Author-selected fields
The disclosure dialog uses checkboxes for each detail. The author decides which project counts and model setup notes belong in the final statement.
Methods disclosure
OpenVerbatim turns review records into draft disclosure language that a researcher can inspect, narrow, copy, and revise for a methods section.
Author control
It gives researchers structured choices and copy-ready text. The page does not turn project records into a public badge.
The disclosure dialog uses checkboxes for each detail. The author decides which project counts and model setup notes belong in the final statement.
The disclosure stats endpoint reads project records for generated coding suggestions and reviewed decisions, then returns counts for the generator.
The generated statement is plain text that can be copied into a thesis, manuscript, or methods appendix and then edited against the target policy.
Statement flow
The workflow is designed for researchers who need to declare AI assistance without letting a tool write beyond the evidence it has.
OpenVerbatim fetches disclosure stats only when the author explicitly opens the tool.
Controls let the author include or exclude generated suggestions, manual confirmations, manual rejections, automated confirmations, and model setup.
The output is a methods statement draft, not a journal compliance guarantee.
The final wording stays with the researcher, supervisor, journal, or IRB workflow.
Some disclosure tools turn methods reporting into a public badge. OpenVerbatim keeps that boundary narrower. The product can assemble a draft from project records, but the author controls the included fields and the final text.
That matters for qualitative research because methods language has to match the actual analytic workflow. A thesis chapter, article submission, and IRB update may need different wording even when they describe the same project.
The generator can use exact project counts when the author chooses to include them. Those counts are for the generated statement, not for a public share badge or a page-level claim about the research.
Related trust pages
Show that participant withdrawal was processed without retaining the interview.
redacted sharingPublish only individually approved excerpts through a public field whitelist.
trust overviewReview the suggested-until-confirmed workflow and audit model.
OpenVerbatim entity
OpenVerbatim is an open-source (Apache-2.0) qualitative data analysis platform for coding and analyzing interview transcripts. AI-suggested codes stay marked as suggestions until a human reviewer confirms or rejects them, and every decision is kept in an audit trail. The full feature set is available when self-hosted; there is no paid feature wall.
FAQ
OpenVerbatim can draft a methods disclosure statement from project records. The author chooses which details to include, copies the text, and edits it for the target institution or journal.
No. It provides author-controlled disclosure text. The final wording must be checked against the relevant thesis, journal, IRB, or supervisor requirements.
Yes. The generator exposes individual controls so researchers can choose the disclosure fields they want to include.
No. Project counts belong in the statement only when the author actively generates and chooses them. They are not shown as a public badge or marketing claim.
Try the evidence loop
OpenVerbatim drafts disclosure language from author-selected fields so the final statement can stay specific to the study.