AIJIM SHARK
Science

Research Methodology

Design Science Research approach to evidence-first decision systems

Design Science Research Framework

AIJIM is built on Design Science Research (DSR) methodology, which combines rigorous empirical investigation with practical system development. The approach follows a cyclical problem identification → solution design → evaluation cycle.

DSR Principle: Solutions must be simultaneously novel (advancing science), rigorous (empirically grounded), and practical (implementable in real contexts).

Research Program Structure

The AIJIM research program develops from a published environmental-journalism model through an empirical visibility diagnosis and an evidence-first reference architecture into the current protocol specification.

1

Paper 1: AIJIM Reference Model

Status: Published at BIS 2026 (Springer LNBIP 584)

Establishes the theoretical foundation: the five invariants (I1–I5) that govern evidence-first decision systems and formalizes the gap between ideal and actual evidence evaluation practices.

3

Paper 3: Protocol Specification

Status: First full author draft under supervisor review; not submitted

Specifies five enforceable invariants, first-class publication identity, portable audit bundles, and three Triple Falsifiability loci: Producer Conformance, Surface Observability, and Audit Replicability. ECAM-X and AEI-Delta remain bounded evaluation outputs; separate scientific measurement axes remain distinct from those protocol loci. AIJIM TCRE remains a separate proposed research instrument with explicit NOT_MEASURED/CANNOT_VERIFY boundaries.

The Research Cycle

The research structure implements the core DSR cycle:

  1. Problem Identification: Evidence evaluation in practice lacks reproducibility artifacts and formal verification mechanisms.
  2. Solution Design: The five invariants provide a principled architecture (Paper 1 theorizes this).
  3. Artifact Development: AIJIM is a working system that implements the protocol (Paper 3 specifies and evaluates this).
  4. Evaluation: Named lifecycle, mutation, and external-consumer experiments provide bounded conformance and interoperability evidence. Field efficacy and improved decision quality remain open empirical questions.

PhD Research Context

Institution: University of Technology Sydney (UTS), Faculty of Science

Funding: EXIST Research Program (Grant 03EGTTH025)

Supervisor Team: Specializes in evidence systems, investigative practices, and AI governance

Focus: Domain-agnostic evidence-first decision systems with journalism as proof case

Relevance to Practitioners

While rooted in academic research, AIJIM's DSR methodology ensures practical applicability:

  • Reproducibility: Declared run contracts require their named configurations and artifacts; missing material remains visible rather than being inferred as complete.
  • Verifiability: Formal invariants ensure that critical properties hold at runtime, not just in theory.
  • Measured versus open: The current evidence supports bounded protocol behavior; field impact, adoption, and better decisions require separate studies.
  • Domain Flexibility: The evidence-first pattern generalizes beyond journalism to any field requiring reproducible analysis.
DSR Success Criterion: Future field work must test whether the enforceable publication record improves real review and decision processes. The current implementation does not claim that outcome yet.