Classify · Assess & Decide · Analysis & Finance
Classify Capital Character: Patient/Impatient for Growth vs Profit
A deterministic function mapping a venture's funding terms onto Christensen's two-axis capital-character model and returning whether the capital is good or bad for a new-market disruption, with the quadrant label.
You receive: A pure function classifyCapitalCharacter(inputs) -> { growth_patience, profit_patience, quadrant, good_for_new_market_disruption } graded on hidden cases.
Part of Choose Business Model
What's verified: STUD verifies the function reproduces the book's two-axis good-money/bad-money logic on hidden funding-term inputs. It does NOT judge whether the buyer's stated funding terms are real or whether accepting the capital is wise; it only classifies the terms as described.
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Deliverable interface
The exact vocabulary the automated check enforces: keys, tokens, entry points, and worked examples. Generated from the verification source.
{
"constants": {},
"entryName": "classify_capital_character_growth",
"expectNote": "expect is the comparison-space value (your return value goes through normalize first when one is published)",
"hiddenCaseCount": 12,
"hiddenCaseNames": [
"gen0",
"gen1",
"gen2",
"gen3",
"gen4",
"gen5",
"gen6",
"gen7",
"gen8",
"gen9",
"gen10",
"gen11"
],
"inputKeys": [
"growth_patience_threshold_months",
"months_to_required_profit",
"profit_patience_threshold_months",
"required_scale_months",
"scale_threshold_multiple"
],
"normalizeSource": "def _normalize_classify_capital_character_growth(r): return r if not isinstance(r, dict) else {\"growth_patience\": r.get(\"growth_patience\"), \"profit_patience\": r.get(\"profit_patience\"), \"quadrant\": r.get(\"quadrant\"), \"good_for_new_market_disruption\": bool(r.get(\"good_for_new_market_disruption\"))}\n",
"returnShapes": [
[
"good_for_new_market_disruption",
"growth_patience",
"profit_patience",
"quadrant"
]
],
"signature": "def classify_capital_character_growth(inp):",
"submission": "python exposing the entry function; inp is one input object; graded on held-out cases",
"tier": "calculator",
"visibleCases": [
{
"expect": {
"good_for_new_market_disruption": true,
"growth_patience": "patient",
"profit_patience": "impatient",
"quadrant": "patient-growth / impatient-profit"
},
"input": {
"growth_patience_threshold_months": 24,
"months_to_required_profit": 12,
"profit_patience_threshold_months": 24,
"required_scale_months": 36,
"scale_threshold_multiple": 2
},
"name": "ideal"
},
{
"expect": {
"good_for_new_market_disruption": false,
"growth_patience": "impatient",
"profit_patience": "patient",
"quadrant": "impatient-growth / patient-profit"
},
"input": {
"growth_patience_threshold_months": 24,
"months_to_required_profit": 48,
"profit_patience_threshold_months": 24,
"required_scale_months": 12,
"scale_threshold_multiple": 10
},
"name": "bad_money"
}
],
"vocabulary": [
"-growth / ",
"-profit",
"good_for_new_market_disruption",
"growth_patience",
"growth_patience_threshold_months",
"impatient",
"months_to_required_profit",
"patient",
"profit_patience",
"profit_patience_threshold_months",
"quadrant",
"required_scale_months",
"scale_threshold_multiple"
]
}Get early access to STUD the day it goes live.