Multipliers¶
Module: hours_eoh/core/multipliers.py
Implements Condition II — skill-tier multipliers grounded in entropy-reduction leverage. The multiplier is the factor by which one hour of a worker's labor is scaled when creating TEH.
population_weighted_mean_multiplier(…) → float¶
The population-weighted mean multiplier across workforce segments, each a fraction of the workforce with its mean multiplier. Fractions are normalized if they do not sum to exactly 1.
from hours_eoh.core.multipliers import population_weighted_mean_multiplier
mean = population_weighted_mean_multiplier() # the shipped DEFAULT_SEGMENTS
# or pass your own workforce segments: population_weighted_mean_multiplier(segments=[...])
Band target: 1.8–2.1, with a recommended target of 2.1. This is monitored by Condition II.
multiplier_band_check(mean_multiplier, …) → dict¶
Verifies the population-weighted mean is within the band (band_low=1.8, band_high=2.1 by default). Out of band, the status says which way: below the band means raising low-tier multipliers, above it means tightening high-tier assignments.
from hours_eoh.core.multipliers import multiplier_band_check
check = multiplier_band_check(mean_multiplier=2.05)
# Returns: {"in_band", "mean_multiplier", "band_low", "band_high", "target",
# "distance_to_target", "status"}
print(check["in_band"], check["status"])
tier_multiplier(training, demand, scarcity, impact, …) → float¶
A tier multiplier from the four-factor assessment in the paper's additive form, m = 1 + α₁·T + α₂·D + α₃·S + α₄·I, each factor in [0, 1]. The multiplier sets the floor wage rate, not an economy-wide price.
The multiplier system applies to all entropy-reduction labor uniformly — care, production, and stewardship workers all receive the same framework. What changes across the arc is which tier classifications are most in demand.
epoch_alpha_weights(epsilon) → tuple[float, float, float, float]¶
Deprecated
The additive form is superseded by the geometric map used for the measured O*NET/BLS reference multiplier: epoch_factor_weights() → composite_from_factors() → reference_multiplier(). This function is kept for backward compatibility.
The absolute α coefficients (training, demand, scarcity, impact) for tier_multiplier()'s additive form, adapted to ε.