01Search lineage before claiming novelty
Treat existing theory, standards and prior art as inputs. Classify a result as antecedent, rediscovery, synthesis, extension, application, operationalization or novelty-unassessed before using stronger language.
02Prefer established vocabulary
Do not coin a local term where a mature field or standard already has a suitable one. New terminology should purchase real precision rather than merely make familiar machinery sound proprietary.
03Keep epistemic authority within defensibility
Machine cognition may expand what can be produced faster than it expands what a human curator can understand. This maxim builds on existing claim-accountability and guarantorship traditions; it is an operating rule, not a claim of first discovery.
04Separate contribution from authority
Use mature contributorship machinery such as CRediT where it fits. Contribution does not automatically confer authority over truth or interpretation, and later validation should not erase provenance.
05Design for epistemic handoff
When an initiator cannot evaluate a promising idea, preserve its origin and route it toward missing expertise, evidence or verification rather than forcing a choice between false authority and dismissal.
06Distinguish generation from discovery
Record candidate generation, significance recognition, validation, integration and realization separately. Do not decide by vocabulary alone whether a machine or human “discovered” the result.
07Use standardized provenance first
Use W3C PROV for ordinary provenance, RO-Crate for research-object packaging and CRediT for contribution roles. Extend locally only where the research problem is not adequately represented.
08Open by default, but not recklessly
Knowledge compounds when others can inspect, reuse and challenge it. Technical mechanisms with plausible IP sensitivity should receive an explicit publication/protection review before disclosure.
09Publish to establish provenance, not priority mythology
Early public disclosure creates a timestamped record and invites criticism. It does not prove novelty, correctness, mastery or legal priority over unknown prior art.
10Version corrections visibly
When prior art or criticism changes a claim, revise the public object and preserve the reason. Do not silently smooth the history into a story in which the project was always right.
11Treat attention as a scarce resource
This principle has deep antecedents, especially Herbert Simon. The research task is to identify how machine-generated candidate abundance changes the allocation problem.
12Prefer selection quality over generation volume
The objective is not to maximise the number of ideas. It is to improve the rate at which valuable possibilities are recognized, validated, routed and realized.
13Build demonstrations, not only arguments
Software, models and reproducible analyses force conceptual claims into contact with constraints, but a working implementation is not itself proof of theoretical novelty.
14Use exclusivity only when it enables realization
Patenting is an instrument, not a default. It is justified only when temporary exclusivity is plausibly necessary for difficult real-world implementation and after prior art is properly considered.
15Keep institutions provisional
Agalmic Research should be judged by the quality, lineage-awareness, openness and durability of its work rather than by prematurely imitating an established institute.