In:Choosing a Grammar: Learning paths and ambiguous evidence in the acquisition of syntax
Isaac Gould
[Linguistik Aktuell/Linguistics Today 238] 2017
► pp. v–viii
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Published online: 19 June 2017
https://doi.org/10.1075/la.238.toc
https://doi.org/10.1075/la.238.toc
Table of contents
Chapter 1.Introduction
1.A model for language learning
1.1Core themes: A first look
1.2Revisiting the core themes: A look at some similar models
2.The puzzle of ambiguous evidence
2.1Preliminary considerations
2.2The general case
2.3The subset case
3.Ambiguous evidence and modeling learner errors and variability
3.1Errors
3.2Variability
4.Ambiguity and development
Chapter 2.The Learning Model
1.Introduction
2.Overview of the model
2.1Introducing the model with two toy examples
2.2The learning procedure: A summary
2.3Ambiguous vs. unambiguous evidence
2.4Prior probabilities and the update procedure
2.5Generality of the model and learning results
3.Comparison with other models
3.1Sakas and Fodor (2001): The Structural Triggers Learner
3.2Gibson and Wexler (1994): The Triggering Learning Algorithm
3.3Yang (2002): The Naïve Parameter Learner
4.Summary
Chapter 3.The Acquisition of Verb Movement in Swiss German: Modeling child production errors and variability
1.Introduction
2.The core data of verb placement in Swiss German
2.1Adult grammar
2.2Child productions
3.Some possible analyses
3.1Alternative #1: Overgeneralizing V2 in embedded clauses
3.2Alternative #2: Extraposition in embedded clauses
3.3Alternative #3: Overgeneralizing VR/VPR
3.4Schönenberger’s analysis: Verb movement in embedded clauses
4.A learning model for the acquisition puzzle
4.1Analysis of the adult and child grammars
4.2Overview of the model
4.3Insight of the model
4.4Predictions for the model
5.Results and discussion
5.1Priors and update procedure
5.2Results
5.3A closer look at the acquisition data: The distribution of subjects in embedded clauses
6.Comparison with other learning models
7.The broader German perspective
8.The relation between input and learning
9.Summary
Chapter 4.Head-finality and Verb Movement in Korean: Modeling variability and non-variability across learners
1.Introduction
2.Modeling the effects of parameter interaction: The core example
2.1A schematic version of the model: Learning in a 3-parameter hypothesis space
2.2Results of the 3-parameter model
3.Making the model more general: A simplified Korean
3.1Expanding the hypothesis space
3.2Expanding the corpus
3.3Predictions for the model
4.Han et al. (2007) and the current model: A deeper look at modeling end-state variability
4.1Review of Han et al. (2007)
4.2Comparison of Han et al. (2007) and the current model
4.3Toward a unification of Han et al. (2007) and the current model
5.Results and discussion
5.1Results of the 5-parameter model
5.2Variability with a probabilistic learner: A broader perspective
6.Comparison with other models
7.Constraining the model: A first attempt
8.Summary
Chapter 5.The Case of Zero-Derived Causatives in English: Learning from implicit negative evidence
1.Introduction
2.Pylkkänen (2008) and the learning challenge
2.1Review of Pylkkänen (2008)
2.2The learning challenge
3.Addressing the challenge
3.1Learning from implicit negative evidence: The case of zero-derived causatives
3.2Making the model more general
3.3Results
3.4Learning the grammar of the superset language
4.Comparison with other models
5.Summary
Chapter 6.Learning biases
1.Introduction
2.A problem for defaults
2.1Errors in Swedish
2.2Errors in English
2.3Toward accounting for the Swedish and English errors
3.Constraining the model: A new proposal
4.Summary
Chapter 7.Final Summary
References
Appendix 1.Swiss German input types and corresponding compatible grammars
Appendix 2.Additional evidence for a Root-selecting grammar in English
Index
