Template · CSV · v1.0
Aggregate result schema
Empty release structure for condition estimates, uncertainty, suppression, and notes.
Download CSVTemplate and data catalog
Files should clarify the evidence—not expose respondents.
Version 1.0 includes reusable planning and reporting templates. They contain no respondents or empirical findings; aggregate study releases will appear only after completed fieldwork and disclosure review.
Template · CSV · v1.0
Aggregate-release codebook
Definitions and allowed values for the public result schema.
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Disclosure-test worksheet
Plan exact stimuli, unaided interpretation, recognition, trust, and reporting checks.
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Message-review worksheet
Record independent 0–2 rubric judgments, evidence, blockers, and revisions.
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Question-order audit
Check priming, teaching, consistency pressure, skip logic, and context.
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Claim register
Map exact and implied claims to evidence scope, owners, decisions, and review triggers.
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Cross-border change log
Separate language, currency, offer, disclosure, and operational differences.
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Sampling inference audit
Document the target, frame, recruitment, error risks, and permitted reporting lane.
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Decision brief
Freeze the decision, actions, contrast, outcomes, thresholds, and stop conditions.
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Reporting checklist
Audit provenance, flow, measurement, estimates, limits, disclosures, and corrections.
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These files are blank planning structures, not validated instruments or industry standards. You may adapt them for internal or commercial work with attribution to Message Test Bench. Do not imply endorsement, certification, or that an empty schema contains research evidence.
Release standard
Future public research releases will use aggregate rows only. Names, emails, device identifiers, panel identifiers, verbatim personal narratives, and row-level respondent files do not belong in this catalog. Small cells will be suppressed; additional combinations may be withheld when they could make a person or household reasonably identifiable.
Versioning and provenance
Every future empirical dataset will include a release date, version, study identifier, codebook, methods link, source and transformation notes, license, and corrections history. A material correction produces a new version while the prior change remains documented.