Public status notice · 2026.08-A

Simulation — independent research initiative

BBQ is not a university, an accredited or degree-granting institution, or a registered nonprofit or charity. This website presents labelled demonstration material and external references. BBQ has no affiliation with Anthropic and cannot establish eligibility for any Anthropic program.

Read the full status and disclaimer

Public document index

RA / 03

Research agenda

Research agenda — not results

Proposed questions in reproducible computation, scientific provenance, and transparent AI-assisted research.

DP / 03

Demonstration projects

Demonstration project — no real study

Worked documentation structures using invented records, no participants, and no empirical outcomes.

SP / 03

Synthetic role profiles

Synthetic profile — not a real person

Non-human role models that demonstrate responsibility fields without creating identities or credentials.

CA / 05

Cases register

synthetic + external

Fictional quality-control scenarios separated from independently documented external cases.

ER / 08

External literature

External reference — not a BBQ output

Real scholarly records with original authorship, DOI, venue, source notes, and no BBQ output claim.

Institutional status at a glance

Every status value below is deliberately conservative. An absent legal or academic fact is shown as absent, not inferred from the domain, design, terminology, or subject matter.

Current public institutional status
Status fieldDeclared valueInterpretation
UniversityNoNo university status is claimed.
Accredited institutionNoNo accreditation evidence exists for this initiative.
Degree-granting authorityNoThe site offers no courses, credits, qualifications, or degrees.
Registered nonprofit or charityNot claimedIndependent and non-commercial describes intent, not legal status.
Relationship to AnthropicNoneNo affiliation, sponsorship, endorsement, authorization, or partnership is claimed.
Real personnel directoryNoRole profiles are synthetic interface demonstrations.
Real internal research outputsNone claimedResearch pages describe agendas and demonstrations, not completed studies.
External literatureClearly separatedExternal authorship, affiliation, venue, DOI, and rights are preserved.

Current research agenda

RA-01Research agenda — not results

Reproducible computational research records

A proposed programme for making computational claims inspectable from research question through data transformation, analysis environment, and reported conclusion.

3 proposed questions · reviewed 2026-08-29

RA-02Research agenda — not results

Scientific metadata and claim provenance

A proposed study of how publication metadata, primary sources, correction status, and local interpretation can be separated in a durable evidence register.

3 proposed questions · reviewed 2026-08-29

RA-03Research agenda — not results

Transparent documentation for AI-assisted research

A proposed framework for recording where generative systems enter a research workflow, what evidence they can access, and which decisions remain human responsibilities.

3 proposed questions · reviewed 2026-08-29

How records are classified

Public content taxonomy
ClassWhat it may containWhat it cannot establish
Research agendaProposed questions and methodsNot a completed study or result
Synthetic profileA fictional role model for interface demonstrationNot a real person, appointment, credential, or affiliation
Demonstration projectA worked documentation patternNo real participants, funding, partner, or outcome
Synthetic caseA fictional quality-control scenarioNot a client, incident, or impact claim
Synthetic dataDeterministically authored rowsNo real subject, organization, or measurement
External referenceAn independently published scholarly recordNot a BBQ output or relationship
External documented caseA source-grounded account of external workNo BBQ role identified in cited sources; no relationship claimed
Site policy / draft policyRules applied to the website or a labelled governance modelNot accreditation or legal-entity governance

Selected external reading

These works provide background vocabulary for the agendas. They are independently authored and published; selection for this catalogue is not authorship, endorsement, collaboration, or institutional affiliation.

External reference — not a BBQ outputREF-DATASHEETS-DATASETS

Datasheets for datasets

Timnit Gebru; Jamie Morgenstern; Briana Vecchione; Jennifer Wortman Vaughan; Hanna Wallach; Hal Daumé III; Kate Crawford

Communications of the ACM (2021). DOI: 10.1145/3458723

The framework asks dataset creators to document why a dataset exists, what it contains, how it was collected and processed, where it should and should not be used, how it is distributed, and how it will be maintained. It gives downstream users context that files alone cannot provide, while remaining documentation rather than a fairness, legality, or quality certificate.

Publication status
active
Affiliation field
partially present
Last checked
2026-08-29
External reference — not a BBQ outputREF-PRISMA-2020

The PRISMA 2020 statement: an updated guideline for reporting systematic reviews

Matthew J. Page; Joanne E. McKenzie; Patrick M. Bossuyt; Isabelle Boutron; Tammy C. Hoffmann; Cynthia D. Mulrow; Larissa Shamseer; Jennifer M. Tetzlaff; Elie A. Akl; Sue E. Brennan; Roger Chou; Julie Glanville; Jeremy M. Grimshaw; Asbjørn Hróbjartsson; Manoj M. Lalu; Tianjing Li; Elizabeth W. Loder; Evan Mayo-Wilson; Steve McDonald; Luke A. McGuinness; Lesley A. Stewart; James Thomas; Andrea C. Tricco; Vivian A. Welch; Penny Whiting; David Moher

BMJ (2021). DOI: 10.1136/bmj.n71

PRISMA 2020 updates the reporting checklist and flow-diagram framework for systematic reviews. Its relevance here is structural: a reporting guideline can make methods and selection decisions inspectable, but completing a checklist is not by itself proof that the review question, included evidence, analysis, or conclusion is correct.

Publication status
active
Affiliation field
not present in source
Last checked
2026-08-29
External reference — not a BBQ outputREF-STOCHASTIC-PARROTS

On the Dangers of Stochastic Parrots

Emily M. Bender; Timnit Gebru; Angelina McMillan-Major; Shmargaret Shmitchell

Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (2021). DOI: 10.1145/3442188.3445922

The paper examines risks associated with increasingly large language models, including resource costs, undocumented training data, encoded harms, and misleading interpretations of generated text. It is relevant to disclosure design because it asks what developers and researchers should know before treating fluent output as meaningful evidence.

Publication status
active
Affiliation field
present
Last checked
2026-08-29

Browse the complete external literature register.