Solstad & Bott (2022): On the Nature of Implicit Causality and Consequentiality #
This file formalizes the Two-Mechanism Account of Solstad and Bott. Implicit causality
(I-Caus), the coreference bias of a continuation after because, is verb-semantic: on the
authors' Empty Slot Theory, a stimulus argument causes the psychological state the verb
names without the verb saying how, so the argument carries an underspecified proposition
that an explanation fills. Implicit consequentiality (I-Cons), the bias after and so, is
discourse-structural: on the Contiguity Principle of Kehler, a consequence continues
from the final state of the prompt's eventuality, held by the experiencer of the state or by
the participant the action affects. Both mechanisms read off a verb class's proto-role grid
(Dowty): CarriesSlot is the stimulus label, HoldsEndState the experiencer label or
causal affectedness, ICaus and ICons the resulting coreference predictions, and Bias
routes them through the direction of the cause–effect relation a connective signals.
The rival One-Mechanism Account of Crinean and Garnham reads both biases off one causal
decomposition, causes with agents and stimuli alike, consequences with experiencers and
patients, so a continuation about the end-state argument should be a consequence. The
Two-Mechanism Account lets slot filling take precedence over contiguity, so a slot predicate
is continued by an explanation whichever argument the continuation is about. oneMechanism
and twoMechanism state the two coherence predictions; they agree on the slot argument and
diverge exactly on the end-state argument of a slot predicate, the paper's Asymmetry
Hypothesis. The accounts also part on agent-patient verbs, whose agent is a cause on the
One-Mechanism reading but carries no slot, since it causes by the very action the verb names.
Four sentence-continuation experiments on German stimulus-experiencer (ärgern) and experiencer-stimulus (bewundern) verbs test the hypothesis. Experiment 1 confirms the mirror coreference biases: after weil the stimulus argument, after sodass the experiencer, with the two per-verb biases almost perfectly anticorrelated. Experiment 2 (full stop) finds explanations the most frequent relation for both classes, about three times as frequent as consequences. Experiment 3 (forced reference) finds explanations at least as frequent as consequences even when the continuation is forced onto the I-Cons argument, against the One-Mechanism symmetry. Experiment 4 finds explanatory specifications, continuations giving the direct cause of the psychological state, almost only in I-Caus-congruent explanations, and consequence specifications, restatements of the experiencer's state, essentially never: consequences introduce an eventuality subsequent to the prompt's, as contiguity predicts.
Implementation notes #
The experimental results are reported in prose above; the library's format for
experimental data is pending. The psych grids are the substrate's psychCausal and
psychState, which are each other's flip, so the mirror theorem is one instance of
bias_flip. The agent-evocator grid judgment follows the paper's description of
Crinean and Garnham: the evocator is causally affected by the agent's act and, through
the verb's presupposition of a preceding eventuality it took part in, the non-agentive cause
of the agent's intention, so it is both the slot argument and the end-state argument.
Agent-patient verbs take the manner-contact grid mannerContact.
References #
The argument positions of a prompt Name₁ verb-ed Name₂.
Instances For
Equations
- SolstadBott2022.instDecidableEqArgument x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
Equations
- One or more equations did not get rendered due to their size.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Equations
- SolstadBott2022.instReprArgument = { reprPrec := SolstadBott2022.instReprArgument.repr }
The other argument position.
Equations
Instances For
The proto-role profile a grid assigns to a position.
Equations
Instances For
The grid with subject and object exchanged, when there is an object.
Equations
- SolstadBott2022.flip r = Option.map (fun (o : ArgumentStructure.EntailmentProfile) => { subjectProfile := o, objectProfile := some r.subjectProfile }) r.objectProfile
Instances For
The two mechanisms #
Mechanism 1, the empty slot. A stimulus causes the psychological state the verb names without the verb saying how, so it carries an underspecified proposition that an explanation fills. An agent causes by the action the verb names and carries no slot.
Equations
Instances For
Mechanism 2, the Contiguity Principle. A consequence continues from the final state of the prompt's eventuality, held by the experiencer of the psychological state or by the participant the action affects.
Equations
Instances For
Equations
- One or more equations did not get rendered due to their size.
A slot argument is entailed to cause.
A slot argument holds the end state only if it is causally affected, so on a grid without affected arguments the two mechanisms never pick the same argument.
I-Caus coreference goes to the slot argument.
Equations
- SolstadBott2022.ICaus r a = ∃ p ∈ SolstadBott2022.profileAt r a, SolstadBott2022.CarriesSlot p
Instances For
I-Cons coreference goes to the end-state argument.
Equations
- SolstadBott2022.ICons r a = ∃ p ∈ SolstadBott2022.profileAt r a, SolstadBott2022.HoldsEndState p
Instances For
Equations
- SolstadBott2022.instDecidableICaus r a = id inferInstance
Equations
- SolstadBott2022.instDecidableICons r a = id inferInstance
The connectives of the continuation prompts, German weil and sodass, the paper's because and and so.
- because : Connective
- andSo : Connective
Instances For
Equations
- SolstadBott2022.instDecidableEqConnective x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
Equations
- One or more equations did not get rendered due to their size.
Equations
- SolstadBott2022.instReprConnective = { reprPrec := SolstadBott2022.instReprConnective.repr }
Equations
- One or more equations did not get rendered due to their size.
Instances For
The cause–effect relation a connective signals.
Equations
Instances For
A connective elicits a coreference bias toward the slot argument when the relation it signals seeks its cause in the continuation, and toward the end-state argument when it seeks its effect there.
Equations
- One or more equations did not get rendered due to their size.
Instances For
Equations
- One or more equations did not get rendered due to their size.
Exchanging subject and object exchanges the biases, whatever the connective.
The psych doublets #
The mirror of Experiment 1: the biases of the experiencer-stimulus class are those of the stimulus-experiencer class with the arguments exchanged.
Stimulus-experiencer verbs: I-Caus to the subject, I-Cons to the object.
Experiencer-stimulus verbs: I-Caus to the object, I-Cons to the subject.
The two accounts and the Asymmetry Hypothesis #
The One-Mechanism Account's I-Caus argument: whichever argument the verb entails to cause, agent or stimulus alike.
Equations
Instances For
Equations
- SolstadBott2022.instDecidableICausOne r a = id inferInstance
The coherence relation the One-Mechanism Account predicts for a continuation about a:
an explanation about a cause argument, a consequence about an end-state argument.
Equations
- One or more equations did not get rendered due to their size.
Instances For
The coherence relation the Two-Mechanism Account predicts: slot filling takes precedence over contiguity, so a slot predicate is continued by an explanation whichever argument the continuation is about, and a slotless predicate has no preferred relation.
Equations
- SolstadBott2022.twoMechanism r = if ∃ (a : SolstadBott2022.Argument), SolstadBott2022.ICaus r a then some Discourse.Coherence.Relation.explanation else none
Instances For
The accounts agree on the slot argument.
The Asymmetry Hypothesis holds that about the end-state argument of a slot predicate, an argument not itself entailed to cause, the One-Mechanism Account predicts a consequence and the Two-Mechanism Account an explanation.
For the psych doublets the accounts diverge at the I-Cons argument, the condition Experiment 3 forces.
The four verb classes #
The evocator argument of judgement verbs (criticise, congratulate): affected by the agent's act and, through the verb's presupposition of a preceding eventuality it took part in, the non-agentive cause of the agent's intention.
Equations
Instances For
Agent-evocator verbs: an agent acting on an evocator.
Equations
- SolstadBott2022.judgment = { subjectProfile := ArgumentStructure.accomplishmentSubjectProfile, objectProfile := some SolstadBott2022.evocator }
Instances For
Equations
- SolstadBott2022.instDecidableEqVerbClass x✝ y✝ = if h : x✝.ctorIdx = y✝.ctorIdx then isTrue ⋯ else isFalse ⋯
Equations
- One or more equations did not get rendered due to their size.
Instances For
Equations
- SolstadBott2022.instReprVerbClass = { reprPrec := SolstadBott2022.instReprVerbClass.repr }
The proto-role grid of each class.
Equations
Instances For
The class's I-Caus bias, the slot argument if any.
Equations
- c.icausBias = List.find? (fun (x : SolstadBott2022.Argument) => decide (SolstadBott2022.ICaus c.roles x)) [SolstadBott2022.Argument.np1, SolstadBott2022.Argument.np2]
Instances For
The class's I-Cons bias, the end-state argument if any.
Equations
- c.iconsBias = List.find? (fun (x : SolstadBott2022.Argument) => decide (SolstadBott2022.ICons c.roles x)) [SolstadBott2022.Argument.np1, SolstadBott2022.Argument.np2]
Instances For
Stimulus and evocator arguments carry the slot, agents and patients do not: I-Caus is subject-biased for stimulus-experiencer verbs, object-biased for experiencer-stimulus and agent-evocator verbs, and balanced for agent-patient verbs, as the large norming studies the paper reviews found.
I-Cons goes to the object for every class but the experiencer-stimulus verbs, whose only state is the subject's.
The evocator plays a dual role, being both the slot argument and the end-state argument.
Where the accounts part on agent-patient verbs: the agent is a cause on the One-Mechanism reading, so that account predicts a subject bias, but no argument carries a slot, so the Two-Mechanism Account predicts no I-Caus bias and no preferred relation.