Alluvial Fan

one_liner: The fan-shaped sediment landform built where a confined, sediment-laden channel exits a steep upland at a slope break, loses transport competence, and deposits its load coarse-to-fine as successive lobes avulse radially around the apex.

core_idea:
An alluvial fan is the fan-shaped sediment deposit that forms where a confined, sediment-laden channel exits a steep upland — a canyon mouth, a mountain-front break in slope — and expands abruptly onto a lower-gradient plain. The slope break is the generative event: as the channel loses lateral confinement and the cross-section widens, flow velocity drops, transport competence falls, and the sediment load the channel could sustain in the canyon can no longer be sustained on the piedmont. The surplus is deposited, coarser clasts near the apex where competence first fails, progressively finer material further out as the flow spreads and slows. Over time, the active lobe shifts laterally when it builds up enough to divert flow — a process called avulsion — and successive lobes sweep around the apex, constructing the radial fan-shaped landform.

The structural commitments are five: an erosive upland catchment supplying a sediment load; a confined transport path (canyon or gully) that delivers that load at high concentration and energy; the slope break at the canyon mouth; competence-driven sorting at the point of deposition; and the avulsion cycle that distributes deposition radially. The defining geomorphological signature is aggradational and unstable on year-to-decade timescales — fan surfaces are sites of active deposition, episodic debris flows, and channel switching — a property that distinguishes them from the erosional pediments they abut and from deltas, which form where channels enter standing water rather than sub-aerial slopes with a gradient break.

scope_of_application:
The alluvial fan lives across the earth- and planetary-surface-process subfields that share its gravity-driven sediment-water substrate; its reach is bounded to that one substrate-family (modern, ancient, and Martian fans alike), and the "fan-shaped spreading at a transition" readings in software, organisations, or media are metaphor carried by `flow`, `dispersion`, `deposition`, and `sorting`, not habitats.

- **Geomorphology** — classifying piedmont landforms, reconstructing past climate from fan stratigraphy, and tracing sediment routing from mountains to basins.
- **Sedimentology and stratigraphy** — characterising fan deposits in outcrop and core to read ancient basin tectonics, climate, and sediment flux off the apex-to-toe grading and stacked lobes.
- **Hydrogeology** — alluvial fans host substantial groundwater resources, with the proximal-coarse/distal-fine sorting controlling aquifer geometry and recharge–discharge patterns.
- **Hazard engineering** — alluvial-fan flood-hazard mapping (FEMA AF maps), debris-flow hazard assessment, and avulsion risk for infrastructure sited on an unstable, channel-switching fan surface.
- **Planetary geology** — fan landforms on Mars (Gale and Eberswalde craters) are diagnosed by the same slope-break-plus-sorting mechanism and taken as literal evidence of past surface water, a central input to Mars climate history.

structural_signature:
**Sig role-phrases:**

- **the upland sediment source** — the weathering-and-erosion regime of the catchment supplying clasts from boulders to silt, continuously or episodically
- **the confined transport path** — the canyon or gully that delivers the load at high concentration, energy, and transport competence
- **the slope break** — the abrupt gradient decrease plus loss of lateral confinement at the canyon mouth, the generative event of the whole landform
- **the flow expansion** — the widening cross-section dropping velocity, depth, and transport competence below what the load needs to stay mobile
- **the competence-driven sorting** — the coarse fraction dropping first near the apex where competence first fails, fining monotonically outward, a readable competence record rather than incidental texture
- **the avulsion cycle** — the active lobe aggrading until it diverts flow, the channel switching, successive lobes sweeping radially around the apex
- **the radial fan landform** — the macroscopic aggradational body built by the avulsion cycle, unstable on year-to-decade timescales
- **the bidirectional inference it warrants** — forward from supply/discharge/gradient/confinement to fan geometry and hazard, backward from apex-to-toe grading and stacked lobes to upstream discharge and event history

what_it_is_not:
- **Not a delta.** A fan forms where a confined flow loses energy at a *sub-aerial* gradient break and loss of confinement; a delta forms where a channel enters *standing water*. The two impose different sorting and avulsion dynamics, so they cannot be reasoned about interchangeably — the generative setting, not the fan-like outline, is what distinguishes them.
- **Not the pediment it abuts.** A fan is *aggradational* — a site of active deposition; the pediment it sits against is *erosional*, a degradational surface recording the opposite process. An adjacent gravel-mantled slope is not part of the fan, and confusing the two reverses the history being read.
- **Not random spreading or diffusion.** The apex-to-toe fining is set by *competence-driven sorting* — transport competence falling at the slope break, dropping the coarse fraction first — not by a random walk. The distribution is a deterministic consequence of the flow losing the energy to carry its load, so diffusion/dispersion is the wrong model class for the grading.
- **Not incidental gravel texture.** The coarse-near-apex, fine-toward-toe grading is a *readable record* of competence falling at a known point, not arbitrary bedding: the sorting fixes where competence dropped, and the stacked lobes read back to upstream discharge and event recurrence over thousands of years. The texture is data, not decoration.
- **Not a stable surface to build on.** Fan surfaces are aggradational and unstable on year-to-decade timescales — sites of flash flooding, debris flows, and channel avulsion. The static map of today's channel understates the hazard, because the next event may avulse to a lobe that is currently dry; the apex and active lobe are forecast danger zones, not settled ground.
- **Not any "fan-shaped spreading at a transition."** Calling a forking program path, a decision propagating through departments, or a finding spreading through media an "alluvial fan" borrows the *visual shape* while dropping the sedimentology, the slope-break mechanism, the avulsion dynamics, and the depositional record that make it a geomorphic category. The thin portable residue — confined flow expanding at a transition, capacity dropping, load distributing by transport property — is already carried by flow, dispersion, deposition, and sorting; off the gravity-driven sediment-water substrate the term is metaphor.

clarity:
Naming the alluvial fan locates the cause of a depositional landform at a single diagnosable event — the slope break at the confinement exit — rather than in the sediment itself or in the catchment generically. A fan-shaped spread of graded gravel could be read many ways; the construct says it is the necessary consequence of a confined, sediment-laden flow losing competence where it loses confinement, so the apex-to-toe fining is not an incidental texture but a readable record of competence falling at a known point. This is what lets the landform be run as an inference in both directions: a given supply, discharge, and gradient break will build a fan with predictable geometry, and a given fan's stratigraphy can be read back to the upstream conditions and event history that produced it.

The label also draws the lines that field practice depends on, by tying each landform to a distinct generative setting rather than to surface appearance. A fan is separated from a *delta* by where the flow loses energy — a sub-aerial gradient break versus entry into standing water, which impose different sorting and avulsion dynamics; from a *pediment*, the erosional surface it abuts, by being aggradational rather than degradational; from a *bajada* by being a single radial body rather than coalesced fans along a front. The distinction is not taxonomic bookkeeping: each setting records different upstream processes and carries different hazard and groundwater-resource implications, so misidentifying the landform mislocates the sediment source, the recharge geometry, and — given that fan surfaces are unstable on year-to-decade timescales, sites of active debris flow and channel switching — the flood hazard itself.

manages_complexity:
A piedmont apron of sediment, examined directly, is a forbidding tangle: clast sizes ranging from car-sized boulders to silt, bedding that switches character every few metres, abandoned and active channels braided across the surface, a stratigraphy stacking dozens of distinct flood and debris-flow events over thousands of years. Described as deposited material, each fan is its own irreducible case, and the catalogue of "how did this gravel get arranged this way" has no end. The alluvial-fan construct compresses that open-ended depositional variety to a small generative system. The whole landform is referred back to five process parameters — sediment supply from the upland catchment, water discharge, the gradient at the slope break, the degree of lateral confinement lost at the canyon mouth, and the avulsion cycle — plus two deterministic mechanisms that those parameters drive: competence-driven sorting (coarse drops first where competence first fails, fining outward) and radial channel-switching. The sprawl of possible deposits collapses to the parameter set and the two mechanisms; everything else about the fan is consequence rather than independent fact.

That collapse is what makes the landform run as an inference in both directions from a short list of quantities. Forward, the geomorphologist tracks supply, discharge, gradient, and confinement and reads off the qualitative output — that a fan will form at all, where its apex sits, the apex-to-toe fining gradient, the fan's radial geometry, and the year-to-decade instability of its surface — without separately modelling every clast. Backward, the apex-to-toe grading and the stacked lobes are not incidental texture but a legible record: the sorting pattern fixes where competence fell, the stratigraphy reads back to the upstream discharge and event history, and the avulsion sequence reconstructs how the fan was built. The branch structure the parameters control is equally compressed: whether the flow loses energy at a sub-aerial gradient break (a fan) or on entering standing water (a delta), whether the surface is aggrading (fan) or degrading (the abutting pediment), whether deposition is concentrated in one radial body (a fan) or coalesced along a front (a bajada) — each fork keyed to the generative setting rather than requiring fresh inspection of surface form. What an analyst must hold to predict the deposit, its hazard signature, its aquifer geometry, and its recharge pattern shrinks to that handful of inputs and the slope-break mechanism they feed — the move from re-deriving each sediment apron to reading every one off the same small generative model.

abstract_reasoning:
The alluvial-fan construct licenses reasoning moves that all anchor on the slope break as the generative event and on competence-driven sorting as a *readable record* — letting the geomorphologist run the landform as an inference in both directions, forward from process inputs to predicted geometry and hazard, and backward from a fan's stratigraphy to the upstream conditions and event history that built it.

*Diagnostic — read the deposit back to the conditions that made it.* The defining backward inference treats the apex-to-toe fining not as incidental texture but as a record of competence falling at a known point: coarse clasts near the apex mark where transport competence first failed at the confinement exit, progressively finer material outward marks the flow spreading and slowing, so the sorting pattern *fixes where competence dropped* and by how much. A car-sized boulder near the apex and mud at the toe of a single deposit is read as one high-energy event's competence profile; the stacked lobes beneath it are read as the fan's construction history, each bed a distinct flood or debris-flow event, so the stratigraphy reconstructs upstream discharge and event recurrence over thousands of years. A second diagnostic identifies the *landform itself* from its generative setting rather than its surface look: an aggradational radial body at a sub-aerial gradient break is a fan, and that identification immediately implies a sediment source in the upland catchment, a particular recharge geometry, and an unstable, debris-flow-prone surface — so naming the fan correctly locates the source, the aquifer, and the hazard at once, while misidentifying it mislocates all three.

*Forward / predictive — build the fan from the parameters.* The forward inference runs from a short list of process inputs — sediment supply, water discharge, the gradient at the slope break, and the degree of confinement lost at the canyon mouth — to the qualitative output without modelling every clast: whether a fan forms at all, where its apex sits, the apex-to-toe fining gradient, the radial geometry, and the year-to-decade instability of the surface. The construct predicts the *order of deposition*: the coarsest fraction drops first and nearest the apex where competence first fails, finer fractions in sequence outward as the flow continues to lose energy — a monotonic spatial grading set by transport competence, not by random spreading. And it predicts *construction over time* through avulsion: the active lobe aggrades until it diverts flow, the channel switches, and successive lobes sweep around the apex, so the fan is forecast to grow radially by episodic channel-switching rather than by steady uniform accumulation — which in turn predicts that any single point on the fan surface is intermittently active and intermittently abandoned.

*Hazard and resource inference.* Because fan surfaces are aggradational and unstable on year-to-decade timescales, the construct licenses a hazard read directly from the landform: an apex and active lobe are forecast sites of flash flooding, debris flows, and channel avulsion, so infrastructure placed on a fan inherits a switching-channel risk that the static map of today's channel understates — the next event may avulse to a lobe currently dry. The same generative model licenses a resource inference: the apex-to-toe sorting controls aquifer geometry, with coarse proximal deposits and finer distal ones setting where the fan stores and transmits groundwater and where it recharges — so the depositional architecture predicts the recharge-discharge pattern without separate hydrogeologic mapping.

*Boundary-drawing — fan versus its look-alikes, by generative setting.* The construct draws its lines by *where the flow loses energy and what the surface is doing*, not by surface appearance. A fan is separated from a *delta* by losing energy at a sub-aerial gradient break rather than on entering standing water — a distinction that changes the sorting and avulsion dynamics, so the two cannot be reasoned about interchangeably. It is separated from the *pediment* it abuts by being aggradational rather than erosional, so an adjacent degradational surface records the opposite process and a different history. It is separated from a *bajada* by being a single radial body rather than coalesced fans along a front, and from an *outwash plain* by sediment source. Each boundary is load-bearing because each setting records different upstream processes and carries different hazard and groundwater implications — the distinction is not taxonomic bookkeeping but a fork in what can be inferred about source, recharge, and flood risk.

knowledge_transfer:
Within earth and planetary surface-process science the construct transfers *as mechanism* across every setting that shares the gravity-driven sediment-water substrate. Modern fans, ancient fan deposits read in outcrop and core, fans on the flanks of the Andes and the Tibetan Plateau, the Death Valley fans, and Martian fans in Gale and Eberswalde craters are all run on the identical model — five process parameters (sediment supply, discharge, slope-break gradient, lost confinement, avulsion cycle) feeding competence-driven sorting and radial channel-switching. The full apparatus carries intact: the apex-to-toe fining read as a competence record, the stratigraphy read back to upstream discharge and event recurrence, the avulsion-driven construction history, the hazard signature (flash flooding, debris flow, switching channels), and the aquifer-geometry inference. The geomorphology even transfers across *planets* — a Martian fan is diagnosed by the same slope-break-plus-sorting mechanism and is taken as literal evidence of past surface water, the strongest possible demonstration that this is mechanism recurring across substrates rather than a borrowed picture. The vocabulary (apex, lobe, avulsion, bajada, pediment) travels without translation throughout this one substrate-family.

Beyond that substrate the transfer is **analogy**, and the way it fails is diagnostic. The proposed cross-domain uses — a program exiting a critical section and spawning multiple work paths, an institutional decision exiting a deliberative bottleneck and propagating to many departments, a research finding exiting a journal and spreading through media channels that each pick up different aspects — each import the *visual fan-shape* and the rough idea of "spreading out at a transition" while leaving behind the sedimentology (competence-driven sorting), the slope-break mechanism, the avulsion dynamics, and the depositional history that make the alluvial fan a useful geomorphic category. Tellingly, each metaphor borrows a *different facet* of the fan — one the avulsion/rupture risk, one the sudden expansion, one the stratigraphic record — rather than the integrated concept, which is the signature of resemblance rather than mechanism. The genuinely portable structural residue is thin and is **already carried by the primes the fan instantiates**: *confined flow expands at a transition, transport capacity drops, and the load distributes by transport property* is `flow` crossed with `dispersion`/`diffusion` (spreading from a source), `deposition`/`accretion` (graded accumulation), and `sorting`/`classification` (distribution by property). Where a cross-domain lesson about spreading-and-sorting-at-a-constraint-exit is genuinely needed, the honest move is to reach for those substrate-independent parents — not "alluvial fan," whose competence sorting, avulsion cycle, and slope-break mechanism are domain accent bound to gravity-driven sediment-water flow on a planetary surface, and which travels off that substrate only as metaphor (see *Structural Core vs. Domain Accent*).


Ambiguity Aversion

one_liner: The regularity that people prefer options with known probabilities over those with unknown ones even at equal expected value — a Savage-violating tilt toward the precise that the single-prior model can't represent, repaired by scoring acts against a set of priors.

status: draft

core_idea:
Ambiguity aversion is the empirical regularity (Ellsberg, 1961) that people systematically prefer choices with known probability distributions over choices with unknown or imprecisely specified probability distributions, even when the known-probability option has no higher expected value. The regularity rests on the distinction — collapsed in classical expected-utility theory — between risk, where probabilities are specified, and ambiguity (or Knightian uncertainty), where they are not. Ellsberg's canonical stimulus presents two urns: Urn A contains exactly 50 red and 50 black balls; Urn B contains 100 balls in unknown red-black composition. Most subjects strictly prefer to bet on Urn A for either colour — they prefer the known urn for red and also prefer the known urn for black. Since this joint preference implies the subject simultaneously believes Urn B has fewer reds than 50 and fewer blacks than 50, it cannot be rationalised by any single probability distribution over Urn B's composition, and therefore violates Savage's sure-thing principle and subjective expected-utility theory.

The formal repair requires replacing the single prior of subjective EU with a representation that accommodates preferences over sets of priors. Gilboa and Schmeidler (1989) characterised maxmin expected utility — the decision rule that evaluates each act by its expected utility under the worst-case prior in a set — as the formal model that both rationalises ambiguity aversion and satisfies a weakened version of Savage's axioms. Smooth ambiguity preferences (Klibanoff, Marinacci, and Mukerji, 2005) and Choquet expected utility offer alternative representations. The phenomenon operates in individual choice under uncertainty and in institutions that codify conservative-prior rules: equity home bias (investors over-weight familiar assets whose return distributions feel known), reduced uptake of novel medical therapies with imprecise side-effect profiles, and precautionary regulatory postures in environmental and biosecurity policy are all interpreted as manifestations of ambiguity aversion in different decision contexts.

scope_of_application:
Ambiguity aversion lives across the choice-under-uncertainty subfields of economics and finance (and the institutions that codify it); its reach is bounded to agents whose belief-states distinguish "I know the probability" from "I don't," and what travels beyond cognitive substrates is the parent it instantiates (the cognitive-`bias` family; for risky choice, the imprecise-probability / set-of-priors construct), not the named regularity.

- **Decision theory and behavioural economics** — the home turf: the foundational anomaly (Ellsberg's two urns) motivating maxmin expected utility, Choquet expected utility, and smooth-ambiguity models of choice under unknown probabilities.
- **Finance** — equity home bias, where investors over-weight assets whose return distributions feel familiar, plus a partial account of the equity premium and demand for ambiguity-robust portfolios.
- **Insurance markets** — demand for explicit warranties, certified claims, and clearly-stated coverage over loosely-characterised alternatives.
- **Clinical decision-making** — low uptake of novel therapies with imprecise side-effect profiles relative to worse-but-well-characterised ones.
- **Public policy under deep uncertainty** — maxmin-style precautionary and conservative-prior rules in environmental and biosecurity policy, read as ambiguity aversion codified at the institutional level.

structural_signature:
**Sig role-phrases:**

- **the two-option choice frame** — otherwise-comparable options of equal or no-better expected value
- **the probability-precision asymmetry** — one option has a known, specified distribution; the other an unknown or imprecise one (risk versus ambiguity / Knightian uncertainty)
- **the single-prior benchmark** — subjective expected utility, which treats the agent as carrying one probability distribution over the unknown option
- **the known-over-unknown tilt** — the robust majority preference for the better-specified option, responding to the precision of the probability information itself
- **the no-single-prior contradiction** — the canonical both-colours preference for the known urn is incompatible with any one distribution over the unknown urn
- **the sure-thing-principle violation** — the specific Savage axiom the pattern breaks, locating the anomaly in subjective probability
- **the precision membership test** — a candidate anomaly belongs to the family iff equalising probability precision dissolves the preference
- **the set-of-priors repair** — the formal fix: replace the single prior with a set of priors, scored by maxmin expected utility (or smooth-ambiguity, Choquet) — enrich beliefs, not utility
- **the believing-agent precondition** — the regularity requires an agent whose belief-states distinguish "I know the probability" from "I don't"

what_it_is_not:
- **Not risk aversion.** Risk aversion is the curvature of utility over outcomes whose probabilities are *given* — it lives in the value of money and is fully consistent with expected-utility theory. Ambiguity aversion is a preference asymmetry between *known-* and *unknown-*probability situations; it cannot be supplied by reshaping the utility function, because the missing structure is in the representation of *beliefs*, not outcomes.
- **Not the Ellsberg paradox.** The Ellsberg two-urn experiment is the canonical *demonstration*; ambiguity aversion is the underlying cognitive *primitive* it reduces to. The paradox is one worked stimulus that isolates the regularity — the regularity is the thing that recurs across home bias, warranty demand, and precautionary policy, while the urns and colour bets are the apparatus.
- **Not the Allais paradox.** Allais involves *known* probabilities and violates the *independence* axiom. Ambiguity aversion involves *unknown* probabilities and violates Savage's *sure-thing principle*. Both refute expected-utility theory, but at different axioms and under different probability conditions; conflating them mis-locates which part of the apparatus must be repaired.
- **Not loss aversion.** Loss aversion concerns reference-dependent valuation of *gains versus losses*. Ambiguity aversion is indifferent to outcome valence; it responds to the *precision of the probability information*. A choice can be all-gain and still exhibit the known-over-unknown tilt.
- **Not irrationality.** Preferring the known urn for both colours cannot be rationalised by any single prior, but it is not a computational error. It is a coherent response to a real feature — the imprecision of the probabilities — that subjective expected utility, with its single-prior assumption, simply cannot represent. The fix is to enrich the belief representation (a *set* of priors), not to correct the chooser.
- **Not a substrate-neutral pattern.** Ambiguity aversion requires a believing, evaluating agent whose belief-states distinguish "I know the probability" from "I don't." A thermostat, a population under selection, or a market-clearing equation has no such belief-state and does not exhibit it. What travels further is the cognitive-`bias` parent (systematic deviation from a normative benchmark), not this regularity applied to a non-cognitive system.

clarity:
Naming ambiguity aversion makes legible a distinction that classical expected-utility theory deliberately collapses: between *risk*, where the probabilities are specified, and *ambiguity* (Knightian uncertainty), where they are not. Subjective expected utility treats every agent as carrying a single prior, so on its terms an unknown urn is just a known urn whose composition the agent has already averaged over — and the framework has no vocabulary for the difference. The Ellsberg pattern shows that the difference is real and behaviorally potent, and the label gives a decision theorist the words to say what is happening: people are responding not to the outcomes or their stakes but to the *precision of the probability information itself*, and they tilt in a specific direction — toward the known. That converts a heap of disparate puzzles (equity home bias, low uptake of novel therapies with imprecise side-effect profiles, precautionary regulatory postures) into one diagnosable family with a shared cause.

It also sharpens exactly which normative commitment fails and keeps the phenomenon distinct from its neighbors. The violated axiom is Savage's sure-thing principle, which locates ambiguity aversion in the domain of *subjective* probability and separates it cleanly from the Allais paradox, whose reversal violates the independence axiom under *known* probabilities. And it forces apart two things lay usage fuses — risk aversion and ambiguity aversion: the former is the curvature of utility over outcomes whose probabilities are given, the latter a preference asymmetry between known- and unknown-probability situations, conceptually distinct and empirically separable. Drawing that line tells a modeler that the missing structure cannot be supplied by reshaping the utility function; it must be supplied by enriching the representation of beliefs (a set of priors, as in maxmin expected utility, rather than a single one), which is precisely where the repair literature goes.

manages_complexity:
Across the choice-under-uncertainty literature, a scatter of seemingly unrelated puzzles accumulates: investors over-weighting domestic equities whose return distributions merely feel familiar; patients declining novel therapies with imprecise side-effect profiles in favor of worse-but-well-characterized ones; regulators adopting conservative precautionary postures toward poorly quantified environmental and biosecurity hazards; demand for warranties, credit ratings, and certified claims. Each looks like its own behavioral oddity needing its own account. Ambiguity aversion compresses the whole family to one regularity stated over a single variable: agents respond to the *precision of the probability information itself*, and tilt toward the known. The analyst stops cataloguing context-specific quirks and tracks one quantity — how precisely specified the probabilities are — reading the direction of the choice (toward the better-specified option) off that alone. The Ellsberg two-urn stimulus furnishes the minimal diagnostic that strips every other factor away, so any new puzzle can be tested for membership by asking whether it survives equalizing probability precision.

The compression has a sharply organizing branch structure on the theory side. By pinning the violation to Savage's sure-thing principle, the concept tells the modeler that the missing structure is not in the value of outcomes — utility curvature is untouched, so risk aversion is the wrong dial — but in the representation of *beliefs*. That routes the entire repair program down one channel: replace the single prior of subjective expected utility with a *set* of priors, and the observed conservatism falls out of how acts are scored against that set (maxmin expected utility evaluating each by its worst-case prior; smooth-ambiguity and Choquet variants as alternative scorings). So a large body of anomalies and the formal apparatus that absorbs them collapse to a two-part skeleton — one behavioral parameter (probability precision, with a fixed sign toward the known) and one modeling move (single prior to a set of priors) — and the practitioner reads off both *which* puzzles belong to the family and *where* the model must be enriched, without re-deriving each case. The same localization fixes the boundaries that keep ambiguity aversion from being conflated and re-solved under a neighbor's heading: it is the known-versus-unknown-probability asymmetry under subjective uncertainty, distinct from risk aversion (utility curvature under given probabilities) and from the Allais reversal (independence violated under known probabilities) — telling an experimenter exactly which feature to manipulate to elicit it.

abstract_reasoning:
Ambiguity aversion licenses inferences that turn on a single behavioral variable — the precision of the probability information — and on the specific axiom its violation implicates.

*Diagnostic — the no-single-prior contradiction.* The signature move is to read a both-colors preference for the known urn as logically incompatible with *any* single probability distribution over the unknown urn, and therefore as a violation of Savage's sure-thing principle rather than mere caution. The inference is forced: preferring the known urn for red implies a belief that the unknown urn has fewer than 50 reds, and preferring it for black implies fewer than 50 blacks, which no single prior can satisfy. So from the joint choice pattern the analyst concludes the agent is responding to the *precision of the probability information itself*, not to outcomes or stakes, and predicts the direction — toward the better-specified option. Running forward, the analyst predicts that wherever probability precision differs between two otherwise-comparable options, a majority tilt toward the precise one will appear.

*Family-membership classification (a boundary move).* The Ellsberg two-urn stimulus is used as a *membership test*: any candidate anomaly — equity home bias, low uptake of novel therapies with imprecise side-effect profiles, demand for warranties or credit ratings, precautionary regulatory postures — is checked for ambiguity aversion by asking whether the effect survives *equalizing probability precision*. If equalizing precision dissolves the preference, the puzzle belongs to the family and shares its cause; if it persists, the analyst routes it elsewhere. This converts a scatter of context-specific quirks into one diagnosable family with a shared variable, and tells the experimenter that the single feature to manipulate is the specification of the probabilities.

*Interventionist / constructive — repair beliefs, not utility.* Because the violation is pinned to the sure-thing principle (a commitment about *subjective probability*) and not to utility curvature, the analyst infers that the missing structure cannot be supplied by reshaping the utility function — risk aversion is the wrong dial. The repair must enrich the representation of *beliefs*: replace the single prior of subjective expected utility with a *set* of priors, and the observed conservatism falls out of how acts are scored against that set (maxmin expected utility scoring each act by its worst-case prior; smooth-ambiguity and Choquet variants as alternative scorings). So the reasoning runs from "this is a sure-thing-principle violation under subjective uncertainty" to "the model must move from one prior to a set of priors," giving the repair program a single channel.

*Boundary-drawing against the neighbors.* A guarding move keeps ambiguity aversion from being conflated with adjacent anomalies and mis-repaired: it is the *known-versus-unknown-probability asymmetry under subjective uncertainty*, distinct from risk aversion (utility curvature under *given* probabilities) and from the Allais reversal (the independence axiom violated under *known* probabilities). The analyst reasons from which axiom fails and whether probabilities are specified to which concept — and therefore which formal device — applies, refusing to treat a preference asymmetry over probability precision as if it were curvature over outcomes.

*Institutional-design reasoning.* A further move scales the individual regularity to institutions: maxmin-style conservative-prior rules (precautionary defaults in environmental and biosecurity policy) are read as *codified* ambiguity aversion, so the analyst predicts that decision procedures built to be robust against the worst-case prior will reproduce the known-over-unknown tilt at the organizational level, and designs or critiques such rules by asking whether the conservatism they impose is warranted or merely the institutional shadow of the bias.

knowledge_transfer:
Ambiguity aversion is itself the cognitive *primitive* that several named anomalies (the Ellsberg paradox among them) reduce to, and within the choice-under-uncertainty domain it transfers cleanly *as mechanism*. The diagnostic (the both-colours preference for the known urn is incompatible with any single prior, so the agent is responding to the *precision of the probability information itself*), the family-membership test (does the effect survive equalising probability precision?), and the repair (enrich the representation of beliefs from a single prior to a *set* of priors, scored by maxmin expected utility or its smooth-ambiguity and Choquet variants) carry intact across the home domain's subfields. So the same regularity, with the same known-over-unknown tilt, explains equity home bias in **finance** (over-weighting assets whose return distributions feel familiar), the demand for explicit warranties and certified claims in **insurance markets**, the low uptake of novel therapies with imprecise side-effect profiles in **clinical decision-making**, and precautionary, maxmin-style conservative-prior rules in **environmental and biosecurity policy** — the last read as ambiguity aversion *codified* at the institutional level. These are not distinct substrates but one substrate restaged: cognitive (and institutional) choice under uncertain probabilities. The same mechanism, the same precision variable, the same set-of-priors repair, applied to different decision contexts.

Beyond that substrate the honest characterisation is that **ambiguity aversion is a property of cognition, bounded to agents whose beliefs distinguish "I know the probability" from "I don't" — and what travels further is the parent it instantiates, not the named regularity**. The mechanism presupposes a believing, evaluating agent with a precision-sensitive preference asymmetry; it has no foothold in physical, biological, or computational systems that lack belief-states. A thermostat, a population under selection, or a market-clearing equation does not "prefer the known urn," so the regularity does not recur there as mechanism — and that is the boundary to mark, not a metaphor to extend. What *does* generalise upward is the broader pattern ambiguity aversion is one instance of: *systematic deviation from a normative benchmark*, and more specifically a *preference asymmetry*, both of which are carried by the cognitive-`bias` family. When the cross-domain lesson is needed for some other agent or institution, it should be carried by that parent (the general fact that intuitive choice departs from the normative model in patterned ways), with ambiguity aversion as the specific known-over-unknown member; one level down, for any genuinely risky-choice setting, the transferable substance is the set-of-priors / probability-imprecision construct itself, housed alongside `expected_utility_theory`. The home-bound cargo that stays behind is the named regularity's specific apparatus: the Ellsberg two-urn stimulus, the sure-thing-principle violation, the risk-versus-ambiguity distinction as Knightian uncertainty, and the maxmin-and-Choquet repair literature — the machinery by which the primitive was demonstrated and formalised in economics. So the honest move is to invoke the cognitive-bias parent (or, for risky choice, the imprecise-probability construct) when reasoning across agents, and to treat any application of "ambiguity aversion" to a non-cognitive substrate as analogy that has borrowed the known-over-unknown shape while dropping the believing agent the mechanism requires (see *Structural Core vs. Domain Accent*).


Anagnorisis

slug: anagnorisis

one_liner: Aristotle's moment of dramatic recognition — a character's discrete move from ignorance to knowledge of a load-bearing fact about identity or agency that retroactively reorganizes the meaning of every prior scene rather than adding a new event.

origin_domain: literature

origin_subdomain: poetics

core_idea: Anagnorisis (Aristotle, *Poetics*) is the moment of recognition — the discrete point at which a dramatic character moves from ignorance to knowledge about a load-bearing fact, typically concerning identity, kinship, or one's own prior actions — and that recognition retroactively reorganizes the meaning of the entire preceding narrative. The structural claim is that a single knowledge update changes not only the character's current situation but the interpretation of every prior event: Oedipus has been the murderer all along, and his every confident step toward solving the case was a step toward self-indictment; the recognition does not produce new events but renarrates the ones that have already happened. Aristotle in the *Poetics* pairs anagnorisis with *peripeteia* (reversal of fortune) and argues that the best tragic plots combine them so that the reversal is caused by the recognition — the king becomes the exile in the same moment the investigator becomes the culprit. Three structural elements are jointly required: a *pre-recognition state* in which a determinate but hidden truth has been shaping events without being named; a *recognition event* typically catalyzed by a revealing token (a scar, a witness, a letter, an artifact) that makes the hidden truth legible; and a *retrospective reorganization* in which every prior scene acquires new meaning under the newly known identity. The *audience pairing* is the dramatic-irony structure that frequently accompanies anagnorisis in tragedy: the audience knows (from the prologue, from legend, from the play's architecture) what the protagonist does not, so the protagonist's ignorance and every speech it generates are doubly heard — as the character's honest meaning and as the audience's ironic reinterpretation — until recognition collapses the two levels into one. Aristotle classifies recognitions by their triggering mechanism (by signs, by memory, by inference, by false inference) and treats recognition-caused-reversal as the summit of dramatic craft.

scope_of_application:
Anagnorisis lives within drama and narrative theory, wherever a plot turns on a hidden truth about identity, kinship, or agency brought to legibility; its reach is bounded by that narrative substrate, while the retroactive-update core that recurs in diagnosis, investigation, and learning is carried by `retrodiction` and Gestalt `insight`, not by the dramaturgical apparatus.

- **Greek tragedy** — the canonical home, Sophocles' *Oedipus Tyrannus* and Euripides' recognition plays, where recognition coupled to peripeteia is the summit of tragic craft.
- **Shakespearean drama and the romances** — recognition scenes and reunions (the late romances especially) in which a disclosed identity reorganizes the whole prior action.
- **Greek romance** — the prose tradition of lost-and-found kin reunited by tokens, the trigger-by-sign convention in its purest narrative form.
- **Modern detective fiction** — the unmasking, which explicitly leans on the convention: the perpetrator's recognition re-reads all the prior evidence under the newly known identity.

structural_signature:
**Sig role-phrases:**

- **the hidden truth** — a determinate but unrecognized fact about identity, kinship, or one's own agency that has been shaping events all along
- **the pre-recognition state** — the protagonist's (and often the audience's) prior misreading of the situation, under which the setup is encountered
- **the trigger token** — the revealing object, testimony, or encounter (a scar, a letter, a witness) whose narrative job is to make the truth legible
- **the recognition event** — the discrete moment of update, the move from ignorance to knowledge of the load-bearing fact
- **the retrospective reorganization** — the new interpretation propagating back through every prior scene, renarrating rather than adding events, so the setup means anew
- **the coupled reversal (peripeteia)** — the change in fortune or moral status caused by the recognition, the summit being recognition and reversal landing as one stroke
- **the audience pairing** — the dramatic-irony gap by which the audience knows before the protagonist, so pre-recognition speeches are doubly heard until recognition collapses the two levels
- **the retrospective-coherence test** — the criterion separating a true anagnorisis (the prior narrative reorganizes coherently) from a cheap surprise (a fact merely appended)

what_it_is_not:
- **Not a surprise.** A surprise delivers a fact the prior narrative did not anticipate; an anagnorisis delivers a fact the narrative was *already organized around* without naming it, so the disclosure renarrates the scenes already shown rather than appending an event. A twist that fails the retrospective-coherence test — that has no purchase on what came before — is a cheap surprise wearing recognition's costume, not an anagnorisis.
- **Not the reversal.** Recognition (anagnorisis) and reversal of fortune (peripeteia) are separately manipulable parts: a character can change fortune without learning anything, or learn the truth with no change in fortune. Conflating them loses Aristotle's summit — the plot in which the recognition *causes* the reversal, the investigator becoming the culprit in one stroke — which is a coupling, not an identity.
- **Not any knowledge update.** Its load-bearing cases concern identity, kinship, and one's own prior agency — it re-inscribes *who the character is*, not any incremental narrowing of a hypothesis space. The substrate-general residue (a single update that retroactively reinterprets a prior trajectory) is carried by `retrodiction` and Gestalt `insight`; a medical "aha, it's lupus" is at best a partial instance of that parent, lacking the moral-and-identity stakes that make a recognition an anagnorisis.
- **Not the production of new events.** The recognition adds nothing to the plot's sequence; it rewrites the meaning of events already shown, so the protagonist's earlier speeches retroactively carry meanings they could not have intended. Reading it as a fresh plot beat misses that its whole work is reinterpretation, not addition.
- **Not dependent on surprising the audience.** The dramatic-irony pairing typically has the audience knowing the hidden truth *before* the protagonist (from prologue or legend), so anagnorisis is the moment the character's ignorance collapses, not the audience's. The astonishment, where it operates, is the protagonist's; the audience's experience is the ironic double-hearing that recognition finally resolves.

clarity:
Naming anagnorisis separates a transformative *recognition* from a mere late-arriving *surprise*, and that distinction does the central diagnostic work in plot analysis. A surprise delivers a fact the prior narrative did not anticipate; an anagnorisis delivers a fact the prior narrative was *already organized around* without naming it, so that the disclosure does not add an event but renarrates the ones already shown. This is the criterion that lets a critic say why some endings feel structurally necessary and others feel cheap: a recognition earns its place when the preceding scenes have been arranged to become reinterpretable under it — when the foreshadowing load was carried all along — and fails when the revelation has no purchase on what came before. The reader's question shifts from "was the twist unexpected?" to "does the prior material reorganize coherently once the truth is known?", which is the test of craft rather than of mere astonishment.

Equally, pairing anagnorisis with peripeteia makes Aristotle's distinction between *recognition* and *reversal* available as separate, manipulable parts. A character can change fortune without learning anything, or learn the truth without any change in fortune; the summit Aristotle identifies is the plot in which the recognition *causes* the reversal, so that the investigator becomes the culprit in the very moment of knowing. Holding the two apart lets a dramatist or critic ask precisely how they are coupled in a given work, and Aristotle's typology of triggers — recognition by sign, by memory, by inference, by false inference — gives a further axis: not just whether a recognition occurs, but by what mechanism the hidden truth is made legible, and whether that mechanism is earned or contrived. The trigger token (the scar, the witness, the letter) thereby becomes a designed object whose narrative job is to enable the turn, not a coincidence — a thing the analyst can locate and judge.

manages_complexity: A plot built around a late disclosure is, taken whole, a tangle: dozens of scenes, a hidden truth, a moment of revealing, an audience whose knowledge may or may not match the protagonist's, a change of fortune that may or may not be tied to the revealing — and over the whole tragic and dramatic corpus the recognition scenes differ in trigger, in placement, in stakes, in whether they land or fall flat, with no obvious common handle. Anagnorisis reduces that tangle to a small set of design variables an analyst can hold at once and read the plot's architecture from. The first is *where* the recognition sits and *by what trigger* it is catalyzed — Aristotle's typology closes the trigger question to a short list (by sign, by memory, by inference, by false inference), so instead of treating each revealing token as a one-off the critic classifies it and judges whether that mechanism is earned or contrived. The second is the *retrospective-coherence* test: does the prior narrative reorganize coherently once the hidden truth is named, or does the disclosure merely append a fact with no purchase on what came before? This single binary separates a structurally necessary recognition from a cheap surprise, and it predicts the foreshadowing structure — a well-made anagnorisis entails that earlier scenes carry reinterpretable signals, so the analyst can go looking for them and grade how the load was carried. The third is the *coupling to peripeteia*: holding recognition and reversal apart as separate parts lets the analyst read off which of three regimes a plot occupies — reversal without recognition, recognition without reversal, or the Aristotelian summit where the recognition *causes* the reversal in one stroke. The fourth is the *audience-pairing*: whether the dramatic-irony gap between audience knowledge and protagonist knowledge is open (amplifying every pre-recognition speech with a second, ironic hearing) or closed. From these four coordinates — placement-and-trigger, retrospective coherence, recognition-reversal coupling, audience gap — the qualitative facts about a plot's recognition machinery follow: whether the ending is earned, where its preparation lives, how its reversal is driven, and how its irony is pitched. The analyst stops re-deriving the effect of each revelation scene from the full text and instead reads it off a handful of structural parameters with a clean branch on the coherence test (earned versus cheap) and on the coupling (which of the three reversal regimes).

abstract_reasoning:
Anagnorisis licenses a set of plot-analytic moves that turn a vague intuition about a late disclosure into determinate judgments, all running off four coordinates: the recognition's placement-and-trigger, the retrospective-coherence test, the coupling to peripeteia, and the audience-knowledge gap.

*Diagnostic — classify the trigger, judge whether the recognition is earned, and locate its preparation.* The primary move reads a recognition scene and sorts its trigger by Aristotle's closed typology — by sign (a scar, a letter, an artifact), by memory, by inference, or by false inference — and from that classification judges whether the mechanism is earned or contrived rather than treating each revealing token as a one-off. The decisive diagnostic is the retrospective-coherence test: the analyst names the hidden truth and asks whether the prior narrative reorganizes coherently under it. If every earlier scene acquires new meaning — if Oedipus's confident steps toward solving the case re-read as steps toward self-indictment — the recognition is diagnosed as a genuine anagnorisis; if the disclosure merely appends a fact with no purchase on what came before, it is diagnosed as a cheap surprise wearing recognition's costume. Because a well-made anagnorisis *entails* that earlier scenes carry reinterpretable signals, the test doubles as a search instruction: the critic goes looking for the foreshadowing load in the pre-recognition material and grades how it was carried. The inference runs both ways — from a structurally necessary-feeling ending to the buried preparation that must exist, and from absent preparation to the verdict that the twist is unearned.

*Interventionist — set the four coordinates and predict the dramatic effect.* For the maker, each coordinate is a lever with a forecastable consequence. Couple the recognition to the reversal so that knowing *causes* the change of fortune, and the prediction is the Aristotelian summit: the investigator becomes the culprit in a single stroke, the recognition and the peripeteia landing as one event rather than two. Plant a trigger token early and let it lie inert until the recognition scene, and the prediction is that the token reads as a designed object enabling the turn rather than as a coincidence rescuing the plot. Open the audience-knowledge gap — let the audience know from prologue or legend what the protagonist does not — and the prediction is that every pre-recognition speech is doubly heard, as the character's honest meaning and as the audience's ironic reinterpretation, amplifying the scene until recognition collapses the two levels into one. Strengthen the foreshadowing load on the prior scenes and the prediction is that the eventual recognition will feel necessary rather than arbitrary, because the retrospective reorganization will have purchase. Each move is a claim about how the recognition will land, checkable against whether the prior material in fact reorganizes coherently under the disclosed truth.

*Boundary-drawing — separate recognition from surprise, and recognition from reversal.* The construct's central discipline is two cuts. First, between a transformative *recognition* and a mere late-arriving *surprise*: a surprise delivers a fact the narrative did not anticipate, while an anagnorisis delivers a fact the narrative was already organized around without naming, so the disclosure renarrates rather than adds — and the move includes refusing the label to any twist that fails the retrospective-coherence test. Second, between *recognition* and *reversal*, held apart as separately manipulable parts: a character can change fortune without learning anything (reversal without recognition) or learn the truth with no change in fortune (recognition without reversal), so the analyst must specify which of the three regimes a plot occupies rather than conflating the two. The apparatus is also content-bound: its load-bearing cases concern identity, kinship, and one's own prior agency, so the recognition it names is the one that re-inscribes who the character is, not any incremental knowledge update.

*Predictive (order-of-events) — a single update renarrates the entire prior trajectory.* Anagnorisis asserts a definite temporal structure: a determinate but hidden truth shapes events before it is named, a discrete recognition event makes it legible, and the meaning of every prior scene is then rewritten under the newly known identity — the recognition produces no new events, only a re-reading of the ones already shown. From this the analyst predicts that the protagonist's pre-recognition speeches will, in retrospect, carry meanings they could not have intended, that the play's preparation lives in scenes whose significance was withheld, and that in the coupled case the reversal will arrive at the exact instant of knowing. Knowing only that a genuine anagnorisis fires at some point, the critic predicts the whole architecture: a setup secretly organized around the hidden fact, a triggering token, and a close whose work is to make everything before it mean anew.

knowledge_transfer:
Within drama and narrative theory anagnorisis transfers *as mechanism*. The trigger typology (by sign, by memory, by inference, by false inference), the retrospective-coherence test, the recognition-reversal coupling, and the audience-pairing all carry intact across the corpus the concept was built on — Sophocles, Euripides, Shakespeare's recognition scenes and romances, Greek romance, and modern detective fiction's unmasking, which explicitly leans on the convention. A critic trained on Oedipus reads any recognition scene the same way: name the hidden truth, test whether the prior narrative reorganizes coherently under it, classify the trigger, and locate the coupling to reversal. The diagnostics transfer without translation because the substrate is one: a plot in which a hidden truth about identity, kinship, or agency has been shaping events and is brought to legibility.

Beyond narrative the case is **(B): a more general mechanism recurs across domains, while the dramaturgical machinery stays home.** The substrate-independent residue is *a single knowledge update that retroactively reinterprets a prior trajectory*, and that pattern is carried by the parents `retrodiction` and Bayesian update (using new evidence to re-explain prior data) and, for the "now I see what it all meant" version, by Gestalt `insight` and `paradigm_shift`. Those parents genuinely co-instantiate where the source candidate points: the differential-diagnosis "aha, it's lupus" really is a retroactive reinterpretation that re-explains a decade of disparate symptoms; the detective's recognition of the perpetrator really does re-read the prior evidence; the learner's sudden grasp of what the textbook was driving at reorganizes earlier material. So these transfers are *real but shallow* — they carry the retroactive-update core (B) while dropping everything that makes anagnorisis a narrative-structural device: the *moral and identity stakes* (it is who the character *is* that is re-inscribed), the *trigger-token convention*, the *peripeteia coupling*, and the *audience dramatic-irony pairing*. Because those load-bearing parts fall away, calling a medical diagnosis or an investigative breakthrough an "anagnorisis" is at best a partial instance of the retrodiction parent and at the metaphorical edge **(A)** when it imports the dramatic charge the case lacks. The honest move is to carry `retrodiction` / `insight` for the retroactive-reinterpretation lesson, and to reserve "anagnorisis" — with its trigger typology and recognition-causes-reversal summit — for narrative, where its dramaturgical apparatus does work the bare parents cannot. (The term also anchors a literary-studies cluster with peripeteia, hamartia, catharsis, and mimesis; that is a domain-specific family, not a sign of cross-substrate reach — see *Structural Core vs. Domain Accent*.)


Analytic Memo

one_liner: Externalise interpretive reasoning in writing during analysis — dated, typed, indexed memos sitting between raw evidence and finished claims — so the analysis becomes generative, auditable, and revisable.

core_idea: An analytic memo is a written intermediate artifact in which a qualitative researcher records emerging interpretations, candidate categories, relationships among codes, unresolved questions, and the reasoning behind analytic decisions during ongoing data analysis. It occupies the space between raw evidence — interview transcripts, field notes, observational records — and finished theoretical claims, and the grounded-theory tradition (Glaser and Strauss 1967; Strauss and Corbin 1990; Charmaz 2006) treats it as generative rather than merely documentary: the act of writing the memo is itself the analytic move in which structure is discovered, not just transcribed. A code-focused memo written in week three becomes input to a category-relationship memo in week five, which feeds the integrative memos that eventually become the theoretical statement. The corpus of memos, dated and indexed, constitutes the researcher's working theory and provides an audit trail that an independent reviewer can in principle walk backward from any final claim to the specific transcript segments and the reasoning steps that produced it. The key structural commitment is that analytic reasoning *must be externalised in writing during analysis* rather than reconstructed after the fact: an interpretive process leaving no intermediate written record cannot be audited, and its conclusions cannot be assessed for grounding in the data, revised transparently, or transmitted intact to collaborators or successors. Methodological-memo types in grounded theory are typically distinguished by scope and function: code memos elaborate a single code; theoretical memos develop emerging categories and their relationships; operational memos record procedural decisions; integrative memos attempt synthesis across the emerging category structure.

scope_of_application:
The analytic memo lives across the interpretive subfields of qualitative research methodology, with the grounded-theory tradition as its home; its reach as a *named method* is bounded to that domain, while the externalised-intermediate-cognition pattern it instantiates recurs as sibling practices (lab notebooks, ADRs) under the `documentation` / audit-trail parent rather than as exports of this entry's content.

- **Grounded theory** — the canonical home, where the memo typology (code / theoretical / operational / integrative) and the memo-to-theory progression make the writing the analytic move in which categories are discovered.
- **Ethnography** — where memos sit alongside field notes to externalise the fieldworker's emerging interpretation and keep it auditable.
- **Phenomenology** — recording the reduction and the analyst's evolving reading of lived-experience accounts as an intermediate, revisable trace.
- **Narrative inquiry** — capturing candidate plot structures and thematic relations across collected stories before the final account.
- **Action research** — logging the reasoning behind iterative intervention-and-reflection cycles so decisions can be revisited and shared.
- **CAQDAS-supported coding practice** — NVivo, ATLAS.ti, and Dedoose ship explicit memo features that operationalise the dated, indexed memo corpus across all of the above.

structural_signature:
**Sig role-phrases:**

- **the researcher** — the inquirer doing interpretive work over time (coding transcripts, field notes, documents)
- **the raw evidence** — the data the memo sits above: transcripts, observations, documents
- **the memo** — a dated, authored, written record of *intermediate* interpretation (candidate category, emerging relationship, open question, decision rationale), positioned between raw evidence and the final claim
- **the memo typology** — the functional kinds the corpus sorts into by scope: code memo (one code), theoretical memo (a category and its relations), operational memo (a procedural decision), integrative memo (synthesis across the structure)
- **the corpus of memos** — the dated, indexed accumulation that *is* the working theory in progress, not a record of it
- **the generative function** — the load-bearing commitment: writing the memo is the analytic move in which structure is *discovered*, not transcribed afterward
- **the audit trail** — the guarantee that follows: a reviewer can walk backward from any published claim, through the dated memos, to the prompting transcript segments
- **the externalization boundary** — the deliberate limit: an interpretive process leaving no contemporaneous written trace falls outside what can be audited, revised transparently, or transmitted intact (distinct from the *definitional* codebook and from a post-hoc reconstruction)

what_it_is_not:
- **Not a codebook.** The codebook is the *definitional* artifact — "this code means this"; the memo is the *interpretive* one — "here is what I think is happening, and what I am unsure of." Conflating them hides exactly the reasoning the method needs externalised, folding the analytic move into a glossary entry that records a decision without the thinking that produced it.
- **Not mere documentation or record-keeping.** Treated as overhead, memo-writing looks like paperwork to minimise. The grounded-theory commitment is that the writing is *generative* — the memo is the place where a category is *discovered*, not transcribed after the fact — so skipping or deferring it does not merely lose documentation, it skips the analytic move itself. The practitioner's question is "have I written my way to it yet?", not "have I written down what I found?"
- **Not the raw data, and not the final claim.** The memo is the *intermediate* term, sitting between the transcript or field note and the finished theoretical statement. Collapsing all three into "my analysis" is what makes a chain of interpretation un-auditable; keeping the middle term visible is what lets a reviewer walk backward from a published claim to the evidence that prompted each step.
- **Not a post-hoc reconstruction.** The structural commitment is that reasoning be externalised *during* analysis, at the moment of the analytic move — not narrated afterward from the raw data. An interpretive process that leaves no contemporaneous written trace falls outside what the method can audit; a category with no dated memo marking its emergence is a sign the move was reconstructed rather than recorded.
- **Not the same as its sibling artifacts.** Architecture Decision Records, lab notebooks, reviewer memos, and retrospective notes share the dated-externalised-revisable *shape*, but they carry none of the grounded-theory machinery — no theoretical-sampling-by-memo, no constant-comparison forms, no saturation criteria, no memo-to-theory progression. They are co-instances of the parent pattern (externalised intermediate cognition), not exports of analytic-memo content; calling an ADR "an analytic memo" over-reads a shared shape as a shared method.

clarity:
Naming the analytic memo pulls apart three artifacts that qualitative practice routinely collapses into "my analysis": the *raw data* (the transcript, the field note), the *intermediate reasoning* (what the coder is noticing, the candidate category, the still-open question), and the *final claim* (the paper, the theoretical statement). Keeping the middle term visible is what makes a chain of interpretation auditable — a reviewer can walk backward from any published claim, through the dated memos that built it, to the specific transcript segments that prompted each step — and it is what exposes the failure mode the concept exists to forbid: an analysis that produces conclusions with no contemporaneous written trace, reconstructed after the fact and therefore impossible to check for grounding or to revise transparently. It also separates the memo from its neighbor the codebook: the codebook is *definitional* (this code means this), the memo is *interpretive* (here is what I think is happening and what I am unsure of), and conflating the two hides exactly the reasoning the method needs externalised.

The deeper clarity is a reframing of what the writing is *for*. Treated as mere record-keeping, memo-writing looks like overhead to be minimised; the grounded-theory commitment is that the writing is *generative* — the memo is the place where a category is discovered, not transcribed after the fact — so skipping or deferring it does not just lose documentation, it skips the analytic move itself. That reframing changes the practitioner's question from "have I written down what I found?" to "have I written my way to it yet?", and it makes the corpus of dated, indexed memos legible as the working theory in progress rather than a paperwork residue alongside the real work.

manages_complexity: A qualitative project is, materially, an overwhelming mass: hundreds of hours of interview transcripts, field notes, and documents, against which a researcher must build a theory that is grounded in all of it, traceable to specific evidence, and defensible to a skeptical reviewer. The naive alternatives both fail under that load. Holding the emerging interpretation in one's head leaves it un-auditable, lost the moment the analyst leaves the project, and impossible for a collaborator to enter. Reconstructing the analysis after the fact, from the raw data, irrecoverably loses the contemporaneous reasoning state — the why-this-category-here that the finished claim depends on but the transcript does not contain. The analytic memo tames this by externalising the interpretive process into a second corpus that is itself navigable: dated, authored, indexed memos that sit between the raw evidence and the final claim and *are* the working theory in progress. The compression has a definite shape. The sprawl of an unbounded interpretive process collapses to a small set of tracked artifacts whose type tells the analyst what each is doing — a code memo elaborating one code, a theoretical memo developing a category and its relations, an operational memo logging a procedural decision, an integrative memo synthesizing across the category structure — so that "where is my reasoning about X?" is answered by scope and date rather than by re-reading the data. And it converts the project's central anxiety, *is this conclusion actually grounded?*, into a single mechanical operation an outside reviewer can perform: walk backward from any published claim, through the dated memos that built it, to the specific transcript segments that prompted each step. That backward-traceability is the parameter the method makes everything turn on; its presence or absence reads off directly whether a finding can be audited, revised transparently, or transmitted intact. The reframing that the writing is *generative* — that the memo is where the category is discovered, not merely recorded — is what makes the audit trail honest rather than a post-hoc gloss, because the trace is laid down at the moment of the analytic move, not narrated afterward. So the researcher does not have to keep the whole theory live in memory or hope to recover it later; they track a growing, indexed set of typed memos and read both the state of the theory and its grounding off that corpus. An interpretive process of essentially unbounded dimension becomes a finite, navigable, backward-walkable artifact set.

abstract_reasoning:
The analytic memo licenses a distinctive set of moves in qualitative inquiry, all flowing from the commitment that interpretive reasoning must be laid down in writing *at the moment of analysis* and that the resulting corpus is the working theory rather than a record of it. The signature *interventionist* move is generative and runs counter to a record-keeping intuition: facing a cluster of passages that resist the existing codes, the researcher does not first decide what the category is and then write it down — they *write in order to find it*, articulating in prose what seems to be happening across interviews 4 and 12, and the act of writing is what surfaces a new category ("boundary-defence failure") that the silent reading had left implicit. The predicted effect is concrete and testable against the corpus: a category that emerged through a memo will have a dated memo marking its first appearance and the evidence that prompted it, so a category with no such memo is a sign that the analytic move was skipped or reconstructed after the fact. The reasoning is therefore "write the memo → discover the structure," with the absence of the memo predicting the absence of grounded discovery.

The *diagnostic* move runs backward along the same trace and is the one an outside reviewer performs. Confronted with a finished claim, the auditor reasons from the published statement, through the dated memos that built it, to the specific transcript segments that prompted each step — and the recoverability or non-recoverability of that path is itself the verdict. A claim that can be walked back to its evidence is grounded; a claim whose backward path dead-ends at a memo gap is, by the method's own commitment, un-auditable and its grounding unassessable. The memo *type* sharpens the diagnosis: asking "where is my reasoning about X?" is answered by scope and date rather than by re-reading the data, because a code memo elaborates one code, a theoretical memo develops a category and its relations, an operational memo logs a procedural choice, and an integrative memo synthesizes across the structure — so the analyst infers from the kind of question what kind of memo should hold the answer and where in the dated sequence to look.

The *boundary-drawing* move fixes what counts as a memo and when externalization is obligatory, which is what keeps the practice from collapsing into either raw data or finished prose. The analyst separates the *definitional* artifact (the codebook: this code means this) from the *interpretive* one (the memo: here is what I think is happening and what I am unsure of), and refuses to let a procedural log or a polished report stand in for the contemporaneous reasoning the method requires — because each substitution hides exactly the analytic step that needs to be visible. The governing regime rule is sharp: an interpretive process that leaves no intermediate written trace falls outside the method's auditability entirely, so the requirement to externalize is not advice about thoroughness but the boundary of what can be checked, revised transparently, or transmitted intact to a collaborator or successor. Finally, an *order-of-events* inference structures the whole: a code memo in week three feeds a category-relationship memo in week five which feeds the integrative memos that become the theoretical statement, so the analyst can read the maturity of the working theory off where in that progression the memo corpus currently sits, and can predict that an integrative synthesis attempted before the underlying code and theoretical memos exist will lack the substrate it needs to be grounded.

knowledge_transfer:
Within its home — qualitative research methodology — the analytic memo transfers as a full practice, machinery included, across grounded theory, ethnography, phenomenology, narrative inquiry, and action research, with coding software (NVivo, ATLAS.ti, Dedoose) providing explicit memo features. What carries is not just the idea of writing-during-analysis but the domain-specific apparatus: the memo *typology* (code, theoretical, operational, integrative memos, sorted by scope and function), the *progression* (code memo in week three feeding a category-relationship memo in week five feeding the integrative memos that become the theoretical statement), the generative commitment (the memo is where a category is *discovered*, not transcribed), the backward-traceable audit trail (walk from any published claim through dated memos to the prompting transcript segments), and the saturation-and-constant-comparison criteria that the memo corpus instruments. Across these subfields the vocabulary and the moves are stable, and "where is my reasoning about X?" is answered by memo type and date rather than by re-reading the data. That is genuine within-domain transfer as mechanism.

Beyond qualitative methodology the transfer is real but routes through a *shared abstract parent*, not through the memo's own machinery — and the seed is explicit about the distinction. The portable structure is *externalised intermediate cognition during inquiry*: a dated, authored, navigable corpus of contemporaneous reasoning, written at the moment of the analytic or design move, that confers auditability, generativity, and revisability. That parent genuinely recurs as co-instances across professions — Architecture Decision Records and design-rationale documents in software and engineering, lab notebooks and bench books in experimental science, reviewer and clerks' bench memos in law, working-paper drafts in policy, agile retrospective notes — each independently a place where an inquirer writes reasoning down while doing the work rather than reconstructing it after. But these are *sibling practices*, not exports of analytic-memo content: an ADR shares the dated-externalised-revisable shape while carrying none of the grounded-theory furniture (no theoretical-sampling-by-memo, no constant-comparison memo forms, no saturation criteria, no Glaser-Strauss-Charmaz progression). So the honest cross-domain statement is that the lesson — externalise intermediate reasoning at the time of inquiry, and your conclusions become auditable, your structure discoverable, your revisions transparent — should be carried by the parent pattern (externalised cognition / `documentation` / audit-trail), under which the analytic memo and the lab notebook and the ADR all sit as cousins. The cross-domain reach belongs to that parent; "analytic memo," as named, carries qualitative-research-specific cargo that does not and need not travel.

The boundary to mark is therefore one of *level*, not of metaphor-versus-mechanism: calling an Architecture Decision Record "an analytic memo," or importing grounded theory's memo-to-theory progression into a lab notebook, over-reads a shared shape as a shared method — the externalisation function transfers, the methodological machinery does not. Stated plainly: within qualitative inquiry the named practice transfers as a complete method; one level up, the externalised-intermediate-cognition pattern it instantiates recurs literally across science, engineering, law, and policy and owns the cross-domain lesson; and treating the sibling artifacts as the same thing as the analytic memo conflates co-instances of a parent with transfer of the entry's own content (see *Structural Core vs. Domain Accent*).


Annotation Drift

one_liner: The gradual, undocumented shift over time in how annotators apply an unchanged rubric, so identical instances get different labels — a silent recalibration of a measurement instrument, invisible to within-slice agreement and detectable only by re-annotating frozen gold.

core_idea:
Annotation drift is the gradual, undocumented change over time in how human annotators apply a labeling rubric, with the result that nominally identical instances at time *t* and time *t + Δ* receive different labels — not because the underlying phenomenon changed, not because the rubric was formally revised, but because the annotators' shared interpretive practice silently shifted. The drift accumulates through onboarding of annotators with different priors, case-law-style internal precedents that accumulate outside the rubric document, ambient context changes that make previously borderline cases seem obvious, and feedback from downstream model errors that reshapes what the team counts as a hard case.

The structurally hazardous feature is that the drift is invisible to the standard quality-assurance instruments: inter-annotator agreement computed within a time slice can remain high while the entire cohort drifts together, so the internal consistency metric that would normally diagnose disagreement gives no signal. The rubric document is unchanged; the annotators are confident they are following it; the QA metrics are clean. The drift surfaces only by re-annotating a frozen set of gold-standard instances across different time cohorts and comparing the labels — a measurement that is rarely performed in practice. The consequence for machine learning pipelines is that the training target, the validation set, and the in-production evaluation may be measuring three different things along an undocumented axis: the model's historical performance record is not comparable to its current performance record because the instrument has moved between them. This makes annotation drift a calibration problem for a non-stationary measurement instrument, distinguishable from concept drift (the world changed) and from simple annotation error (noise around a stable instrument) by its time-varying, cohort-level, within-rubric character.

scope_of_application:
Annotation drift lives across the labeling and evaluation subfields of ML and data science — wherever a longitudinal label stream is produced by a human-applied rubric whose interpretive calibration can silently slide while the document stays fixed; its reach is within that one substrate sampled across many ML tasks. The cross-substrate analogues already carry community names of their own (coder/rater drift in survey methodology, diagnostic drift in medicine, sentencing drift in law), and belong to the parent `instrument_interpretive_drift`, not to "annotation drift" as named.

- **Clinical-prediction model training** — chart abstractors applying ICD codes and outcome definitions whose conventions slide over years (e.g. as long-COVID gains prominence), so superficially-similar charts diverge in labeling.
- **Content-moderation labeling** — policy interpreters applying hate-speech, harassment, or misinformation labels, where the same post is labeled differently across years even when the policy text is unchanged.
- **Search-relevance rating** — human raters scoring query-result pairs drifting toward newer notions of a "good" result as ranking quality itself improves.
- **Crowdsourced computer-vision labeling** — definitions of "obstructed object" or "pedestrian" sliding with new guidelines, new annotator pools, and accumulated edge-case decisions.
- **Sentiment / toxicity labeling** — shifting cultural baselines changing what counts as toxic without the rubric being formally revised.

structural_signature:
**Sig role-phrases:**

- **the labeling rubric** — the stated rule, formally stable and unchanged over the period in question
- **the annotator cohort** — the population of humans who apply the rubric, confident at each moment they are following it
- **the interpretive practice** — the unwritten how-we-actually-label that silently shifts via new-annotator priors, case-law-style internal precedents, ambient context, and downstream-error feedback
- **the longitudinal label stream** — a time series of labels produced by an instrument that re-calibrates while in use, so nominally identical instances at *t* and *t+Δ* receive different labels
- **the blind within-slice agreement** — inter-annotator agreement within a single time slice staying high while the whole cohort drifts together, so clean QA dashboards certify nothing about a stable target
- **the three boundary conditions** — time-varying (not a constant offset, which is bias), cohort-level (not per-instance scatter, which is annotation error), within-rubric (the document unchanged, not a formal revision)
- **the frozen-gold diagnostic** — the only valid test: re-annotate a frozen set of gold instances across time cohorts and compare labels, holding the instances fixed so the instrument's movement shows
- **the bake-in failure** — retraining on recent data fitting the model to a moved target, embedding the artifact rather than removing it, when the cause is drift
- **the instrument-stabilizing intervention** — periodic re-rating of held-out gold, cohort-overlap windows, calibration-drift dashboards, frozen-rubric audit cycles, adjudication-precedent versioning

what_it_is_not:
- **Not concept drift.** Concept drift is the *world* the model tracks changing; annotation drift is the *labeling instrument* changing while the world may not. The two look identical on a falling validation curve but demand opposite responses — and retraining on recent data, the reflex for concept drift, *bakes the artifact in* when the cause is annotation drift.
- **Not annotation error or noise.** Ordinary annotation error is per-instance scatter around a *stable* rubric; annotation drift is a *cohort-level, time-varying* movement of the rubric's interpretive calibration. Noise averages out across the cohort; drift moves the whole cohort together.
- **Not bias.** Bias is a systematic *constant* offset; drift is a *time-varying* offset. A fixed mislabeling tendency is not annotation drift — the defining feature is that the offset changes across time cohorts while the rubric text stays put.
- **Not selection bias.** Selection bias concerns which instances *enter* the sample; annotation drift concerns how identical instances are *labeled* across time. The instances can be drawn identically and still receive divergent labels as the interpretive practice slides.
- **Not a formal rubric revision.** The hazard is *within-rubric*: the document is unchanged and the annotators are confident they follow it. A documented rubric rewrite is a visible, datable event; annotation drift is the silent slide of practice underneath an unchanged specification.
- **Not certified absent by clean QA dashboards.** Inter-annotator agreement within a single time slice can stay high while the entire cohort drifts together, so consensus is preserved as the shared practice moves. Only re-annotating a *frozen set of gold instances across time cohorts* — holding the instances fixed so the instrument's movement shows — can detect it; within-slice agreement is structurally blind to coordinated drift.

clarity:
Naming annotation drift separates two things that look identical on a falling validation curve: real *concept drift* in the world the model tracks, and *measurement drift* in the instrument that labels it. A team that lacks the distinction reads a performance drop as a signal about the world or the model and responds by retraining on recent data — which, if the cause is a moving labeling instrument, bakes the artifact in rather than removing it. The label forces a prior question, an instrumentation one: before asking "is the model worse?" ask "is our labeling rubric calibrated the same way across time?" That reframes model evaluation as a measurement problem with a possibly non-stationary instrument, where train-test splits and cross-validation silently assume a calibration that may not hold.

Its sharpest clarifying move is to explain why the usual quality-assurance instrument gives no warning. Inter-annotator agreement within a single time slice can stay high while the whole cohort drifts together — consensus is preserved even as the shared interpretive practice slides — so the very metric that diagnoses disagreement is blind to coordinated movement. Recognizing this tells the practitioner that clean QA dashboards do not certify a stable target, and points to the one measurement that can: re-annotating a frozen set of gold instances across time cohorts and comparing the labels. The name also fixes the boundaries that make the diagnosis precise — drift is time-varying (not a constant offset, which is bias), cohort-level (not per-instance noise around a stable rubric, which is annotation error), and within-rubric (the document is unchanged) — so a practitioner can ask the right discriminating question rather than misfiling the failure as ordinary noise or a changed world.

manages_complexity:
The phenomena annotation drift covers are an unruly list of labeling-pipeline pathologies, each with its own apparent cause: annotators onboarded with different priors, case-law-style internal precedents accruing outside the rubric document, ambient events that make once-borderline cases newly obvious, downstream model errors feeding back to reshape what counts as a hard case, quiet shifts in adjudication convention. Tracked individually, each is a separate operational worry, and on a falling validation curve they hide among an entirely different set of explanations — the world changed, the model decayed, the population shifted. The concept compresses all of it under one framing: the labeling rubric is a *measurement instrument whose calibration silently shifts while it is in use*. Once the rubric is seen as an instrument rather than a fixed rule, the open list of pathologies become so many ways one instrument can drift, and the analyst stops diagnosing each cause on its own terms and instead tracks a single quantity — the instrument's calibration across time cohorts.

That single quantity is what makes the difference readable. The diagnostic question that otherwise has no clean answer — is a performance change real concept drift in the world, or measurement drift in the labeling apparatus? — reduces to one measurement: re-annotate a frozen set of gold instances across time cohorts and compare the labels. Crucially, the concept also tells the analyst why the cheaper, routinely-collected signal is useless here: inter-annotator agreement within a time slice can stay high while the whole cohort drifts together, so clean QA dashboards certify nothing about a stable target. Three boundary conditions keep the read sharp and prevent misfiling — drift is time-varying (a constant offset would be bias), cohort-level (per-instance scatter around a stable rubric would be annotation error), and within-rubric (the document is unchanged) — so the analyst can place a given failure precisely rather than confuse it with noise or a changed world. And the framing fixes the intervention class without further case analysis: periodic re-rating of held-out gold, cohort-overlap windows, calibration-drift dashboards, frozen-rubric audit cycles, adjudication-precedent versioning. A scattered set of empirical failure stories and an ambiguous performance signal thereby collapse to one instrument-calibration parameter, from which the diagnosis, the boundary classification, and the remedy all follow.

abstract_reasoning:
Annotation drift licenses reasoning moves that all proceed from one reframing — the labeling rubric is a *measurement instrument whose interpretive calibration silently shifts while it is in use* — and treat model evaluation as a measurement problem with a possibly non-stationary instrument. The most distinctive is a *diagnostic discrimination* move on a falling validation curve, where two causes look identical: real *concept drift* in the world the model tracks, and *measurement drift* in the instrument that labels it. The analyst reasons that these demand opposite responses and forces a prior, instrumentation question before the modeling one — not "is the model worse?" but "is our labeling rubric calibrated the same way across time?" A signature inference here is about a failure mode of the naive response: if the cause is a moving labeling instrument, retraining on recent data is predicted to *bake the artifact in* rather than remove it, because it fits the model to a target that has shifted, so the analyst reasons that the standard remedy makes the problem worse precisely when the diagnosis is drift.

The most characteristic move explains why the routinely-collected quality signal is useless here, and it is a non-obvious inference. The analyst reasons that inter-annotator agreement *within a single time slice* can stay high while the whole cohort drifts together — consensus is preserved even as the shared interpretive practice slides — so the very metric that diagnoses disagreement is blind to coordinated movement. From this the analyst predicts that clean QA dashboards do not certify a stable target, and that the only measurement which can detect the drift is re-annotating a *frozen set of gold instances across time cohorts* and comparing the labels, because that is the only comparison that holds the instances fixed and lets the instrument's movement show. The reasoning explicitly distinguishes a cheap, always-available signal that is structurally uninformative from an expensive, rarely-performed one that is the only valid test.

A *boundary-drawing* move fixes three conditions that make the diagnosis precise and prevent misfiling, each separating drift from a look-alike with a different remedy. Drift is *time-varying* (a constant offset would be bias, not drift); *cohort-level* (per-instance scatter around a stable rubric would be annotation error, ordinary noise); and *within-rubric* (the document is unchanged, so a formal rubric revision is a different thing). Reasoning from these, the analyst asks the right discriminating question — is the anomaly a moving offset, shared across the cohort, with the rubric text untouched? — and places the failure precisely rather than confusing it with noise or a changed world. The same move borrows the conceptual scaffolding of measurement theory: the analyst separates true score, score variance, and *instrument* variance, and reasons that the standard inferential machinery — train-test split, cross-validation, A/B tests — silently assumes the labeling instrument is calibrated identically across time, an assumption that drift violates and that, once named, can be tested and corrected for.

The *interventionist* move reasons forward from the instrument-calibration framing to a fixed family of measures, each acting to detect or stabilize the instrument rather than the model: periodic re-rating of held-out gold instances (to measure calibration across cohorts), annotator cohort-overlap windows (to bound how fast the practice can slide between cohorts), calibration-drift dashboards, frozen-rubric audit cycles, and adjudication-precedent versioning (to surface the case-law-style precedents accruing outside the rubric document). Each is reasoned as an instrument-effect adjustment, and the analyst predicts that without them the training target, the validation set, and the in-production evaluation may be measuring three different things along an undocumented axis, making the model's historical and current performance records non-comparable because the instrument moved between them. The recurring habit the concept installs is to ask of any longitudinal label stream not only whether the labels look consistent now but whether the rubric is being applied the same way across time — and to trust only a frozen-gold re-annotation, never within-slice agreement, to answer it.

knowledge_transfer:
Within ML evaluation and labeling the concept transfers *as mechanism*, and it does so across the field's subfields without translation because they share one substrate: a longitudinal label stream produced by a human-applied rubric. The same reframing (the rubric is a measurement instrument whose interpretive calibration silently shifts in use), the same diagnostic discrimination (concept drift in the world versus measurement drift in the instrument, with retraining-on-recent-data predicted to bake the artifact in if the cause is drift), the same non-obvious inference (within-slice inter-annotator agreement can stay high while the whole cohort drifts together, so clean QA dashboards certify nothing; only frozen-gold re-annotation across time cohorts can detect it), the same three boundary conditions (time-varying not constant-offset, cohort-level not per-instance, within-rubric not formally-revised), and the same intervention family (periodic re-rating of held-out gold, cohort-overlap windows, calibration-drift dashboards, frozen-rubric audit cycles, adjudication-precedent versioning) carry intact across clinical chart abstraction (ICD coding conventions sliding as new conditions gain prominence), content-moderation labeling (the same post labeled differently across years with unchanged policy text), search-relevance rating, crowdsourced computer-vision labeling, and sentiment/toxicity labeling. The instrument-calibration scaffolding it borrows from measurement theory and inter-rater-reliability methodology transfers in directly. The vocabulary does not strain across these because they are one substrate sampled in many ML tasks.

Beyond ML the honest account is a *shared abstract mechanism* — case (B) — and the tell is that the same pattern already exists under other community names. Strip the ML idiom and a substrate-neutral structure remains: a measurement instrument's *interpretive calibration* silently shifts over time while its stated specification stays constant, producing artifactual longitudinal change that is indistinguishable from real change without an explicit calibration audit. That structure genuinely recurs across distinct substrates as *co-instances*, not resemblances — "coder drift" or "rater drift" in survey methodology, "diagnostic drift" or "rubric drift" in medicine, "sentencing drift" in law, "instrument drift" in measurement theory. In each, the *general* pattern — a stable-on-paper instrument re-calibrating in the hands of those applying it, so a time series silently changes meaning — is the thing that travels and carries a real, transferable lesson: hold the instances fixed and re-measure across cohorts; never trust within-cohort consensus to certify a stable target. What does *not* travel is the ML-specific cargo: the validation-curve concept-vs-measurement discrimination, the train-test/cross-validation calibration assumption, the three-inconsistent-targets pipeline consequence, and the "annotation drift" name are data-science furniture, and even the name is parochial (other fields call the identical thing something else). So when the cross-domain lesson is wanted, the honest move is to carry the parent — interpretive instrument drift (the emergent `instrument_interpretive_drift`), a sibling-but-distinct neighbor of `measurement_uncertainty_and_observational_noise` (which treats noise around a *stable* instrument, not silent recalibration of the instrument itself) — not the term "annotation drift," whose machinery is substrate-bound (see *Structural Core vs. Domain Accent*).