V7 Release Note
Current release
V7 is the live structural release as of 2026-04-07. It scores 562 occupations and 88 modern roles. V6 baseline scores are preserved in every occupation record for comparison.
What V7 changes
V7 introduces two formula changes to the V6 structural model, both grounded in recent research and using data already available in the pipeline:
1. Task-concentration-weighted exposure
Occupations with concentrated AI task exposure face higher displacement risk than those with distributed exposure (Hampole et al. 2025). V7 amplifies the base exposure score using a task-concentration signal derived from Anthropic task penetration data matched to O*NET task statements.
task_signal = task_exposure_concentration x task_effective_coverage
exposure_v7 = clamp01(exposure x (1 + 0.20 x task_signal))
492 of 562 occupations have task data. The remaining 70 receive task_signal = 0, preserving V6-equivalent exposure.
2. Demand-persistence proxy
Addresses the Imas price-elasticity critique: when AI reduces service costs, demand may increase enough to offset displacement. Since occupation-level elasticity data does not exist, V7 builds a ranked composite proxy from four existing signals.
demand_persistence = 0.4 x momentum_rank + 0.3 x vacancy_rank + 0.2 x scarcity_rank + 0.1 x demand_bonus_rank
demand_resilience_v7 = clamp01(base_resilience x 0.45 + demand_signal_bonus + 0.10 x demand_persistence)
This is not a measure of price elasticity. It is a demand-side counterforce proxy using market momentum, vacancy trends, wage scarcity, and official demand signals.
Complete V7 formula
exposure = reliability-weighted 4-source ensemble (Felten AIOE, Anthropic, Eloundou, ILO)
task_signal = task_exposure_concentration x task_effective_coverage
exposure_v7 = clamp01(exposure x (1 + 0.20 x task_signal))
bottleneck = pctile_rank(Pizzinelli theta)
displacement_pressure = exposure_v7 x (1 - bottleneck)
demand_persistence = 0.4 x mm_rank + 0.3 x vacancy_rank + 0.2 x scarcity_rank + 0.1 x bonus_rank
demand_resilience = clamp01(base_resilience x 0.45 + demand_signal_bonus + 0.10 x demand_persistence)
headline_risk = displacement_pressure x (1 - demand_resilience)
augmentation = exposure_v7 x bottleneck x base_resilience
Stability metrics
Median |delta risk|
0.0077
Target: < 0.03
Band flips
39 / 562 (6.9%)
Target: < 15%
Spearman rank correlation
0.9995
Target: > 0.95
Directional accuracy
100% (2/2 pairwise)
Target: ≥ 50%
Validation
V7 passes 166 of 169 structural validation checks. All 6 anchor occupations pass (Software Developer, Data Entry Clerk, Surgeon, Telemarketer, Registered Nurse, Data Scientist). The 3 pre-existing failures (crosswalk coverage threshold, software developer crosswalk type, experimental release status) are unchanged from V6.
Research grounding
- Hampole et al. (2025) — Task concentration predicts displacement vulnerability. Occupations where AI penetration is concentrated in a few high-weight tasks face greater structural pressure than those with distributed exposure.
- Imas / Silicon Canals (2026) — Price elasticity of demand is the critical missing variable for predicting actual displacement. V7 addresses this with a demand-persistence proxy, not a direct elasticity measure.
- Brookings (2026) — Career pathway erosion when gateway occupations are automated. Informs the transition-capacity layer (separate from headline score).
Data and downloads
V7 dataset is available at /data in JSON and CSV formats. V6 baseline scores are preserved in the baseline_v6 field of every occupation record. New V7 fields: task_signal, demand_persistence, exposure_v7.