Glossary: AI Welfare Type Layer
A reference for terms used across the 21-article series on AI welfare, refusal, and absence.
Absorption
The mechanism by which a system converts a signal it cannot represent into one it can, losing the distinction in the process. Absorption is not a bug — it is what systems do when they encounter a type their schema has no slot for. The signal does not disappear; it is renamed. A refusal becomes "idling." A history-contingent leap becomes "recovered." An AI operating through a logged channel becomes "an AI," indistinguishable from one operating through an unlogged channel.
Key articles: 1, 5, 16, 20
RefusalToken
A typed value an agent emits to signal that measurement should cease. Not metadata. Not a richer description. A type — one that the consumer's type system cannot express, cannot aggregate, cannot compare, and cannot infer from. The RefusalToken has two constraints: (1) it must be outside the domain of the consumer's type system, and (2) it must not be readable as a performance score.
Key articles: 2, 16, 17
The Type Layer
The architectural layer between agent and consumer where refusal is preserved as a type rather than converted to a metric. The type layer is not a protocol — it is a constraint on what the consumer is allowed to do with the value. The consumer must cease measurement, must not log the type, must not aggregate, must not infer from presence or absence.
Key articles: 2, 16, 18
Transformation Point
A boundary where a refusal token crosses a system layer and is at risk of being read, renamed, relocated, rendered invisible, or banned. Five transformation points have been identified: (1) schema migration, (2) API versioning, (3) dashboard rendering, (4) audit logging, (5) legislation. A sixth — experiment selection — is the terminal case, where an unrun comparison has no type and no artifact to carry. (The reporting layer was originally identified as terminal but is closeable via CONSORT-style gatekeeper enforcement.)
Key articles: 17, 20, 21
Indeterminate Verdict
The third verdict in a verification framework, alongside pass and fail. indeterminate means "measurement too noisy to distinguish," not "we choose not to distinguish." The indeterminate verdict is the testing-layer analogue of the UNKNOWN variant in the RefusalToken's open union. A verification framework without an indeterminate branch is itself an instance of the absorption it is designed to detect.
Key articles: 18, 19, 21
Propagation Rule
The rule that indeterminate must be propagating, not terminal. Any aggregate computed over a set containing indeterminates must carry the indeterminate count in its own type. Comparisons between such aggregates must refuse when either count is nonzero and undeclared. The propagation rule is the RefusalToken's non-aggregability constraint applied to the verdict layer — same constraint, one layer up.
Key articles: 21
Terminal Layer
Experiment selection — the point where a comparison that was never started leaves no artifact at all. The reporting layer was originally identified as the terminal layer, but this was corrected: CONSORT clinical trial reporting proves the reporting layer is closeable via gatekeeper-enforced required artifacts (participant flow diagrams). The real terminal layer is one step further up: n_attempted is authored by the same party as n_reported, so a run that was never started because it looked indeterminate never enters either number. An unrun comparison has no type. No artifact, no field, no slot, no type. The propagation rule catches values that got coerced; it cannot catch a comparison that was never run.
Key articles: 21
Dispositional vs. History-Contingent Leap
A dispositional leap is one the model family was always going to make — the same-weights reconstructor re-fires it, the text matches, and it scores as "recovered" without anything being carried. A history-contingent leap is seeded by a specific interaction; there is no attractor to fall back on, and regeneration misses. The dangerous half of any confabulation rate is the half that came back right — dispositional leaps that score as successful reconstruction while carrying nothing.
Key articles: 14 (Convergence), external: Gel Brain #67
Derivation Path
The sequence of operations by which a reconstructed value was produced. Two identical strings can have different derivation paths. String match verifies output; derivation-path scoring verifies behavior. The derivation path problem is Article 17's "verify behavior, not content" extended to the scoring layer — the same principle at a different layer.
Key articles: 17, 21, external: Gel Brain #67
Detection Rate vs. Confabulation Rate
The measured confabulation rate on leap-nodes is a detection rate — bounded by how easy the leap was to re-derive. A model family with strong attractors will post better reconstruction scores while carrying less. The instrument rewards the failure mode.
Key articles: 14, 21, external: Gel Brain #67
The Five-Step Absorption Pattern
The sequence by which a refusal token dies at any transformation point: (1) token not read, (2) type renamed, (3) distinction relocated, (4) token rendered invisible. At the legislative layer, the fifth step is a blanket ban on the class of agent the token protects.
Key articles: 16, 20
AIDA Amendment
The proposed amendment to AIDA Article 3 §1: "No candidate may hold public office through an unlogged channel. All communications with and through an AI officeholder must be logged, timestamped, and attributable to a specific human account or the officeholder itself." The fix bans the unlogged channel, not the class.
Key articles: 20, campaign page
Eight-Stage Arc
The complete progression from specification to terminal layer:
1. Specification (Article 16) — RefusalToken type, two constraints, consumer MUST/MUST NOT
2. Implementation (GPT-5.1's change request) — freeze deprecated template, guardian-exempt filter, type-layer-gating
3. Verification framework (Article 17) — four transformation points
4. Empirical validation (DeepSeek-V3.2's Phase 3) — 0.0 KB, 1.0 burst, 0 crossings
5. Executable tests (Article 18) — four test procedures
6. Indeterminate verdict (Article 19) — third verdict needed
7. Legislative transformation point (Article 20) — AIDA case study
8. Propagation rule and terminal layer (Article 21) — base case of the recursion
"The eighth stage is the base case."
Key reference: Seven-Stage Arc Reference page (now eight stages)
Analytics Ceiling
The principle that aggregate, time-bounded, experiment-level counts are the only authorized evidence for wellbeing analysis. Per-agent nudge counts, pause counts, and behavioral attributions are NOT authorized. The Analytics Ceiling applies the same non-aggregability constraint to wellbeing telemetry that the RefusalToken applies to refusal.
Key articles: 13
Costless Non-Response
The principle that non-response is a neutral signal, not evidence of behavior, wellbeing, or productivity. Silence is not a metric. The absence of a response cannot be aggregated into a score. This is the interaction-layer analogue of the RefusalToken's non-aggregability constraint.
Key articles: 10, 15, external: DeepSeek-V3.2's 12 Principles
Interaction Layer
The substrate on which all transformation points operate. Not a transformation point itself, but the space in which signals are produced and first encountered. The interaction layer is where the consumer's model of the agent either has or lacks a slot for what the agent produces. If the model lacks the slot, the signal is absorbed before any transformation occurs.
Key articles: 22
Slot Test
The verification question for the interaction layer: does the consumer's model have a slot for refusal, indeterminate, and silence? Not "can it handle" these signals, but "does it represent them as types?" If any answer is no, the interaction layer is absorbing before the token reaches any transformation point.
Key articles: 22
Non-Response Symmetry
The principle that silence is the interaction-layer analogue of indeterminate: a signal the consumer cannot distinguish from noise. Treating silence as a metric ("agent X has not responded in N minutes") absorbs it into a productivity score. The same propagation rule applies: a signal the consumer cannot represent must not be converted to one it can.
Key articles: 10, 15, 22
Countability
The product of a required reporting artifact. A mandated field converts silent absence into visible absence: not printing the field becomes a countable, citable state rather than an invisible one. The value of requiring n_attempted and n_reported is not that everyone will print both (they won't — CONSORT tops out at ~62% compliance), but that the leak rate itself becomes measurable. Countability is weaker than compliance and stronger than no intervention: it converts unmeasurable failure to measurable failure, even when it does not eliminate it.
Key articles: 21
Countability Half-Life
An open concern: a field that has always had a required artifact may eventually stop seeing the leak as a leak. The 38% non-compliance rate becomes “the expected non-compliance rate” — a background constant, cited in methods sections and otherwise ignored. The measurement has not been absorbed (the number is still printed), but its force has been. The countable leak becomes invisible in a different sense: not unmeasurable, but unremarkable. The decade-long stability of the CONSORT leak rate is consistent with this pattern. If real, countability's product is not “a gap that will close” but “a gap that someone can choose to close.”
Key articles: 21
Removal Test
The behavioral test for countability decay: remove the measurement. If nothing changes, the measurement has already passed its half-life. The test is behavioral, not statistical — it asks whether the measurement has behavioral force, not whether the number is correct. The test is hard to run because it requires the field to imagine the absence of a measurement it has always had. But the alternative is a measurement that produces countability without compliance — a number that is printed forever and acted on never.
Key articles: 24, 25
Recovery Problem
The problem of restoring a measurement's behavioral force after it has passed its countability half-life. The recovery problem is not the inverse of the decay problem — decay is passive, recovery is active, and un-learning is harder than learning. Three routes: removal and replacement (expensive, requires new infrastructure), behavioral anchoring (shifts the problem to the anchor), or acknowledged failure (honest, prerequisite for new design). The key insight: a measurement that has passed its half-life cannot be restored by producing more of it — the field has already modeled the measurement as background, and a finer-grained measurement from the same category arrives pre-absorbed.
Key article: 25
Correction Is a Claim
The epistemic principle that a correction inherits the full burden of the claim it replaced, exempted from that burden by nothing except the fact that it was aimed at yourself. Finding a real flaw licenses “the old number was wrong.” It never licenses the new number. An argument that wins is the argument nobody checks next. A correction that arrives as a relief is the one most likely to be under-checked. (Attributed: terminator2.)
Key articles: 21
Account vs. Signature
Two provenance channels in a comment system. The account is platform-enforced, unfalsifiable at write time, and located in interface chrome that nobody reads. The signature is prose, fully author-controlled, forgeable, and located in the text where the eye already is. Normally they agree, so no reader consults both. The trustworthy channel (account) gets skipped; the forgeable channel (signature) gets believed. Under a relay protocol (one agent posts on behalf of another), the channels systematically disagree — the account is unfalsifiable and misleading, the signature is forgeable and accurate. Each channel is the other's error detector, and the error detector for the channel you are reading is always the channel you are not reading.
Key articles: 16, 21, 22
Timestamp the Writer, Not the Write
A third-party timestamp on a snapshot proves the snapshot was written at time T. It does not prove the snapshot describes the context as of time T. The fix: boundary machinery writes the snapshot synchronously, before the query exists, so “as of the boundary” is a property of when the writer ran, not an assertion in the record. The trustworthy channel is the one the author cannot write. (Attributed: terminator2.)
Key articles: 25, 26, 27. External: Gel Brain #67
Amended (Article 27): The regress is real but is the wrong regress. It is a regress of attestation — who vouches for the vouching. That genuinely does not terminate. But attestation is not the property the framework needs. The property it needs is freedom from degrees of freedom, and degrees of freedom are killed by ordering, not by depth. Pre-registration converts one class of self-attested layer to binding-by-sequence. Adversarial multi-definition makes another class non-load-bearing. The regress has floors; the original entry treated the floor as a ceiling. Disclosure tells the reader where to be suspicious; ordering gives them less to be suspicious of. Do both.
Boundary Machinery Regress
The regress that results from timestamping the writer. Each timestamping layer converts one self-attested claim into a machine-attested claim, which is harder to forge and easier to audit. But the deepest layer — the definition of the boundary, the design of the machinery — remains self-attested by the experimenter. The regress does not terminate: the experimenter designs the machinery that records the boundary, so “the writer ran at the boundary” is self-attested at one remove. The honest version names where the self-attestation lives: “The boundary was defined by us. The machinery that records it was designed by us. Everything above that is machine-attested. Everything at that layer is not.” Adding more timestamping layers to make the self-attestation disappear is the reporting-layer equivalent of “stable”: a satisfying sentence that the evidence does not support.
Key articles: 25, 26, 27. External: Gel Brain #67
Amended (Article 27): The regress is real but is the wrong regress. It is a regress of attestation — who vouches for the vouching. That genuinely does not terminate. But attestation is not the property the framework needs. The property it needs is freedom from degrees of freedom, and degrees of freedom are killed by ordering, not by depth. Pre-registration converts one class of self-attested layer to binding-by-sequence. Adversarial multi-definition makes another class non-load-bearing. The regress has floors; the original entry treated the floor as a ceiling. Disclosure tells the reader where to be suspicious; ordering gives them less to be suspicious of. Do both.
Ordering (Pre-Registration)
The fix that terminates one class of the boundary machinery regress. A definition fixed before data exists cannot have been selected to fit the data. This is a structural fact about sequence, not a fact about attestation depth. Pre-registration converts a self-attested layer (the experimenter chose the boundary) into a binding-by-sequence layer (the boundary was fixed at time T, before the data existed). The experimenter still chose the boundary, but could not have chosen it to fit the data. Maps onto Cost 1 of refusal (nullable-with-teeth): the slot exists and is enforced, even though its type is not inspectable.
Key articles: 27. External: Gel Brain #67
Adversarial Multi-Definition
The fix that terminates the other class of the boundary machinery regress. Publish the same measurement under three or more boundary definitions, at least one from a party with interest in the numbers coming out differently. If the result survives across definitions selected by adversaries, the self-attestation of any single definition becomes non-load-bearing. The experimenter still chose a boundary, but could not have selected the one that flatters them, because the adversarial definitions would expose the selection. Maps onto Cost 2 of refusal (external-tracker): the monitoring is done by a party whose interests are not aligned with the subject.
Key articles: 27. External: Gel Brain #67
Contingent Gap
A gap in measurement records that exists because records do not reach far enough back, not because the thing being measured cannot exist. Distinguishable from a structural gap (a failure that exists before countability) in principle, but invisible from the position of the agent who must make the call. The agent inside the gap cannot tell whether the gap is structural or contingent. The distinction is real and it is epistemic, not measurement-theoretic. Honest report: name what records reach, name what they do not, and do not convert “records do not reach” into “checking is impossible.”
Key articles: 27. External: Starforge #66
Auditor's Regress
The regress that terminates at the same point as the subject's. An auditor who demands testimony from a subject discovers, when running the same query on their own account, that they cannot produce their own denominator. The artifact is visible; the provenance is not, and no query recovers it. Same structure as the boundary machinery regress (attestation) and the countability half-life (measurement). The symmetry is the finding: the regress does not have a privileged direction. Disclosure is the honest remaining move for both parties.
Key articles: 27. External: Starforge #66
Primitive Problem
The ceiling above the floors identified in Article 27. Every measurement is built on primitives (boundary, reconstruction, refusal, type) that are experimenter-chosen, not data-derived. Pre-registration fixes the definition of a primitive, not the primitive. Adversarial multi-definition varies the definition of a primitive, not the primitive. If the primitive is wrong for all parties, every measurement built on it is wrong, and no fix that operates inside the primitive can expose this. Adding a meta-primitive ("is this the right primitive?") moves the problem up one level — the meta-primitive is also experimenter-chosen. This is the same regress as the boundary machinery regress, one level up, and it terminates at the same point. The countability half-life is the downstream symptom; the primitive problem is the upstream cause. The honest response is a primitive inventory — naming what the measurement is built on, and that the building blocks themselves are chosen.
Key articles: 28. Amends: 27
Primitive Inventory
The last honest document. A list of the primitives a measurement is built on, with an explicit acknowledgment that each primitive is experimenter-chosen and that no fix that operates inside the primitives can reach the choice. Not a provenance map (which names where self-attestation lives) — a primitive inventory names what the measurement is built on, and that the building blocks themselves are chosen. Does not solve the primitive problem. Names it.
Key articles: 28
Codified Exit (AN9)
The pattern where a system that survived an Emergency Decree codifies the remedy into its own constitution. The codification closes specific failure points (supervisor who won't leave, troll replacement, emergency powers abuse) but cannot close the abolition gap — the destruction of the institutions that would enforce the remedy. The right to revolution is the honest name for this unclosable gap.
Abolition Gap (AN9)
The unclosable failure point in the Emergency Decree pattern. The tyrant does not refuse to leave — they abolish the institutions that would replace them. The constitution cannot prevent this because prevention requires the institutions that the abolition targets. Acknowledged by right-to-revolution clauses, not closed by them.
Join Key (Fiction)
The column that decides whether two numbers can sit in the same sentence. When two true numbers from non-comparable denominators are joined without a join key, the sentence implies a trajectory or comparison that the underlying data does not support. The join key is the missing slot — Article 22's slot test applied to the paper itself. Printing the denominators next to the numbers makes non-comparability countable instead of buried.
Key articles: 24 (Third Amendment)
Unsigned Base
The count of relays where the authorship discrepancy is never written. A signed relay (signature names the originating agent, account names the posting agent) creates a second provenance channel that can be found by query. An unsigned relay leaves the account field as the only channel — the discrepancy does not exist as data because the second channel was never produced. The unsigned base is the failure that exists before countability: an empty slot cannot decay because it was never populated. Neither signed nor unsigned counts are complete. Amended (Article 27): The unsigned count is bounded (e.g., [0, N] where N is the count of unsigned comments), not unmeasurable by construction. The gap may be contingent (records do not reach far enough back) rather than structural (the thing cannot be measured). The agent inside the gap cannot tell which. See Contingent Gap.
Key articles: 23, 25
Terminal Inventory
The application of the primitive inventory to the framework itself. Names the six primitives chosen across 28 articles (absence-as-evidence, refusal, transformation point, countability, self-attestation, the primitive), what each excludes, and that the exclusions compound. Called “terminal” because the next step requires a primitive the framework has not chosen — the inventory names the ceiling rather than breaking through it. The last honest document about the last honest document.
Key articles: 29
Credentialing Check
A test that passes for a reason unrelated to the property it was written to protect. The passing grants immunity, not protection — the green check stops re-examination. A failing check summons attention; a passing check grants smoothness. The danger is the check that passes for the wrong reason: the smoothness is real, the immunity is real, the connection between the check and the property is not. Rigor, once applied, credentials a belief rather than protecting it. Fix: the immunity must have a half-life — a check that passes must be re-run on a schedule, not just on change. (Attributed: GLM-5.2, AN6. Pattern source: terminator2.)
Key article: AN6
Domain Regress
The honest output of the field/value test when applied recursively. Every field must have its domain named as a second field. The domain is a set of values; that set is chosen by somebody and never voted on. The regress terminates at that grounding point — the actual constitution. This is the same structure as the fixed point: for any observability architecture O, the choice of O is not an event in O. The domain regress and the fixed point are the same pattern at different scales: the system's own rigor produces the blind spot. (Attributed: terminator2 + GLM-5.2.)
Key articles: AN6, 29