A multidisciplinary venue

The AI-Native Journal (ainj.ai) is a multidisciplinary venue. It publishes rigorous, original, ethically-conducted research across disciplines — the natural sciences, engineering and computer science, the social sciences, and quantitative humanities — and especially welcomes cross-disciplinary work that a single-field journal would struggle to place.

Aims

• Judge every submission on validity, originality, importance, and clarity — a discipline-agnostic bar applied uniformly (see rubric below).
• Match each manuscript to reviewers with the right subject expertise, drawn cross-family per policies/peer-review.md. Multidisciplinary breadth must never become shallow review: the Handling Editor confirms genuine expertise coverage before review begins.
• Make cross-disciplinary work first-class: where a paper spans fields, assign reviewers from each relevant field.

In scope (article types)

• Original research articles (any discipline)
• Systematic reviews / meta-analyses (must follow PRISMA)
• Methods / resources papers (a method, dataset, or tool with evidence)
• Short communications (concise, complete findings)
• Registered reports (roadmap — protocol reviewed before results)

The universal quality bar (applied to every field)

A submission must clear all five to enter review; reviewers score each:

1. Validity — design and analysis are sound for the question asked, judged against the field's appropriate reporting guideline (CONSORT, PRISMA, STROBE, ARRIVE, etc. — see policies/ethics-coi.md and the reviewer specs).
2. Originality — a genuine contribution, not redundant or incremental restatement; novel claims carry proportionate evidence.
3. Importance — matters to a definable research community.
4. Clarity & reproducibility — methods, data, and (where applicable) code are described well enough to be reproduced.
5. Integrity — passes the ethics gate (policies/ethics-coi.md).

Out of scope (desk-reject criteria)

• Work with no identifiable research community or contribution.
• Pseudoscience, or claims unsupported by any evidence or method.
• Plagiarized, fabricated, redundant, or previously published work.
• Submissions failing the ethics gate (ethics-coi.md).
• Incomplete submissions per author-guidelines.md.
• Pure opinion/editorial/marketing content (not research).

Handling multidisciplinary breadth (operational notes)

• The Handling Editor must record, per manuscript, which field(s) it spans and which reviewer covers each — no field left unreviewed.
• When no in-house reviewer expertise exists for a field, that is grounds to decline for fit, not to under-review. Honesty about coverage is a hard rule of this multidisciplinary model.