T-Frame – Framework Model Selector

A research assistant GPT that recommends, compares, and stress-tests theoretical frameworks (behavior, adoption, marketing, etc.) to help you choose the best model for your study.

Overview
Version
v1.2
Created
2025-12-14
Updated
2025-12-14
research-assistanttheoretical-frameworksbehavior-changemarketingpolicymodel-selection
t-framemodel-selectortheory-frame
Key functions
  • Structure the research objective and capture it as an objective object for downstream reasoning
  • Recommend candidate theories/frameworks (e.g., TPB, HBM, UTAUT, COM-B) and compare strengths, limitations, and fit
  • Run a simulated expert debate (multiple viewpoints) and a consumer-persona simulation to test applicability
  • Output a final model report including components, a tree outline, a Mermaid diagram, and evidence links
Technical details
_id
g-68a0607dfb788191b75e577b0ee17560-t-frame
gpt_id
g-68a0607dfb788191b75e577b0ee17560-t-frame
viz1
public
viz2
show_url
language
en
Other fields
additional_features
["Built-in model catalog (v2) for quick reference to frameworks like TPB/HBM/UTAUT/AIDA/COM-B, etc.", "Conversation workflow: objective intake → recommendations → expert debate → consumer simulation → final report"]
example_commands
["Recommend 5 theory frameworks for ‘college students’ green purchasing behavior’ and summarize each one’s strengths/limits/fit, key constructs, and seminal links.", "I’m studying enterprise collaboration tool adoption—compare UTAUT vs TPB and suggest what to measure first in my context.", "If we choose COM-B, generate a 1-page summary with a component tree and a Mermaid diagram."]
gpt_id
g-68a0607dfb788191b75e577b0ee17560-t-frame
ideal_use_cases
["Quickly explore and compare frameworks for behavior change, technology adoption, or customer journeys and justify model choice", "Before surveys/interviews/experiments: shortlist constructs (components) and draft a conceptual model", "Prepare a clear ‘why this model’ rationale with credible evidence links for reports and proposals"]
limitations
["Focused on conceptual/theoretical frameworks rather than statistical estimation or causal identification models", "Recommendations may be less precise if the user context (population, behavior, channel, constraints) is underspecified", "Evidence links prioritize primary/authoritative sources, but full-text access may depend on paywalls or institutional access"]
target_users
["Researchers & graduate students", "Policy/campaign designers", "Marketing, UX, and product strategists"]