CLANKED

Barrie, ON · POP — · EMP 101,545 · DATA GRADE A

Barrie, ON

48.1 /100

exposure score (OpenAI task-exposure index via NOC crosswalk — single-index tier)

#27 of 41

more exposed than 37% of Canadian CMAs

Secondary measures

19.5%

of workers are in occupations where ≥50% of tasks are LLM-exposed (Eloundou β; threshold-sensitive — note)

97%

of area employment matched to scored occupations (grade A)

Scenario: if replacement-level AI arrives in 2030

2027 2035

Figure 1. Modeled displacement under the median preset (diffusion k=0.8, ceiling 0.75, automation share 0.45, friction lag 1.5y, attrition 3%/y). Solid: positions eliminated. The gap between gross and layoffs is natural attrition — speed of diffusion, not depth of exposure, determines layoffs. This is a scenario, not a forecast: adjust every assumption.

Where the losses land — and your assumptions

Positions eliminated by 2035 per occupation group, under the arrival year selected above. Drag any multiplier if you think we're wrong about a group — your model, your numbers. Multipliers scale that group's task exposure (×0 = immune, ×2 = double).

Table 3. Group exposure = employment-weighted mean task exposure (Eloundou β over the group's local occupations). Bars use the same scenario engine as Figure 1 (median preset).

Most exposed local occupations

OccupationJobsMedian wageExposure [range]
Retail salespersons and visual merchandisers 3,495
61.7
Retail and wholesale trade managers 2,700
68.2
Administrative officers 1,605
82.9
Elementary school and kindergarten teachers 2,425
46.9
Administrative assistants 1,140
94.9
Registered nurses and registered psychiatric nurses 1,995
43.3
General office support workers 1,040
74.2
Cashiers 1,725
41.9
Accounting and related clerks 800
86.6
Transport truck drivers 1,800
35.2

Table 2. Ranked by exposure × local employment. Bands on the 0–100 occupation scale.

Compare Barrie against any other metro — side by side.