---
slug: grain_misalignment_artifact
name: Grain Misalignment Artifact
one_liner: "A spurious result produced when an operation is applied at a decomposition level that differs from the level at which the phenomenon's structure exists — the outcome pole whose choice-pole dual is grain_of_analysis."
type: prime
schema_version: 2
status: density_v2_draft
categories: [epistemic, structural, computational]
origin_domain: statistics_and_measurement
alternate_origin_domains: [geography_spatial_analysis, machine_learning, ecology_and_taxonomy]
aliases: [scale_dependent_artifact, aggregation_artifact, maup_artifact, grain_mismatch_bias]
related: []
solution_archetypes: []
review_flags:
- "OPERATOR-DERIVED (op-01 dualization, sub-flavor 1c) — the outcome/error dual of `grain_of_analysis` along the choice-vs-consequence axis (the artifact that results when the grain choice is wrong). Discovered in the op-01 full sweep 2026-07-03. Verified absent via search_prime + slug check (no grain_misalignment_artifact / maup / aggregation_artifact slug present). COLLISION RISK: strong conceptual overlap with the Modifiable Areal Unit Problem (MAUP) and general aggregation/ecological-fallacy territory — may be an instance-family rather than a distinct prime. STATUS: HOLD — pending owner curation."
- "Created 2026-07-03; STUB ONLY (frontmatter + Core Idea + Notes). Did NOT go through Phase-A triage. SI/SF/similarity grades are PROPOSER ESTIMATES pending triangulation. Body sections (Structural Signature onward) NOT yet written."
- "Phase-C action: re-similarity-check against grain_of_analysis, ecological_fallacy, aggregation, scale, simpson_s_paradox, and any MAUP/aggregation-artifact prime before incorporation; if kept, draw the dual edge to grain_of_analysis (choice→artifact) and parent edges to any aggregation/scale-error genus. one_liner must be synced to a v1 draft per CLAUDE.md before merge."
substrate_independence:
  composite_substrate_independence: 4
  domain_breadth: 4
  structural_abstraction: 4
  transfer_evidence: 3
  reasoning: 'The pattern "an operation applied at the wrong decomposition level yields a result that is an artifact of the level, not of the phenomenon" is stated in pure structural terms — a level of application, a level of true structure, and a mismatch that corrupts recovery — and demands no particular medium, so structural abstraction is a strong 4 (held below 5 because the sharpest formalizations, MAUP and the ecological fallacy, are statistical-spatial rather than fully medium-free). It recurs across substrates: the Modifiable Areal Unit Problem in spatial statistics, the ecological/atomistic fallacies in social science, over- and under-splitting in taxonomy and clustering, over- and under-parameterization in model fitting, and coding-granularity errors in qualitative analysis — a domain breadth of 4. Transfer evidence is real but clusters in statistics, geography, and data analysis rather than spanning the physical and biological sciences exhaustively, so transfer evidence is 3 and the composite is 4.'
similarity_to_nearest_existing_prime:
  slug: grain_of_analysis
  similarity: 0.72
structural_framed:
  label: structural
  aggregate: 0.15
  criteria: {vocab_travels: 0.2, evaluative_weight: 0.1, institutional_origin: 0.1, human_practice_bound: 0.1, import_vs_recognize: 0.2}
  rationale: 'The artifact is a relational error — a mismatch between the level of an operation and the level of a phenomenon''s structure — carrying no normative or institutional content; a wrong grain is not morally wrong, only structurally corrupting. The faint non-zeros reflect that named instances (MAUP, ecological fallacy) are terms of art one carries in, and that the phenomenon is most often diagnosed in human analytic practice; but the underlying structure is recognized wherever an operation is applied across levels, including in automated clustering and model fitting with no human in the loop.'
phase_b_passes_completed: []
---
# Grain Misalignment Artifact

## Core Idea

A grain misalignment artifact is *a spurious result that an operation produces because it was applied at a decomposition level different from the level at which the phenomenon's structure actually lives*. It is the outcome pole of a single axis whose choice pole is `grain_of_analysis`: where grain-of-analysis names the *decision* about which level to operate at, the artifact names *what that decision manufactures when it is wrong*. The operation still runs, still returns numbers, still looks like a measurement of the phenomenon — but the value it reports is a function of the chosen grain rather than of the world, and it moves when the grain moves even though nothing about the underlying phenomenon has changed. The load-bearing property is *level-dependence of the result under a fixed phenomenon*: the same data, re-partitioned or re-aggregated at a different level, yields a materially different answer, which is the signature that the answer is an artifact of the grain.

The mismatch corrupts in two opposite directions, and the artifact is the union of both failure modes. Operate at a *finer* grain than the phenomenon supports — code every sentence, fit a parameter per data point, split taxa past reproductive coherence, cluster past the true number of groups — and the operation reads within-level noise as if it were between-level signal, hallucinating structure that is not there. Operate at a *coarser* grain than the phenomenon supports — lump qualitatively distinct cases under one code, fit one global parameter where the system has regimes, treat distinct species as one taxon, aggregate individuals into areal units — and the operation averages over structure it needed, erasing signal that was really present. In both directions the failure is silent: no error is thrown, because the operation is perfectly well-defined at the wrong level; the corruption shows up only against a *recovery condition* — can the phenomenon's true structure be reconstructed from the operation's output? — which the artifact quietly fails. The characteristic cost of the pattern is therefore *misplaced confidence*: a result that carries all the surface credibility of a valid measurement while being an artifact of the analyst's partition.

Read structurally, the same object appears wherever an operation is applied across a level of decomposition. In **spatial statistics** it is the Modifiable Areal Unit Problem: correlations between variables change — even reverse — when the same points are aggregated into different zones. In **social science** it is the ecological (and atomistic) fallacy: a relationship that holds at the group level need not hold at the individual level, and inferring one from the other manufactures the artifact. In **model fitting and machine learning** it is over- and under-parameterization: too many parameters fit noise, too few fit the mean and miss the regimes; the fitted structure is an artifact of the chosen resolution. In **taxonomy, clustering, and qualitative coding** it is the splitter/lumper artifact: the number and shape of the recovered categories is set by the coding grain, not only by the cases. Across all of these the recognizable move is identical — an operation defined at one level, applied to a phenomenon structured at another, returning an answer that indexes the mismatch rather than the world.

## Notes

**Provenance.** Produced by op-01 dualization, sub-flavor 1c (outcome/consequence dualization), from the input prime `grain_of_analysis`. The dualization inverts the axis from *the choice of grain* to *the artifact that the wrong choice generates*. Single-route proposal in the op-01 full sweep 2026-07-03; convergence signal is therefore weak (one route), and the strong lattice adjacency to its own input prime is the main reason it merits a stub rather than an auto-accept.

**For owner evaluation (keep/cut).** The case FOR: there is a clean choice/consequence lattice gap. `grain_of_analysis` names the decision; this candidate names the failure the wrong decision produces, and the encyclopedia elsewhere does keep some outcome-primes distinct from their choice-primes when the outcome has its own diagnostic signature (here: result-moves-with-grain-under-fixed-phenomenon, and the recovery-condition test). The artifact also has genuine cross-domain reach (MAUP, ecological fallacy, over/under-fitting, splitter/lumper) and a portable diagnostic. The specific RISKS Kurt should weigh: (1) **may collapse into `grain_of_analysis`** — if the artifact is fully entailed by "wrong grain," it is a corollary/theorem of the input prime rather than a separate prime; the similarity estimate (~0.72) is high enough that this is the live worry. (2) **MAUP-instance / aggregation-artifact risk** flagged in the manifest — the sharpest named cases (MAUP, ecological fallacy) may be *the* content, making this a domain instance of a broader aggregation/scale-error prime rather than a prime itself; the manifest suggests evaluating candidate slugs `maup` / `aggregation_artifact`. (3) **genus question** — the better hold may be a general "operation-applied-at-wrong-level artifact" or an "aggregation/scale artifact" genus, with grain-misalignment as one species. There is a real lattice-gap/pair-completion signal (choice-prime present, consequence-prime absent); the decision is whether that gap is worth a distinct prime or is better filled by an edge and a note on `grain_of_analysis`.

**At incorporation.** Re-run similarity against `grain_of_analysis`, `ecological_fallacy`, `simpson_s_paradox`, `aggregation`, `scale`, and any existing MAUP/aggregation-artifact prime; confirm it does not collapse into the input prime before writing the body. If kept, draw the dual edge grain_of_analysis→grain_misalignment_artifact (choice→consequence), a parent edge to whatever aggregation/scale-error genus is chosen, and sibling edges to `ecological_fallacy` / `simpson_s_paradox` if those are present. Sync the final `one_liner` to a v1 draft per CLAUDE.md before merge.
