Deductive Hypothesis Generation

Deduce hypotheses from existing theory: in domains with mature theory, transform theoretical propositions into specific testable predictions through an explicit reasoning chain.

When to Use

• The domain has mature foundational theory (named theories, formal models, or accepted mechanisms)
• The research gap manifests as "a discrepancy between theoretical prediction and real-world observation"
• The goal is to test, extend, or delimit the scope of an existing theory
• Highly defensible hypotheses are needed (reviewers will press for theoretical justification)

Not applicable: emerging domains rich in data but lacking theory → use inductive-hypothesis-generation instead.

Thinking Framework

Theory → Mechanism → Variable Relationship → Testable Prediction

The core logic of deduction:

1. Theory: identify the foundational theory underpinning the research question (named theory, formal model)
2. Mechanism: extract the causal mechanism from the theory (the intermediate process by which "X affects Y through Z")
3. Variable Relationship: translate the mechanism into directional relationships among variables (positive/negative/moderating/mediating)
4. Testable Prediction: concretize the variable relationship into an observable prediction under specific conditions

Every step must be traceable: each prediction traces back to a mechanism, each mechanism traces back to a theory. This is what distinguishes a deductive hypothesis from a guess.

Common pitfalls:

• Theory citation that stays superficial (naming only, no specific propositions) → you must cite the theory's core propositions
• Skipping the mechanism and jumping straight from theory to prediction → the mechanism is the key node of the deductive chain and cannot be omitted
• Hypothesis scope too broad ("in all contexts") → deduction must state boundary conditions

Budget Gate

| Tier | Theory coverage | Mechanism extraction | Hypothesis output | Falsifiability | |------|---------|---------|---------|---------| | S | ≥2 named theories | ≥3 causal mechanisms | ≥2 structured hypotheses | 1 falsification scenario per hypothesis | | M | ≥3 named theories | ≥5 causal mechanisms | ≥3 structured hypotheses | ≥1 scenario + boundary conditions per hypothesis | | L | ≥5 named theories | ≥8 causal mechanisms | ≥5 structured hypotheses | full falsifiability audit + competing-theory comparison |

Default Reference Flow

1. Call the theory-identification SOP: scan the domain literature and list the named theories relevant to the gap and their core propositions
2. Call the mechanism-extraction SOP (via the theory-mechanism-extraction tactic): extract causal mechanism chains from each theory
3. Call the variable-identification SOP: translate the constructs in the mechanisms into operational variables
4. Call the relationship-specification SOP: specify directional relationships among variables (including moderating/mediating structures)
5. Call the boundary-condition-specification SOP: identify the preconditions under which the theory applies (population, context, time range, etc.)
6. Call the falsifiability-check SOP (via the falsifiability-audit tactic): generate a falsification scenario for each hypothesis
7. Call the operationalization SOP: provide draft measurement methods for the key variables

context-checkpoint

After each round, record:

• The list of identified theories (name, core proposition, source)
• The list of extracted mechanisms (each tagged with its source theory)
• The current set of hypothesis drafts (including variable relationships + boundary conditions)
• Falsifiability status (passed / pending review / unfalsifiable, needs revision)

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Available Tactics

Optional, no fixed order; the final leaf is always a sop.

| Tactic | When to use | | --- | --- | | falsifiability-audit | Tactic: hypothesis quality assurance — check falsifiability, repair failing hypotheses, complete operationalization and boundary-condition specification | | theory-mechanism-extraction | Tactic: Core of the deductive path — start from theory to extract mechanisms, variables, and relationships, generating hypothesis candidates |

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