operationalization

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SOP: operationalize abstract concepts into measurable indicators and methods

yogsoth-ai By yogsoth-ai schedule Updated 6/16/2026

name: operationalization description: 'SOP: operationalize abstract concepts into measurable indicators and methods' version: 1.0.0 category: hypothesis-formation type: sop campaign: hypothesis-formulation input: 'Abstract variable description (from variable-identification output)' output: 'Operational definition + measurement method + validity argument (content/construct/criterion)' dependencies: skills: - subagent-spawning

Operationalization

Convert the abstract concepts in a hypothesis into concrete, measurable indicators, and argue for measurement validity.

HARD-GATE

Preconditions (all must hold before starting): 1. At least 1 variable needs operationalizing (especially when operationalizable ≠ "high") 2. The variable's theoretical definition is provided (from the description field of variable-identification)

Not satisfied → stop, return error: variable-identification must be completed first.

Pipeline

  1. Precondition check: verify completeness of the variable description
  2. Concept analysis: decompose the variable's core attributes (conceptual dimensions)
  3. Indicator selection: select 1-2 measurable indicators for each dimension
  4. Measurement method determination: specify the data collection method (survey/experiment/observation/archival/computational)
  5. Validity argument:
    • Content validity: do the indicators cover all key dimensions of the concept?
    • Construct validity: do the indicators converge with related constructs and diverge from unrelated ones?
    • Criterion validity: are the indicators correlated with a validated standard measure?
  6. Output the operational definition

Output Format

[
  {
    "variable": "Variable name",
    "theoretical_definition": "Abstract definition",
    "dimensions": ["Dimension 1", "Dimension 2"],
    "indicators": [
      {
        "indicator": "Indicator name",
        "measurement_method": "How to collect/measure",
        "scale": "nominal | ordinal | interval | ratio",
        "validity": {
          "content": "Justification",
          "construct": "Justification",
          "criterion": "Justification or null if not applicable"
        }
      }
    ],
    "operationalization_notes": "Any remaining challenges or alternatives"
  }
]
Install via CLI
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill operationalization
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