Title:
Subject-verb agreement in Jordanian Arabic : a variationist approach / by Salam Nouri Salem Obeidat ; supervised by Dr. Marwan Jarrah. التوافق بين الفعل والفاعل باللهجة الأردنية : منهج تنوعي
التوافق بين الفعل والفاعل باللهجة الأردنية : منهج تنوعي التوافق بين الفعل والفاعل باللهجة الأردنية : منهج تنوعي
Author:
Obeidat , Salam Nouri Salem, author.
Jarrah, Marwan, supervisor.
The University of Jordan. School of Foreign Languages. Department of English Language and Literature.
General Notes:
Thesis (M. A. in Language, Culture, and Communication)--The University of Jordan (Amman, Jordan), School of Foreign Languages
, Department of English Language and Literature, 2022.
Includes bibliographical references and index.
The current study aims to investigate the sociolinguistic variation of the possible alternatives of subject-verb agreement in Jordanian Arabic (JA) as spoken in Irbid, a city located in northern Jordan. The study adopts the framework of the variationist sociolinguistics (Labov 1972, et seq.) to quantitatively explore the role of a number of social (i.e., age, gender, education and region) and linguistic factors (i.e., word order, animacy of the subject, collectivity of the subject and gender of the subject) in constraining the variant choice of using subject-verb agreement in JA structure. The study uses a corpus of spontaneous speech data including 32 sociolinguistic interviews conducted with 32 participants who speak JA and live in Irbid. Distributional analysis, multivariate analysis, and cross-tabulation techniques are employed using GOLDVARB X (Sankoff, Tagliamonte and Smith, 2005) to analyze the data. The overall distribution of [1600] tokens shows that subject-verb full agreement variant is evidently more frequent than other variants (i.e., number partial agreement, gender partial agreement, and non-concord) in JA. The multivariate analysis reveals that among the social factors, gender and region are found statistically significant in constraining the variant choice. For example, rural male speakers are found to use full subject-verb agreement variant more frequently than urban female speakers, as the latter are found to lead the divergence from using this variant towards the preference of the other aforementioned patterns. Moreover, two linguistic factors (i.e., gender of the subject and animacy of the subject) are statistically significant in conditioning the variant selection. Concerning the gender of the subject, it is found that masculine subjects prefer full subject-verb agreement more frequently than their feminine counterparts. Likewise, animate subjects are found to favor full agreement between the verb and the subject while inanimate subjects disfavor it.
تهدف الدراسة الحالية إلى البحث في التنوع الاجتماعي اللغوي لبدائل التوافق بين الفعل والفاعل في اللهجة الأردنية المحكية في مدينة إربد الواقعة شمالي الأردن. من الناحية النظرية، تتبع الدراسة نهج علم اللغة الاجتماعي التنوعي (لابوف 1972، ومن يليه)، حيث تقدم دليلاً كمياً واضحاً يؤكد الدور الفاعل لعدد من العوامل الاجتماعية (ممثلة بالعمر والنوع الاجتماعي والتعليم والمنطقة السكنية) واللغوية (ممثلة بترتيب الكلمات وحيوية الفاعل وجمعيّة الفاعل وجنس الفاعل) في تحديد اختيار المتغير المتعلق بتوافق الفعل والفاعل في قواعد اللهجة الأردنية.
وتستند الدراسة على متن من الخطاب العفوي المتضمن 32 مقابلة اجتماعية لغوية ل32 مشاركاً جميعهم يتحدثون اللهجة الأردنية ويقيمون في إربد. وتستخدم الدراسة برنامج GoldvarbX (سانكوف، تغليمونتي وسميث، 2005) الذي يتيح إمكانية إجراء التحليل التوزيعي، والتحليل متعدد المتغيرات، وتقنية الجدولة المتقاطعة بهدف تحليل البيانات.
ويبين التوزيع الكلي ل1600 تركيب بشكل واضح أن متغير التوافق الكامل بين الفعل والفاعل هو أكثر تكراراً من المتغيرات الأخرى في اللهجة الأردنية. وتظهر الجداول المتقاطعة للعوامل الاجتماعية واللغوية مدى تقييد تلك العوامل لاختيار المتغير. كما يظهر التحليل متعدد المتغيرات المستخدم لتحديد الدلالة الإحصائية لمجموعة العوامل أن النوع الاجتماعي والمنطقة السكنية هي عوامل اجتماعية تقيد اختيار المتغير. فعلى سبيل المثال خلصت الدراسة إلى أن الريفيين الذكور هم أكثر استخداماً التوافق التام بين الفعل والفاعل من الإناث الحضريات اللواتي يعتبرن رائدات في استخدام أنماط ابتكارية فيما يتعلق بتوافق الفعل والفاعل في اللهجة الأردنية. علاوة على ذلك فقد تم الكشف عن عاملين لغويين (جنس الفاعل، وحيوية الفاعل) لهما أهمية إحصائية في تحديد اختيار المتغير.
The electronic version is available in theses database \\ University of Jordan.
Includes abstracts in Arabic and English.
Subject:
Linguistics
Arabic language -- Jordan -- Dialects.
Language and languages -- Variation.
Arabic language -- Spoken Arabic.
Dissertation Note:
Thesis (M. A. in Language, Culture, and Communication)--The University of Jordan (Amman, Jordan), School of Foreign Languages
, Department of English Language and Literature, 2022.
Physical Description:
1CD-ROM : PDF.
Publication Date:
2022.
Title:
Subjects and objects art, essentialism, and abstraction / by Jeffrey Strayer.
Philosophy of history and culture,
Philosophy of history and culture ;
Author:
Strayer, Jeffrey.
ebrary, Inc.
General Notes:
Includes bibliographical references (p. [367]-373) and index.
pt. 1. Preliminary issues relevant to essentialist abstraction -- pt. 2. On subjects and objects and works of art : general considerations and basic points of relevance to essentialist abstraction -- pt. 3. On subjects and objects and artistic complexes : the material of essentialism -- pt. 4. Identity and subjects, objects, and language : concluding remarks as a preamble to an essentialist investigation of the limits of abstraction.
Electronic reproduction. Palo Alto, Calif. : ebrary, 2013. Available via World Wide Web. Access may be limited to ebrary affiliated libraries.
Publisher:
Brill ; Extenza Turpin [distributor],
Publication Place:
Leiden : Biggleswade :
ISBN:
9789004157149 (hbk.)
900415714X (hbk.)
9789047419327 (e-book)
Subject:
Art, Abstract.
Art, Modern -- 20th century.
Abstraction.
Art -- Philosophy.
Electronic books.
Series:
Philosophy of history and culture, v. 25
Philosophy of history and culture ; v. 25.
Contents:
pt. 1. Preliminary issues relevant to essentialist abstraction -- pt. 2. On subjects and objects and works of art : general considerations and basic points of relevance to essentialist abstraction -- pt. 3. On subjects and objects and artistic complexes : the material of essentialism -- pt. 4. Identity and subjects, objects, and language : concluding remarks as a preamble to an essentialist investigation of the limits of abstraction.
Physical Description:
xviii, 388 p.
Electronic Location:
http://site.ebrary.com/lib/excellence/Doc?id=10461415
Publication Date:
2007.
Title:
Subset selection in regression / Alan Miller.
Monographs on statistics and applied probability ;
Author:
Miller, Alan J.
General Notes:
Includes bibliographical references (p. 223-234) and index.
Machine generated contents note: 1 Objectives -- 1.1 Prediction, explanation, elimination or what? -- 1.2 How many variables in the prediction formula? -- 1.3 Alternatives to using subsets -- 1.4 'Black box' use of best-subsets techniques -- 2 Least-squares computations -- 2.1 Using sums of squares and products matrices -- 2.2 Orthogonal reduction methods -- 2.3 Gauss-Jordan v. orthogonal reduction methods -- 2.4 Interpretation of projections -- Appendix A. Operation counts for all-subsets regression -- A.1 Garside's Gauss-Jordan algorithm -- A.2 Planar rotations and a Hamiltonian cycle -- A.3 Planar rotations and a binary sequence -- A.4 Fast planar rotations -- 3 Finding subsets which fit well -- 3.1 Objectives and limitations of this chapter -- 3.2 Forward selection -- 3.3 Efroymson's algorithm -- 3.4 Backward elimination -- 3.5 Sequential replacement algorithms -- 3.6 Replacing two variables at a time -- 3.7 Genierating all subsets -- 3.8 Using branch-and-bound techniques -- 3.9 Grouping variables -- 3.10 Ridge regression and other alternatives -- 3.11 The nonnegative garrote and the lasso -- 3.12 Some examples -- 3.13 Conclusions and recommendations -- Appendix A. An algorithm for the lasso -- 4 Hypothesis testing -- 4.1 Is there any information in the remaining variables? -- 4.2 Is one subset better than another? -- 4.2.1 Applications of Spj-tvoll's method -- 4.2.2 Using other confidence ellipsoids -- Appendix A.Spjotvoll's method - detailed description -- 5 When to stop? -- 5.1 What criterion should we use? -- 5.2 Prediction criteria -- 5.2.1 Mean squared errors of prediction (MSEP) -- 5.2.2 MSEP for the fixed model -- 5.2.3 MSEP for the random model -- 5.2.4 A simulation with random predictors -- 5.3 Cross-validation and the P SS statistic -- 5.4 Bootstrapping -- 5.5 Likelihood and information-based stopping rules -- 5.5.1 Minimum description length (MDL) -- Appendix A. Approximate equivaence of stppingules -- A.1 F-to-enter -- A.2 Adjusted R2 or Fisher's A-statistic -- A.3 Akaikesinformatibn criterion (AIC) -- 6 Estatmaion of regression eficients -- 6.1 Selection bias -- 6.2 Choice between two varies -- 6.3 Selection rduction -- 6.3.1 Monte C o et tionfias i f d lection -- 6.3.2 Shrinkage methods -- 6.3.3 Using the jack-knife -- 6.3.4 Independent; data sets ; -- 6.4 Conditional likiood estimations -- 6.5 Estimationofpopulation means -- 6.6 Estimating least-squares projections ; -- Appendix A. Changing projections to equate sums of squares -- 7 Bayesian mnethods -- 7.1 Bayesian introduction -- 7.2 'Spike and slab'prior -- 7.3 Normal prior for regression coefficients -- 7.4 Model averaging -- 7.5 Picking the best model -- 8 Conclusions and some recommendations -- References -- Index.
Publisher:
Chapman & Hall/CRC,
Publication Place:
Boca Raton :
ISBN:
1584881712 (acid-free paper)
Subject:
Regression analysis.
Least squares.
Series:
Monographs on statistics and applied probability ; 95
Edition:
2nd ed.
Contents:
Machine generated contents note: 1 Objectives -- 1.1 Prediction, explanation, elimination or what? -- 1.2 How many variables in the prediction formula? -- 1.3 Alternatives to using subsets -- 1.4 'Black box' use of best-subsets techniques -- 2 Least-squares computations -- 2.1 Using sums of squares and products matrices -- 2.2 Orthogonal reduction methods -- 2.3 Gauss-Jordan v. orthogonal reduction methods -- 2.4 Interpretation of projections -- Appendix A. Operation counts for all-subsets regression -- A.1 Garside's Gauss-Jordan algorithm -- A.2 Planar rotations and a Hamiltonian cycle -- A.3 Planar rotations and a binary sequence -- A.4 Fast planar rotations -- 3 Finding subsets which fit well -- 3.1 Objectives and limitations of this chapter -- 3.2 Forward selection -- 3.3 Efroymson's algorithm -- 3.4 Backward elimination -- 3.5 Sequential replacement algorithms -- 3.6 Replacing two variables at a time -- 3.7 Genierating all subsets -- 3.8 Using branch-and-bound techniques -- 3.9 Grouping variables -- 3.10 Ridge regression and other alternatives -- 3.11 The nonnegative garrote and the lasso -- 3.12 Some examples -- 3.13 Conclusions and recommendations -- Appendix A. An algorithm for the lasso -- 4 Hypothesis testing -- 4.1 Is there any information in the remaining variables? -- 4.2 Is one subset better than another? -- 4.2.1 Applications of Spj-tvoll's method -- 4.2.2 Using other confidence ellipsoids -- Appendix A.Spjotvoll's method - detailed description -- 5 When to stop? -- 5.1 What criterion should we use? -- 5.2 Prediction criteria -- 5.2.1 Mean squared errors of prediction (MSEP) -- 5.2.2 MSEP for the fixed model -- 5.2.3 MSEP for the random model -- 5.2.4 A simulation with random predictors -- 5.3 Cross-validation and the P SS statistic -- 5.4 Bootstrapping -- 5.5 Likelihood and information-based stopping rules -- 5.5.1 Minimum description length (MDL) -- Appendix A. Approximate equivaence of stppingules -- A.1 F-to-enter -- A.2 Adjusted R2 or Fisher's A-statistic -- A.3 Akaikesinformatibn criterion (AIC) -- 6 Estatmaion of regression eficients -- 6.1 Selection bias -- 6.2 Choice between two varies -- 6.3 Selection rduction -- 6.3.1 Monte C o et tionfias i f d lection -- 6.3.2 Shrinkage methods -- 6.3.3 Using the jack-knife -- 6.3.4 Independent; data sets ; -- 6.4 Conditional likiood estimations -- 6.5 Estimationofpopulation means -- 6.6 Estimating least-squares projections ; -- Appendix A. Changing projections to equate sums of squares -- 7 Bayesian mnethods -- 7.1 Bayesian introduction -- 7.2 'Spike and slab'prior -- 7.3 Normal prior for regression coefficients -- 7.4 Model averaging -- 7.5 Picking the best model -- 8 Conclusions and some recommendations -- References -- Index.
Physical Description:
xvii, 238 p. : ill. ;
Electronic Location:
http://www.loc.gov/catdir/toc/fy022/2002020214.html
Publication Date:
c2002.
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