feasibility-constrained-formulation

name	feasibility-constrained-formulation
description	Strategy: reshape a research question under resource constraints — pragmatic adjustment that preserves core value
version	1.0.0
category	hypothesis-formation
type	strategy
campaign	research-question
tactics	["question-refinement-loop"]
sops	["scope-assessment","finer-criteria-check","success-criteria-definition"]
dependencies	{"tactics":["question-refinement-loop"]}

Feasibility-Constrained Formulation

Reshape a research question under constraints — when the ideal question exceeds available resources, pragmatically adjust it to be feasible while preserving core research value.

When to Use

• The ideal research question exceeds available resources (time/data/compute/manpower)
• A trade-off between ambition and feasibility is needed
• There are explicit constraints (deadline, budget, data availability)

Thinking Framework

Core logic: constraints are not the enemy, they are design parameters. Good reshaping under constraints = finding "the most valuable question answerable within these constraints."

Constraint Types

Constraint	Adjustment strategy	Example
Insufficient time	narrow scope / use proxy metrics	3 months → pilot study only
Data unavailable	switch data source / switch study object	cannot obtain X → use public dataset Y
Insufficient compute	simplify method / reduce scale	cannot train a large model → use fine-tuning
Insufficient expertise	narrow the domain / collaborate	no biology background → focus on the computational part

Adjustment Principles

• Preserve the core: adjust scope and method, but keep the essence of the core research question
• Use proxies: if direct measurement is infeasible, find a reasonable proxy metric
• Phase it: split a big problem into pilot → full study
• Make trade-offs explicit: explicitly state what was given up due to constraints

Budget Gate

Tier	Constraint analysis	Adjustment options	Output
S	list main constraints	1 adjustment option	a feasible RQ
M	constraint classification + impact assessment	2-3 adjustment options + comparison	best feasible RQ + trade-off statement
L	full constraint map + priorities	multiple options + Pareto analysis	best RQ under constraints + phased plan

Default Reference Flow