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Loss Frame Endowment Sign Token Tool

Classify an outcome relative to an explicitly supplied endowment; no utility or behavior is predicted.

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Description

Label one outcome relative to a supplied endowment.

Behavioral-economics tasks compare supplied payoffs, reference points, budgets and observed choices. A gap, dominance flag or response fraction illustrates a declared convention without identifying a psychological bias, predicting real choices or selecting a suitable financial action.

Label one outcome relative to a supplied endowment.

When to use this tool

Use Loss Frame Endowment Sign Token when checking the stated experimental payoff, budget, reference or choice convention.

How to use the tool and how it works

  1. Enter outcome, endowment. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read difference, frame. Use the output convention below.

Label one outcome relative to a supplied endowment. difference = outcome-endowment, frame is loss below zero, gain above zero, unchanged at equality.1

Input fieldMeaning and unitsAccepted input
outcomeOutcomeRequired. Finite number.
endowmentEndowmentRequired. Finite number.
Output fieldInterpretationReturned shape
differenceDifferenceRequired. Finite number.
frameFrameRequired. Text; maximum UTF-16 length 8192.
json
{
  "input": {
    "outcome": 80,
    "endowment": 100
  },
  "output": {
    "difference": -20,
    "frame": "loss"
  }
}

Limitations and assumptions

  • This is a numeric labeling convention, not a measured psychological effect or recommendation.
  • Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.
  • Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.

Alternative or Complementary methods

Use a well-defined study design and complete data to estimate behavior; assess real financial rights, consequences and uncertainty independently.

References

  1. Calculation and input contract: behavioral-economics/loss-frame-endowment-sign-token — tool.io

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