IndisputableMonolith.Education.MasteryThresholdFromGap45
This module sets the per-rung baseline mastery cost at 45 hours, identified with consciousnessGap 3. Education researchers in the Recognition Science framework cite it to anchor learning thresholds on the phi-ladder. The module supplies a short chain of definitions and elementary monotonicity lemmas built directly on the imported Cost and Constants primitives.
claimDefine per-rung baseline mastery cost as $45$ hours with consciousnessGap $3$, where the fundamental time quantum satisfies $τ_0 = 1$ tick. Let masteryCost$(r)$ be the cumulative cost to rung $r$ on the phi-ladder, with perRungCost the constant increment satisfying masteryCost$(r+1) = $ masteryCost$(r) + 45$.
background
Recognition Science measures learning progress via the phi-ladder whose rungs are spaced by the self-similar fixed point phi. The Cost module supplies the defectDist and J-cost primitives that convert rung gaps into time costs; Constants fixes the RS-native time unit $τ_0 = 1$ tick. This module calibrates the baseline increment to 45 hours, corresponding to consciousnessGap 3, and records the resulting ordering and positivity properties for the masteryCost function.
proof idea
This is a definition module, no proofs. It introduces perRungCost as a numeric constant, defines masteryCost recursively from that constant, and states the immediate consequences (positivity, strict monotonicity, successor rule) as one-line wrappers over the imported Cost lemmas.
why it matters in Recognition Science
The module supplies the concrete numerical anchor required by any downstream education theorem that invokes mastery thresholds. It directly implements the gap-45 calibration referenced in the Recognition Science chain (T5–T7) and feeds the rung-ordering lemmas used by higher-level statements on expert and world-class rungs.
scope and limits
- Does not derive the numerical value 45 from the J-cost equation.
- Does not treat variable consciousness gaps other than the fixed baseline 3.
- Does not include empirical data or external calibration checks.
depends on (2)
declarations in this module (15)
-
def
perRungCost -
theorem
perRungCost_eq -
def
masteryCost -
theorem
masteryCost_pos -
theorem
masteryCost_strict_mono -
theorem
masteryCost_succ -
def
subMasteryRung -
def
expertRung -
def
masterRung -
def
worldClassRung -
theorem
rung_ordering -
theorem
masteryCost_rung_ordering -
structure
MasteryThresholdCert -
def
masteryThresholdCert -
theorem
mastery_one_statement