How to Construct an
Analysis
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2.11 Constraint Ranking by Algorithm
and Computer:
2
•
Constraint Demotion
(Tesar and Smolensky 1998, 2000)
The main idea in constraint demotion is that a loser-favoring constraint moves down in the hierarchy
from some initial ranking until all of its Ls are dominated by Ws, but no further.
•
Recursive Constraint Demotion algorithm (RCD)
Begin by assembling all of the information that can contribute to ranking into a single table called the
support,
since it supports the inferences about ranking.

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The first step in RCD
is to identify all of the
constraints that favor no losers.
•
These are the constraints that have no Ls in their
columns.
•
Constraints that favor no losers are undominated.
•
They belong at the top of the constraint
hierarchy.

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The next step
is to hide the *Complex-Syllable,
*C
unsyll
, and Max-C columns in the support, since
there is nothing more to learn from them.
•
We also must hide any losers that are disfavored
by any of these three constraints. Those losers
have been fully accounted for, so their
performance on lower-ranking constraints is
irrelevant to the ranking.
•
For example, *Complex-Syllable favors the
winner over *[la:n.hin], so *[la:n.hin]’s row has to
be hidden.

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The recursive step
that gives RCD its name. (A recursive procedure is one that
takes its own output as further input.
•
Looking only at the considerably diminished support table (88), search again
for any constraints that favor no losers.
•
Here, Dep meets this criterion.
•
Dep is therefore placed in the constraint
hierarchy below the top-ranked constraints..]

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The recursive step
that gives RCD its name. (A recursive procedure is one that
takes its own output as further input.
•
Looking only at the considerably diminished support table (88), search again
for any constraints that favor no losers.
•
Here, Dep meets this criterion.
•
Dep is therefore placed in the constraint
hierarchy below the top-ranked constraints..]

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RCD can be straightforwardly implemented in a
computer program, and the freely downloadable
OTSoft package includes RCD among its many
features (Hayes et al. 2003).

2.12 The Logic of Constraint Ranking
and Its Uses:
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Elementary Ranking Condition
•
An ERC contains all of the information
about constraint ranking that is provided
by a single winner~loser comparison.
•
An ERC is therefore the same as a single
row of a support table like (85) – it
contains W, L, or an empty cell for every
constraint
•
Which winner~loser pairs are most informative
about ranking?= When does one ERC entail
another ERC?

2.12 The Logic of Constraint Ranking
and Its Uses:
11
•
Since every L must be dominated by some W, ERC (a) tells us that Constraint1 dominates
both Constraint2 and Constraint3. ERC (b) tells us only that Constraint1 dominates
Constraint3, so ERC (a) is more informative.