Question before advocacy
Contributions should address a defined research question, claim, method, dataset, model, or infrastructure need.
Participation does not require prior agreement with the framework. Independent criticism, failed replication, competing models, and well-documented negative results are valid research contributions.
The program is open, but research claims and contributor credit require explicit standards.
Contributions should address a defined research question, claim, method, dataset, model, or infrastructure need.
Reviewers and contributors are not expected to endorse the framework; contrary evidence is welcome.
Authorship, acknowledgment, and institutional credit follow documented work—not title, funding, or affiliation alone.
Accepted outputs retain versions, review states, corrections, disputes, and limitations.
Independent evaluation of definitions, literature coverage, evidence quality, methods, inference, limitations, ethics, and falsifiability.
Relevant doctoral-level research experience, a strong publication or professional record, or demonstrable subject expertise; ability to disclose conflicts and review constructively.
Review a manuscript, Framework 1.0 section, research protocol, or volume brief.
Identify unsupported claims, missing literature, counterexamples, ethical risks, or invalid inference.
Produce a signed or anonymous review memo with major, minor, and editorial comments.
Named reviewer statement or acknowledgment with consent; substantial intellectual revision may qualify for coauthorship only after explicit agreement and accountability for the final work.
Review object, reviewer role, conflict statement, date, reviewed version, recommendation, author response, and disposition.
Email a review proposal or completed memo in PDF/DOCX, identify the exact artifact and version, and include expertise, affiliation, preferred disclosure level, and conflicts.
Turning verbal propositions into explicit variables, equations, causal structures, dynamic systems, proofs, and rival formal models.
Applied mathematics, statistics, econometrics, control theory, network science, complex systems, or theoretical computer science; clear assumptions and dimensional consistency.
Formalize C, Lₑ, Eₙ, E, S, thresholds, feedbacks, and boundary conditions.
Derive testable implications and identify non-identifiability, degeneracy, or alternative specifications.
Build sensitivity, stability, equilibrium, causal, or comparative model notes.
Credit as formalization contributor or model author; coauthorship requires substantial intellectual contribution, drafting or revision, approval, and accountability.
Model ID, equations, notation, assumptions, derivation, parameter ranges, dependencies, tests, review state, code link, and version history.
Submit a concise model note with definitions, assumptions, derivation, testable predictions, failure conditions, references, and any executable code.
Building auditable datasets, construct definitions, measurement protocols, indicators, benchmarks, and uncertainty records.
Data science, statistics, survey research, archival methods, measurement theory, causal inference, or domain data stewardship; provenance and licensing competence.
Map observable indicators to research constructs and document validity limits.
Curate, clean, normalize, and version public or permissioned datasets.
Design missing-data, weighting, uncertainty, bias, comparability, and benchmark protocols.
Dataset authorship, data-curation credit, or acknowledgment according to the artifact and documented role; subsequent papers determine authorship separately.
Dataset or indicator ID, sources, schema, collection and transformation history, license, uncertainty, validation, review status, checksum, and release version.
Send a data note, dictionary/schema, provenance table, license or permission status, sample records, validation plan, and repository link where available.
Testing how micro-level agents, networks, incentives, information, trust, resources, and governance generate macro-level dynamics.
Agent-based modeling, complex adaptive systems, game theory, mechanism design, network analysis, simulation engineering, or reproducible computational research.
Implement baseline and rival multi-agent models for cooperation, trust, entropy, coordination, collapse, or recovery.
Run calibration, sensitivity, ablation, stress, adversarial, and historical-pattern tests.
Publish reproducible scenarios, parameter files, random seeds, outputs, and known failure modes.
Model and software credit based on design, implementation, analysis, and documentation; paper authorship is decided per output and requires accountability.
Model ID, architecture, assumptions, code version, environment, parameters, seeds, datasets, experiments, outputs, failed runs, review, and license.
Submit a repository or archive with README, model specification, environment file, parameter set, reproducible run, results summary, limitations, and desired review.
Using primary and secondary sources to test, refine, bound, or reject civilizational claims across time and place.
History, archaeology, area studies, political economy, sociology, anthropology, demography, or related domain expertise; source criticism and contextual analysis.
Prepare a bounded case study with timeline, unit of analysis, source map, and competing explanations.
Test stability, trust, cooperation, energy, entropy, continuity, or collapse hypotheses against historical evidence.
Identify selection bias, anachronism, missing cases, regional variation, and disconfirming evidence.
Case-study author, coauthor, reviewer, or source contributor according to intellectual responsibility and published output.
Case ID, scope, chronology, source inventory, evidence extracts, claims tested, alternative explanations, uncertainty, review, corrections, and version.
Send a case abstract, research question, scope and dates, source inventory, method, competing explanations, expected output, and conflict or access constraints.
Building the open technical infrastructure needed for provenance, versioning, graph relations, reproducibility, review, and machine-readable research records.
Web or backend engineering, databases, knowledge graphs, semantic web, APIs, research software, information security, privacy engineering, UX, or open-source maintenance.
Prototype GEO objects and Source–Evidence–Claim–Model–Review relations.
Develop schemas, validation, ingestion, query, export, identity, access, dispute, and version workflows.
Review security, privacy, licensing, accessibility, interoperability, and deployment architecture.
Code contributor, maintainer, technical designer, security reviewer, or software author credit based on accepted commits and documented responsibility.
Issue and submission ID, specification, repository, commits, tests, review, security notes, license, release, dependencies, and maintenance status.
Email a technical proposal, architecture note, issue or repository link, relevant experience, license preference, security/privacy considerations, and a bounded first deliverable.
Making concepts accessible across languages while preserving terminology, context, uncertainty, and regional scholarly perspectives.
High-level English plus target-language proficiency; academic or technical translation, terminology management, regional research networks, and cultural-context competence.
Translate or review pages, abstracts, protocols, glossaries, calls, and research summaries.
Maintain terminology, translation memory, locale conventions, RTL/accessibility quality, and version alignment.
Coordinate regional literature, scholars, cases, seminars, and feedback without claiming to represent an entire region.
Translator, translation reviewer, terminology editor, or regional coordinator credit by artifact and version; translation alone does not imply authorship of the underlying theory.
Language pair, artifact and source version, translator/reviewer roles, terminology decisions, unresolved terms, date, corrections, consent, and release.
Send language pair, relevant experience, a short sample or prior work, preferred artifact, regional focus, availability, disclosure preference, and any terminology concerns.
Structured collaboration with universities, laboratories, archives, publishers, foundations, research networks, public-interest organizations, and responsible technology institutions.
A defined institutional mandate, responsible contact, relevant expertise or infrastructure, governance capacity, and willingness to agree on scope, data rights, review, ethics, credit, and publication.
Co-develop a research protocol, dataset, model, workshop, case program, replication study, or open infrastructure prototype.
Provide archives, data access, computing, review, hosting, translation, ethics, or regional coordination under written terms.
Establish a bounded pilot with deliverables, milestones, responsibilities, risk controls, and public reporting.
The institution is credited as partner on agreed outputs; individual contributors are credited by actual role. Funding or affiliation alone does not create authorship.
Agreement ID, scope, parties, individual roles, resources, ethics and data terms, milestones, outputs, review, disclosures, changes, and closeout.
Send a letter of interest naming the institution and responsible contact, proposed question or pilot, capabilities, requested role, resources, constraints, timeline, and decision process.
Credit is agreed before publication and revised when responsibilities change.
Reserved for substantial intellectual contribution, participation in drafting or critical revision, approval of the final output, and accountability for the work.
Specific roles—review, formalization, data curation, software, validation, translation, coordination, and others—are recorded even when they do not meet authorship requirements.
Limited advice, access, logistical assistance, or other support is acknowledged with permission; it is not converted into authorship.
Failed replication, counterevidence, and critical review may receive the same visible contribution treatment as supportive findings.
Public naming, affiliation, profile links, review disclosure, and contribution details require contributor consent and may be limited for safety or confidentiality.
The initial register is a versioned research record. Future GEO or CPC-compatible credentials may be added only after governance, consent, and verification procedures are operational.
Name, ORCID or profile if supplied, affiliation, and disclosure preference
Task, question, artifact, dataset, model, review, translation, or software component
What was proposed, produced, checked, changed, or rejected
Files, repository, commits, review memo, data record, correspondence, or decision log
Submitted, under review, accepted, revised, declined, disputed, withdrawn, or superseded
Dates, versions, dependencies, license, preferred citation, corrections, and successor record
Start with a bounded contribution. A small auditable artifact is more useful than an expansive proposal with no testable output.
Choose the route that best matches the intended artifact and use its email subject.
Include scope, method, evidence or code, provenance, license, limitations, disclosure, and requested outcome.
The program checks relevance, completeness, safety, rights, conflicts, and the appropriate reviewer.
Methods, claims, artifacts, and ethical or technical risks are reviewed; revisions may be requested.
Accepted, revision, declined, disputed, or deferred decisions retain reasons; submission does not guarantee publication.
Authorship, contributor role, public naming, license, and contribution record are confirmed before release.
Accepted work is linked to the relevant page, volume, model, dataset, GEO object, correction, or research update.