Acceptability Judgment Paradigm #
@cite{sprouse-2007} @cite{sprouse-et-al-2012}
Shared vocabulary for the acceptability judgment experimental paradigm — formal-syntax / experimental-syntax studies that elicit sentence acceptability ratings (typically on a Likert or 100-point scale) to test categorical predictions of grammatical theory.
Architectural role #
Paradigms/ is the contract layer between Theories/ and
Phenomena/Studies/. Theories produce predictions in their native
types; bridge theorems in Studies/ translate those predictions into
paradigm-typed predictions and prove they satisfy the empirical patterns
documented in the study file. The paradigm itself is theory-agnostic:
it specifies what kind of input the experiment provides and what
shape of output a theory must produce.
What this file provides #
FactorialCondition: a typed cell in a 2-factor factorial design. Generic over the factor types so that any pair (Bool × WhStrategy,Person × Number,Animacy × Definiteness, …) plugs in.DDResult: a difference-in-differences score (Maxwell & Delaney 2003 method, used by @cite{sprouse-et-al-2012} for island effects and by @cite{chan-shen-2026} for wh-the-hell licensing). Stored as ℚ for exact arithmetic, with a BooleaninteractionSignificantflag for the linear-mixed-effects model's interaction p-value.AccountPredictions: an n-cell prediction tuple from a theoretical account, with amatchesPatterncomparator. Generic overnso that 2×2 (4 cells), 2×3 (6 cells), etc. all use the same machinery.
Out of scope (per CLAUDE.md Processing scope) #
- Statistical-model specifications (LME formulae, contrast coding, random-effect structures) — analysis-pipeline detail
- Stimulus norming details (filler ratings, balancing constraints) — study-internal methodology
- Participant-population metadata (L1, age, dialect) — study metadata
- Raw rating scales / z-score transformations — measurement detail
The paradigm specifies the empirical contract between an account and the data — what cells are tested and what pattern is observed — not the statistical apparatus that produces the pattern.
A typed cell in a 2-factor factorial design (@cite{sprouse-2007}: §2; @cite{sprouse-et-al-2012}: §2.1).
Generic over the two factor types so that the same machinery
accepts any 2×2/2×3/3×3 design. The sentence field carries the
actual stimulus (verbatim from the paper); label is the
experiment's printed condition name.
- label : String
Condition label as printed in the paper (e.g. "WhHell-Situ").
- level1 : F1
Level of the first factor.
- level2 : F2
Level of the second factor.
- sentence : String
Verbatim stimulus sentence.
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A difference-in-differences (DD) score from a 2×2 factorial design, using the Maxwell & Delaney (2003) computation: DD = D2 − D1, where D1 and D2 are the two main-factor differences. A positive DD reflects a superadditive interaction — a penalty above and beyond the sum of the two main effects.
Used by @cite{sprouse-et-al-2012} as the standard test of island effects in experimental syntax, and by @cite{chan-shen-2026} for wh-the-hell licensing.
Stored as ℚ rather than Float to respect linglib's exact-arithmetic
discipline. The interactionSignificant flag records the linear
mixed-effects model's interaction-term p-value (typically p < 0.05).
- comparison : String
Description of the two-factor contrast (e.g. "in-situ vs full movement").
- dd : ℚ
DD score. Positive → superadditive interaction; ≈ 0 → additive.
- interactionSignificant : Bool
Did the LME model's interaction term reach significance?
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A DD score is superadditive if positive — extra penalty beyond main effects.
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- r.Superadditive = (r.dd > 0)
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- r.instDecidableSuperadditive = id inferInstance
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- r.instDecidableAdditive = id inferInstance
A theoretical account's predicted acceptability pattern across n
cells of a factorial design. Each cell is True (predicted acceptable)
or False (predicted unacceptable).
Used to compare a theory's predictions against the empirical pattern
via matches.
- cell : Fin n → Prop
Per-cell predicted acceptability.
- decCell (i : Fin n) : Decidable (self.cell i)
Each cell is decidable (so pattern comparison is decidable).
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Two prediction tuples match iff they predict the same pattern in every cell.
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- a.instDecidableMatches b = Fintype.decidableForallFintype
Build a 4-cell AccountPredictions from four explicit Props (the
standard 2×2 case). Convenience for the most common factorial.
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Build a 3-cell AccountPredictions (e.g., a 1×3 strategy contrast).
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Minimal pairs as introspective grammaticality contrasts — the methodological tradition that Sprouse's factorial-design machinery above was introduced to discipline. A minimal pair records a single (typically the analyst's) judgment per sentence: one is grammatical, one is not, and they differ minimally in the property being tested.
Two parallel families:
* **Word-based** (`MinimalPair`, `PhenomenonData`): sentences are
`List Word`, requiring feature specifications. Used by analyses
that operate on parsed/featural representations (HPSG, DG, Minimalism).
* **String-based** (`SentencePair`, `StringPhenomenonData`): sentences
are raw strings, parseable by any theory. Used by phenomenon data
files that should remain free of theoretical commitments.
A minimal pair: grammatical vs ungrammatical, with context.
Conceptually a degenerate FactorialCondition Unit Bool with the
Bool factor being grammaticality and a single trivial Unit factor;
kept as a distinct shape because the introspective tradition speaks
in grammatical / ungrammatical rather than factorial cells.
- grammatical : List Word
- ungrammatical : List Word
- clauseType : Features.ClauseForm
- description : String
- citation : String
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Collection of minimal pairs for a phenomenon.
- name : String
- pairs : List MinimalPair
- generalization : String
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Check if a grammaticality predicate captures a minimal pair.
Captures the pair iff the predicate accepts the grammatical sentence and rejects the ungrammatical sentence.
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- Paradigms.AcceptabilityJudgment.capturesMinimalPairBy pred pair = (pred pair.grammatical && !pred pair.ungrammatical)
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Check if a grammaticality predicate captures all minimal pairs in a phenomenon dataset.
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- Paradigms.AcceptabilityJudgment.capturesPhenomenonData pred phenom = phenom.pairs.all (Paradigms.AcceptabilityJudgment.capturesMinimalPairBy pred)
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String-based minimal pair for theory-neutral phenomena.
Unlike MinimalPair which uses List Word (requiring feature
specifications), this type uses raw strings that can be parsed by any
theory. This keeps empirical data in Phenomena/ free from
theoretical commitments.
- grammatical : String
The grammatical sentence
- ungrammatical : String
The ungrammatical sentence
- clauseType : Features.ClauseForm
Clause form (declarative, question, etc.)
- description : String
Description of what the pair tests
- citation : String
Citation for the data; empty string for uncited examples.
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- Paradigms.AcceptabilityJudgment.instBEqSentencePair.beq x✝¹ x✝ = false
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String-based phenomenon data for theory-neutral representation.
This is the string-based analogue of PhenomenonData. Phenomena files
should use this type so that empirical data is decoupled from any
particular grammatical theory's representation.
- name : String
Name of the phenomenon
- pairs : List SentencePair
List of minimal pairs
- generalization : String
Generalization captured by this data
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A SentencePair is structurally a 1×2 factorial design: one
Unit-valued first factor, a Bool-valued grammaticality factor,
one cell per Bool value. This makes the relationship to §1's
factorial discipline explicit: SentencePair is the degenerate case
of FactorialCondition Unit Bool lifted to a pair of cells.
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