LEADER 04053nam 2200697Ia 450 001 9910784012503321 005 20230721025428.0 010 $a1-280-70538-8 010 $a9786610705382 010 $a1-85359-925-5 024 7 $a10.21832/9781853599255 035 $a(CKB)1000000000337010 035 $a(EBL)278981 035 $a(OCoLC)560208513 035 $a(SSID)ssj0000139932 035 $a(PQKBManifestationID)11147755 035 $a(PQKBTitleCode)TC0000139932 035 $a(PQKBWorkID)10028269 035 $a(PQKB)11378481 035 $a(MiAaPQ)EBC278981 035 $a(DE-B1597)513652 035 $a(OCoLC)84738258 035 $a(DE-B1597)9781853599255 035 $a(Au-PeEL)EBL278981 035 $a(CaPaEBR)ebr10153077 035 $a(CaONFJC)MIL70538 035 $a(EXLCZ)991000000000337010 100 $a20060428d2007 uy 0 101 0 $aeng 135 $aurnn#---|u||u 181 $ctxt 182 $cc 183 $acr 200 00$aDisinventing and reconstituting languages$b[electronic resource] /$fedited by Sinfree Makoni and Alastair Pennycook 210 $aClevedon $cMultilingual Matters$d2007 215 $a1 online resource (265 p.) 225 1 $aBilingual education and bilingualism 300 $aDescription based upon print version of record. 311 0 $a1-85359-923-9 311 0 $a1-85359-924-7 320 $aIncludes bibliographical references and index. 327 $tFront matter --$tContents --$tThe Contributors --$tForeword --$tChapter 1. Disinventing and Reconstituting Languages --$tChapter 2. Then There were Languages: Bahasa Indonesia was One Among Many --$tChapter 3. Critical Historiography: Does Language Planning in Africa Need a Construct of Language as Part of its Theoretical Apparatus? --$tChapter 4. The Myth of English as an International Language --$tChapter 5. Beyond ?Language?: Linguistic Imperialism, Sign Languages and Linguistic Anthropology --$tChapter 6. Entering a Culture Quietly: Writing and Cultural Survival in Indigenous Education in Brazil --$tChapter 7. A Linguistics of Communicative Activity --$tChapter 8. (Dis)inventing Discourse: Examples from Black Culture and Hiphop Rap/ Discourse --$tChapter 9 .Educational Materials Reflecting Heteroglossia: Disinventing Ethnolinguistic Differences in Bosnia- Herzegovina --$tChapter 10. After Disinvention: Possibilities for Communication, Community and Competence --$tIndex 330 $aThis book questions assumptions about the nature of language and how language is conceptualized. Looking at diverse contexts from sign languages in Indonesia to literacy practices in Brazil, from hip-hop in the US to education in Bosnia and Herzegovina, this book forcefully argues that a critique of common linguistic and metalinguistic suppositions is not only a conceptual but also a sociopolitical necessity. Just as many notions of language are highly suspect, so too are many related concepts premised on a notion of discrete languages, such as language rights, mother tongues, multilingualism, or code-switching. Definitions of language in language policies, education and assessment have material and often harmful consequences for people. Unless we actively engage with the history of invention of languages in order to radically change and reconstitute the ways in which languages are taught and conceptualized, language studies will not be able to improve the social welfare of language users. 410 0$aBilingual education and bilingualism. 606 $aLanguage and languages 606 $aSemantics 610 $alanguage policy. 610 $alanguages. 610 $alinguistics. 615 0$aLanguage and languages. 615 0$aSemantics. 676 $a400 701 $aMakoni$b Sinfree$01543567 701 $aPennycook$b Alastair$f1957-$0626945 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910784012503321 996 $aDisinventing and reconstituting languages$93797097 997 $aUNINA LEADER 04815nam 22006615 450 001 9910484512003321 005 20251116225307.0 010 $a981-15-2035-6 024 7 $a10.1007/978-981-15-2035-8 035 $a(CKB)4100000010480211 035 $a(DE-He213)978-981-15-2035-8 035 $a(MiAaPQ)EBC6112508 035 $a(PPN)242977839 035 $a(EXLCZ)994100000010480211 100 $a20200203d2020 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aQuantitative Economics with R $eA Data Science Approach /$fby Vikram Dayal 205 $a1st ed. 2020. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2020. 215 $a1 online resource (XV, 326 p. 300 illus., 89 illus. in color.) 311 08$a981-15-2034-8 327 $aCh 1 Introduction -- Ch 2 R and RStudio -- Ch 3 Getting data into R -- Ch 4 Wrangling and graphing data -- Ch 5 Functions -- Ch 6 Matrices -- Ch 7 Probability and statistical inference -- Ch 8 Causal inference -- Ch 9 Solow model and basic facts of growth -- Ch 10 Causal inference for growth -- Ch 11 Graphing and simulating basic time series -- Ch 12 Simple examples: forecasting and causal inference -- Ch 13 Generalized additive models -- Ch 14 Tree models. 330 $aThis book provides a contemporary treatment of quantitative economics, with a focus on data science. The book introduces the reader to R and RStudio, and uses expert Hadley Wickham?s tidyverse package for different parts of the data analysis workflow. After a gentle introduction to R code, the reader?s R skills are gradually honed, with the help of ?your turn? exercises. At the heart of data science is data, and the book equips the reader to import and wrangle data, (including network data). Very early on, the reader will begin using the popular ggplot2 package for visualizing data, even making basic maps. The use of R in understanding functions, simulating difference equations, and carrying out matrix operations is also covered. The book uses Monte Carlo simulation to understand probability and statistical inference, and the bootstrapis introduced. Causal inference is illuminated using simulation, data graphs, and R code for applications with real economic examples, covering experiments, matching, regression discontinuity, difference-in-difference, and instrumental variables. The interplay of growth related data and models is presented, before the book introduces the reader to time series data analysis with graphs, simulation, and examples. Lastly, two computationally intensive methods?generalized additive models and random forests (an important and versatile machine learning method)?are introduced intuitively with applications. The book will be of great interest to economists?students, teachers, and researchers alike?who want to learn R. It will help economics students gain an intuitive appreciation of appliedeconomics and enjoy engaging with the material actively, while also equipping them with key data science skills. 606 $aGame theory 606 $aEconomics 606 $aStatistics 606 $aComputer simulation 606 $aSociology?Research 606 $aR (Computer program language) 606 $aGame Theory, Economics, Social and Behav. Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/M13011 606 $aEconomic Theory/Quantitative Economics/Mathematical Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/W29000 606 $aStatistics for Business, Management, Economics, Finance, Insurance$3https://scigraph.springernature.com/ontologies/product-market-codes/S17010 606 $aSimulation and Modeling$3https://scigraph.springernature.com/ontologies/product-market-codes/I19000 606 $aResearch Methodology$3https://scigraph.springernature.com/ontologies/product-market-codes/X22190 615 0$aGame theory. 615 0$aEconomics. 615 0$aStatistics. 615 0$aComputer simulation. 615 0$aSociology?Research. 615 0$aR (Computer program language) 615 14$aGame Theory, Economics, Social and Behav. Sciences. 615 24$aEconomic Theory/Quantitative Economics/Mathematical Methods. 615 24$aStatistics for Business, Management, Economics, Finance, Insurance. 615 24$aSimulation and Modeling. 615 24$aResearch Methodology. 676 $a330.028563 700 $aDayal$b Vikram$4aut$4http://id.loc.gov/vocabulary/relators/aut$0872311 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484512003321 996 $aQuantitative Economics with R$91947554 997 $aUNINA