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Theory construction (E2ET theory lab)

By E2ET contributors

Cross-disciplinary IS theory generation via bisociation: 60 disciplinary personas across 8 tiers in an iterative loop that converges on propositions, constructs and a research agenda.

In placeE2ET theory lab, runs locally; not yet releasedtheoretical
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Input
A raw phenomenon seed
Output
A theory brief: propositions, constructs, mechanisms, boundary conditions, theory type and a research agenda

Description

Data model
Discipline
Information systems
Method family
Theoretical
Design
not specified
Research stage
Research questionLiterature synthesisHypothesesFormal modelingReview
Contributors
E2ET contributors (Software, Methodology, Conceptualization)
Usage
not used in published research yet · Examples: 3 example studies
Source
E2ET theory lab (local) · src/theory_lab
Record
template:theory-building · JSON

Solid tags are declared by the source or mapped from its terms; dashed tags are inferred by a published rule. Hover a tag for its provenance.

The theory lab at a glance

The core creative mechanism is bisociation (Koestler): combining two previously unrelated frames of reference. The rounds repeat until the evaluator's weighted score reaches the threshold, for at most five rounds; after the fifth, E2ET marks the run as converged whatever the score.

Before the rounds
  1. Phenomenologist refines the seed
  2. Cartographer maps the theory landscape
  3. Scout director picks a core team and a guest pool
Each round (up to 5)
  1. Personas write transfer reports in parallel
  2. Bisociation links reports that connect
  3. Synthesizer: batch 1: abduction, articulation, coherence; batch 2: formalization, severe test; batch 3: story check, type check
  4. Evaluator scores the theory
score below 0.70 → rotate guests, next round ↺
After convergence
  1. Integrator builds the theory brief
  2. Researcher approves, iterates or rejects
Fig. 1. The E2ET theory lab loop, from src/theory_lab/runner.py.

Evaluation criteria

CriterionWeight
novelty
Does the theory offer genuinely new insight through cross-disciplinary bisociation? Does it reveal something that researchers in the home field would not see?		0.25
explanatory coherence
Is the theory internally consistent? Do propositions support each other? Are there contradictions or gaps in the causal chain?		0.30
falsifiability
Are the predictions specific, concrete, and testable? Could an empirical study clearly confirm or refute them? Are falsification conditions stated?		0.25
boundary clarity
Are scope conditions well-defined? Is it clear when and where the theory applies and when it does not? Are boundary conditions precise rather than vague?		0.20

Quoted from src/theory_lab/agents/evaluator.py. The theory converges at a weighted score of 0.70.

Tiers of intellectual distance

Personas are grouped by their distance from information systems, from tier 0 (IS itself) to tier 7 (law).

Tier 0 · Information Systems10 personasTier 1 · Economics12 personasTier 2 · Mathematics9 personasTier 3 · Physics6 personasTier 4 · Life Sciences4 personasTier 5 · Computer Science5 personasTier 6 · Social Sciences & Humanities11 personasTier 7 · Law & Regulation3 personas

Steps

  1. 1
    phenomenologist
    Pre-round agent that refines a raw phenomenon seed into a structured phenomenon analysis suitable for theory landscape mapping.
    phenomenologist
    specialist
  2. 2
    cartographer
    Pre-round agent that maps the existing theory landscape around a refined phenomenon, identifying gaps and cross-disciplinary opportunities.
    cartographer
    specialist
  3. 3
    scout_director
    Pre-round agent that selects core team and guest pool personas from the roster, based on the phenomenon and theory landscape analysis.
    scout_director
    specialist
  4. 4
    team_validation
    Every selected persona must exist in the roster, and the core team and guest pool must not overlap.
    check
  5. 5
    persona_reports
    Core team and guests each write a transfer report: source model, target phenomenon, structural mapping, proposed mechanism, boundary conditions and testable predictions. From round 2 each persona also receives the evaluator’s feedback.
    persona_agent
    specialists, parallel, each round
  6. 6
    bisociation
    Links reports that share a mechanism, use structurally analogous mappings, address each other’s boundary conditions or yield converging predictions.
    each round
  7. 7
    synthesis
    Seven micro-stages in three batches: abduction, articulation, coherence, formalization, severe test, story check, type check.
    synthesizer
    specialist, each round
  8. 8
    evaluation
    Scores novelty, explanatory coherence, falsifiability and boundary clarity. At a weighted score of 0.7 or more the theory has converged; otherwise guests rotate and the next round starts, up to five rounds.
    evaluator
    check, each round
  9. 9
    integrator
    Post-convergence agent that transforms raw propositions, constructs, and mechanisms into a coherent, integrated theoretical framework with: 1.
    integrator
    specialist
  10. 10
    human_review
    The researcher approves, iterates with feedback or a different team, or rejects the theory brief.
    human

Versions and evaluations

One version, unreleased

One version so far: E2ET's src/theory_lab, which runs locally and is not yet released. No evaluation records exist yet.

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Cite this template
Persistent identifiers planned 
@software{e2ercontributors2026e2ertheoryconstructione2,
  title   = {E2ER theory construction (e2et theory lab) template},
  author  = {E2ER contributors},
  year    = {2026},
  note    = {E2ER template. Persistent identifier planned},
  url     = {https://e2er.org/templates/theory-building}
}

Checks on this template

  • ✓Output contracts · Every step produced the artifact it declared, in the declared form
    Required of every template.
  • ✓Execution reliability · Analysis code ran and wrote a parseable, non-empty result
    Required of every template.
  • –Numbers · Every number in tables and text matches the output of executed code
    Not applicable. This method produces no computed numbers to match.
  • ○Citations · Every reference resolves to an existing publication via OpenAlex, Semantic Scholar or Crossref
    Proposed. Proposed for the floor; runs log it but may not block on it.
  • ○Verbatim passages · Every claim about a source points to a passage found word for word in that source
    Proposed. Proposed for the floor; runs log it but may not block on it.

Runs of this template

Example: a theory of why validator sets concentrate on public blockchainsExample