Processing Chinese Relative Clauses: Evidence for the Subject-Relative Advantage
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{"title"=>"Processing Chinese Relative Clauses: Evidence for the Subject-Relative Advantage", "type"=>"journal", "authors"=>[{"first_name"=>"Shravan", "last_name"=>"Vasishth", "scopus_author_id"=>"8615749400"}, {"first_name"=>"Zhong", "last_name"=>"Chen", "scopus_author_id"=>"56502501600"}, {"first_name"=>"Qiang", "last_name"=>"Li", "scopus_author_id"=>"55869686600"}, {"first_name"=>"Gueilan", "last_name"=>"Guo", "scopus_author_id"=>"55869624300"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pmid"=>"24098575", "sgr"=>"84884829092", "doi"=>"10.1371/journal.pone.0077006", "scopus"=>"2-s2.0-84884829092", "pui"=>"369937439", "isbn"=>"1932-6203", "issn"=>"19326203"}, "id"=>"2eb85b95-82c9-3db7-9481-cd2676b78d02", "abstract"=>"A general fact about language is that subject relative clauses are easier to process than object relative clauses. Recently, several self-paced reading studies have presented surprising evidence that object relatives in Chinese are easier to process than subject relatives. We carried out three self-paced reading experiments that attempted to replicate these results. Two of our three studies found a subject-relative preference, and the third study found an object-relative advantage. Using a random effects bayesian meta-analysis of fifteen studies (including our own), we show that the overall current evidence for the subject-relative advantage is quite strong (approximate posterior probability of a subject-relative advantage given the data: 78-80%). We argue that retrieval/integration based accounts would have difficulty explaining all three experimental results. These findings are important because they narrow the theoretical space by limiting the role of an important class of explanation-retrieval/integration cost-at least for relative clause processing in Chinese.", "link"=>"http://www.mendeley.com/research/processing-chinese-relative-clauses-evidence-subjectrelative-advantage", "reader_count"=>34, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>4, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>2, "Student > Master"=>7, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>2, "Researcher"=>4, "Student > Doctoral Student"=>5, "Student > Ph. D. Student"=>6, "Student > Postgraduate"=>2, "Student > Master"=>7, "Student > Bachelor"=>4, "Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Engineering"=>2, "Unspecified"=>2, "Mathematics"=>1, "Agricultural and Biological Sciences"=>2, "Arts and Humanities"=>1, "Psychology"=>6, "Social Sciences"=>4, "Computer Science"=>1, "Linguistics"=>15}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Social Sciences"=>{"Social Sciences"=>4}, "Psychology"=>{"Psychology"=>6}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>2}, "Computer Science"=>{"Computer Science"=>1}, "Linguistics"=>{"Linguistics"=>15}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"United States"=>2, "Germany"=>1, "India"=>1}, "group_count"=>0}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1222084"], "description"=>"<p>The posterior distribution of the coefficient using different priors; the final column displays the posterior probability that the coefficient is positive, i.e., the probability that Chinese has a subject relative advantage. See text for details.</p>", "links"=>[], "tags"=>[], "article_id"=>812768, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.t008", "stats"=>{"downloads"=>4, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Results_of_meta_analysis_/812768", "title"=>"Results of meta-analysis.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-02 01:46:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1222082"], "description"=>"<p>Experiment 3: The raw reading times at the five regions of interest in the relative clause types, with 95% confidence intervals.</p>", "links"=>[], "tags"=>["times", "regions", "clause"], "article_id"=>812766, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.g005", "stats"=>{"downloads"=>1, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Experiment_3_The_raw_reading_times_at_the_five_regions_of_interest_in_the_relative_clause_types_with_95_confidence_intervals_/812766", "title"=>"Experiment 3: The raw reading times at the five regions of interest in the relative clause types, with 95% confidence intervals.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-02 01:46:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1222079"], "description"=>"<p>The distributions of residuals from maximal linear mixed effects models for the raw, log-transformed, and negative-reciprocal transformed data at the head noun in the Gibson and Wu dataset.</p>", "links"=>[], "tags"=>["distributions", "residuals", "maximal", "linear", "negative-reciprocal", "transformed", "noun", "gibson", "wu"], "article_id"=>812763, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.g002", "stats"=>{"downloads"=>0, "page_views"=>29, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_distributions_of_residuals_from_maximal_linear_mixed_effects_models_for_the_raw_log_transformed_and_negative_reciprocal_transformed_data_at_the_head_noun_in_the_Gibson_and_Wu_dataset_/812763", "title"=>"The distributions of residuals from maximal linear mixed effects models for the raw, log-transformed, and negative-reciprocal transformed data at the head noun in the Gibson and Wu dataset.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-02 01:46:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1222078"], "description"=>"<p>The raw reading times were the ones reported in the paper. The bottom-right plot show the results of the Box-Cox procedure; the procedure suggests a reciprocal transform for stabilizing variance.</p>", "links"=>[], "tags"=>["distributions", "negative-reciprocal", "transformed", "noun", "gibson", "wu"], "article_id"=>812762, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.g001", "stats"=>{"downloads"=>1, "page_views"=>114, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_distributions_of_the_raw_log_transformed_and_negative_reciprocal_transformed_data_at_the_head_noun_in_the_Gibson_and_Wu_dataset_/812762", "title"=>"The distributions of the raw, log-transformed, and negative-reciprocal transformed data at the head noun in the Gibson and Wu dataset.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-10-02 01:46:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1222091"], "description"=>"<p>The original Gibson and Wu data and Experiment 3 combined: The raw reading times at the five regions of interest in the relative clause types, with 95% confidence intervals.</p>", "links"=>[], "tags"=>["gibson", "wu"], "article_id"=>812775, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.t007", "stats"=>{"downloads"=>3, "page_views"=>21, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Data_Analysis_Experiment_3_and_Gibson_and_Wu_data_combined_/812775", "title"=>"Data Analysis: Experiment 3 and Gibson and Wu data combined.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-02 01:46:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1222090"], "description"=>"<p>Analysis of our Experiment 3 data using negative reciprocal reading times and maximal models. A negative sign on the estimated coefficient is an object relative advantage.</p>", "links"=>[], "tags"=>[], "article_id"=>812774, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.t006", "stats"=>{"downloads"=>5, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Data_Analysis_Experiment_3_/812774", "title"=>"Data Analysis: Experiment 3.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-02 01:46:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1222087"], "description"=>"<p>A partition of SR-like and OR-like strings by NP-animacy. The numbers in bold are bona fide RCs. The other patterns are discussed in the text.</p>", "links"=>[], "tags"=>["corpus"], "article_id"=>812771, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.t003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Summary_of_corpus_search_/812771", "title"=>"Summary of corpus search.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-02 01:46:03"}
  • {"files"=>["https://ndownloader.figshare.com/files/1222086"], "description"=>"<p>Analysis of Gibson and Wu data using negative reciprocal reading times and maximal models. A negative sign on the estimated coefficient is an object relative advantage.</p>", "links"=>[], "tags"=>["gibson", "wu"], "article_id"=>812770, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.t002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Analysis_of_Gibson_and_Wu_data_/812770", "title"=>"Analysis of Gibson and Wu data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-02 01:46:03"}
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  • {"files"=>["https://ndownloader.figshare.com/files/1222089"], "description"=>"<p>Analysis of our Experiment 2 data using negative reciprocal reading times and maximal models. A negative sign on the estimated coefficient is an object relative advantage.</p>", "links"=>[], "tags"=>[], "article_id"=>812773, "categories"=>["Biological Sciences", "Science Policy", "Information And Computing Sciences"], "users"=>["Shravan Vasishth", "Zhong Chen", "Qiang Li", "Gueilan Guo"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0077006.t005", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Data_Analysis_Experiment_2_/812773", "title"=>"Data Analysis: Experiment 2.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-10-02 01:46:03"}
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  • {"unique-ip"=>"11", "full-text"=>"13", "pdf"=>"1", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"3"}
  • {"unique-ip"=>"8", "full-text"=>"5", "pdf"=>"4", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2019", "month"=>"4"}

Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Psychology", "average_usage"=>[284, 458, 579, 688, 782, 879, 957, 1048, 1126, 1204, 1280, 1357, 1415]}, {"subject_area"=>"/Computer and information sciences", "average_usage"=>[297, 488, 616, 724, 828, 939, 1038, 1127, 1223, 1311, 1393, 1479, 1556]}, {"subject_area"=>"/Computer and information sciences/Information technology", "average_usage"=>[265, 446, 547, 656, 751, 809, 898, 978, 1077, 1216, 1295, 1357, 1403, 1469]}, {"subject_area"=>"/Engineering and technology/Software engineering", "average_usage"=>[289, 479, 594, 761, 915, 998, 1133, 1262, 1368, 1465, 1562, 1644, 1724]}, {"subject_area"=>"/Social sciences", "average_usage"=>[289, 475, 593, 703, 805, 902, 990, 1078, 1158, 1250, 1336, 1417, 1482]}, {"subject_area"=>"/Social sciences/Linguistics", "average_usage"=>[290, 461, 572, 671, 770, 847, 934, 1000, 1096, 1189, 1263, 1319, 1382]}]}
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