | Reference month, first day of month (ISO date). Rates are StatCan's three-month moving average for the reference month. |
| as_of | string | Last complete month in the snapshot (pinned for idempotent re-runs). |
| unemployment_rate | float | Unemployment rate: unemployed persons as a percentage of the labour force, three-month moving average, seasonally adjusted. (unit: percent) |
| participation_rate | float | Participation rate: labour force as a percentage of the population aged 15 and over, three-month moving average, seasonally adjusted. (unit: percent) |
| employment_rate | float | Employment rate: employed persons as a percentage of the population aged 15 and over, three-month moving average, seasonally adjusted. (unit: percent) |
| unemp_chg3m_pp | float | 3-month change in the unemployment rate (percentage points). (unit: percentage points) |
| part_chg3m_pp | float | 3-month change in the participation rate (percentage points). (unit: percentage points) |
| emp_chg3m_pp | float | 3-month change in the employment rate (percentage points). (unit: percentage points) |
| unemp_z_12m | float | Z-score of the unemployment rate versus its trailing 12-month mean/std (inclusive, min 8 observations); positive = higher unemployment than usual. (unit: z-score) |
| emp_z_12m | float | Z-score of the employment rate versus its trailing 12-month mean/std (inclusive, min 8 observations); positive = stronger employment than usual. (unit: z-score) |
| cma_spread_unemp_pp | float | Max-minus-min of the unemployment rate across the 41 CMAs for the month (city divergence gauge). (unit: percentage points) |
| deteriorating_flag | boolean | True when the unemployment rate rose >= 0.5pp versus 3 months earlier. |
| improving_flag | boolean | True when the unemployment rate fell >= 0.5pp versus 3 months earlier. |
| strength_score | string | 0-100 labour-market strength score: 100*(0.40*min-max winsorized(-unemployment-rate 12m z-score) + 0.35*min-max winsorized(employment-rate 12m z-score) + 0.25*min-max winsorized(3-month participation-rate change)), winsorized at +/-3, +/-3, +/-2 and min-max normalized across CMAs within the month; 50 when degenerate. Null when any component is unavailable for that CMA-month. (unit: score) |
| strength_rank | string | Per-month strength rank across the 41 CMAs (1 = strongest); deterministic tie-breaks on the unemployment rate then CMA name. Null when the score is null. |
| strength_tier | string | s1 tight (>=70) / s2 balanced (>=45) / s3 slack (>=20) / s4 weak (<20); null when the score is null. |
| row_hash | string | SHA-256 (truncated) of the row's content fields. |
| source_retrieved | string | Source data vintage: latest reference month present in the retrieved series (content-pinned so identical re-fetches hash identically). |
First 10 sample rows — a preview, not the complete dataset.
| cma_name | cma_code | country_code | month | as_of | unemployment_rate | participation_rate | employment_rate | unemp_chg3m_pp | part_chg3m_pp | emp_chg3m_pp | unemp_z_12m | emp_z_12m | cma_spread_unemp_pp | deteriorating_flag | improving_flag | strength_score | strength_rank | strength_tier | row_hash | source_retrieved |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Peterborough, Ontario | 529 | CAN | 2023-09-01 | 2026-08-01 | 2.9 | 61.1 | 59.3 | -3.3 | 1.4 | 3.3 | -1.405 | 1.596 | 6.8 | false | true | 83 | 1 | s1 | 95c632aae49376b0 | 2026-08-01 |
| Kitchener-Cambridge-Waterloo, Ontario | 541 | CAN | 2023-09-01 | 2026-08-01 | 5.6 | 70.5 | 66.6 | -0.6 | 0.3 | 0.8 | -1.511 | 1.523 | 6.8 | false | true | 76.54 | 2 | s1 | 98a2442dfc200319 | 2026-08-01 |
| London, Ontario | 555 | CAN | 2023-09-01 | 2026-08-01 | 5.5 | 67.7 | 63.9 | 0.9 | 1.8 | 1 | 0.808 | 1.904 | 6.8 | true | false | 67.19 | 3 | s2 | 4e7017c6f9b3ada9 | 2026-08-01 |
| Victoria, British Columbia | 935 | CAN | 2023-09-01 | 2026-08-01 | 3.8 | 65.5 | 63 | 0.4 | 3.6 | 3.2 | 1.29 | 2.3 | 6.8 | false | false | 66.99 | 4 | s2 | 0e16044d42f66bfe | 2026-08-01 |
| Trois-Rivières, Quebec | 442 | CAN | 2023-09-01 | 2026-08-01 | 4.1 | 60 | 57.5 | 0.3 | 1.2 | 0.9 | 1.163 | 2.512 | 6.8 | false | false | 64.82 | 5 | s2 | ae4dc03eb7fd108f | 2026-08-01 |
| Kamloops, British Columbia | 925 | CAN | 2023-09-01 | 2026-08-01 | 5.4 | 66.8 | 63.2 | -1.2 | 3.4 | 4 | 0.418 | 0.745 | 6.8 | false | true | 63.12 | 6 | s2 | 25d20b930f37e431 | 2026-08-01 |
| Chilliwack, British Columbia | 930 | CAN | 2023-09-01 | 2026-08-01 | 3.8 | 63 | 60.7 | -0.5 | -0.9 | -0.3 | -2.066 | -0.35 | 6.8 | false | true | 59.74 | 7 | s2 | 078d4100a6bb850a | 2026-08-01 |
| Calgary, Alberta | 825 | CAN | 2023-09-01 | 2026-08-01 | 5.9 | 71.2 | 67 | -0.2 | -0.3 | -0.2 | -1.174 | 0.164 | 6.8 | false | false | 59.13 | 8 | s2 | bef2ad8fec0fc8f4 | 2026-08-01 |
| Québec, Quebec | 421 | CAN | 2023-09-01 | 2026-08-01 | 2.8 | 67.2 | 65.3 | 0 | 1 | 0.9 | 0.327 | 0.666 | 6.8 | false | false | 57.1 | 9 | s2 | cec7cf0624ce1cfa | 2026-08-01 |
| Saint John, New Brunswick | 310 | CAN | 2023-09-01 | 2026-08-01 | 6.5 | 62.5 | 58.5 | 0.8 | 2 | 1.5 | 1.227 | 0.46 | 6.8 | true | false | 53.34 | 10 | s2 | ccf1cb217636565f | 2026-08-01 |
- Current
20260927T123859Z-4c1fb5458f9e · sha256 4c1fb5458f9e…
1,476 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/statcan_cma_labour_intel/cma_labour_divergence_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/statcan_cma_labour_intel/cma_labour_divergence_monthly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/statcan_cma_labour_intel/cma_labour_divergence_monthly
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260927T123859Z-4c1fb5458f9e and its content hash, so readers get exactly the data you used.
Statistics Canada LFS city labour-market divergence intelligence. (2026). Canadian city labour-market divergence intelligence (monthly) [Data set, snapshot 20260927T123859Z-4c1fb5458f9e, sha256 4c1fb5458f9e]. Datazimuts. Retrieved 2026-09-27, from https://datazimuts.com/en/datasets/statcan_cma_labour_intel/cma_labour_divergence_monthly?snapshot=20260927T123859Z-4c1fb5458f9e
@misc{dz_statcan_cma_labour_intel_cma_labour_dive_4c1fb545,
title = {{Canadian city labour-market divergence intelligence (monthly)}},
author = {{Statistics Canada LFS city labour-market divergence intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/statcan_cma_labour_intel/cma_labour_divergence_monthly?snapshot=20260927T123859Z-4c1fb5458f9e}},
note = {Snapshot 20260927T123859Z-4c1fb5458f9e, sha256 4c1fb5458f9e734903849a94d0486bcae0f7d343a94ec385d36c95ac4ab14830; accessed 2026-09-27}
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