02930nam 2200685 450 991045983200332120200520144314.00-8157-2635-X0-8157-2559-0(CKB)3710000000238057(EBL)1781845(SSID)ssj0001335540(PQKBManifestationID)11994110(PQKBTitleCode)TC0001335540(PQKBWorkID)11307060(PQKB)10328784(MiAaPQ)EBC1781845(OCoLC)890531076(MdBmJHUP)muse37688(Au-PeEL)EBL1781845(CaPaEBR)ebr10929309(CaONFJC)MIL642681(OCoLC)893898876(EXLCZ)99371000000023805720140916h20142014 uy 0engur|n|---|||||txtccrGeneration unbound drifting into sex and parenthood without marriage /Isabel V. SawhillWashington, District of Columbia :Brookings Institution Press,2014.©20141 online resource (227 p.)Includes index.1-322-11430-7 0-8157-2558-2 Includes bibliographical references and index.Front Cover; Inside Flap; Title Page; Copyright Information; Table of Contents; Preface; An Introduction; The End of Marriage?; Why Should We Worry?; A Growing Class Divide; Traditionalists and Village Builders; Childbearing by Design Not by Default; The Future: Less Marriage, Fewer Children?; Appendix; Notes; Index; Back CoverOver half of all births to young adults in the United States now occur outside of marriage, and many are unplanned. The result is increased poverty and inequality for children. The left argues for more social support for unmarried parents; the right argues for a return totraditional marriage.In Generation Unbound, Isabel V. Sawhill offers a third approach: change ""drifters"" into ""planners."" In a well-written and accessible survey of the impact of family structure on child well-being, Sawhill contrasts ""planners,"" who are delaying parenthood until after they marry, with ""drifters,"" whoUnmarried mothersUnited StatesUnmarried fathersUnited StatesYouthSexual behaviorUnited StatesFamily planningUnited StatesMarriageUnited StatesElectronic books.Unmarried mothersUnmarried fathersYouthSexual behaviorFamily planningMarriage306.874/32Sawhill Isabel V.302114MiAaPQMiAaPQMiAaPQBOOK9910459832003321Generation unbound2100210UNINA04846nam 2201225z- 450 991057687810332120220621(CKB)5720000000008394(oapen)https://directory.doabooks.org/handle/20.500.12854/84521(oapen)doab84521(EXLCZ)99572000000000839420202206d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierData Science and Knowledge DiscoveryBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (254 p.)3-0365-4316-3 3-0365-4315-5 Data Science (DS) is gaining significant importance in the decision process due to a mix of various areas, including Computer Science, Machine Learning, Math and Statistics, domain/business knowledge, software development, and traditional research. In the business field, DS's application allows using scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data to support the decision process. After collecting the data, it is crucial to discover the knowledge. In this step, Knowledge Discovery (KD) tasks are used to create knowledge from structured and unstructured sources (e.g., text, data, and images). The output needs to be in a readable and interpretable format. It must represent knowledge in a manner that facilitates inferencing. KD is applied in several areas, such as education, health, accounting, energy, and public administration. This book includes fourteen excellent articles which discuss this trending topic and present innovative solutions to show the importance of Data Science and Knowledge Discovery to researchers, managers, industry, society, and other communities. The chapters address several topics like Data mining, Deep Learning, Data Visualization and Analytics, Semantic data, Geospatial and Spatio-Temporal Data, Data Augmentation and Text Mining.Computer sciencebicsscInformation technology industriesbicsscactivity recognitionadaptation processArcGISartificial intelligenceattributionauthorshipautomationbig dataBig Databox-counting frameworkchatbotsclassificationcontent base image retrievalCOVID-19crisis reportingcustomer relationship management (CRM)dashboarddata analysisdata analyticsdata augmentationdata miningdata sciencedatabasesdecision systemsdeep featuresdeep learningdigital humanitiesdigital infrastructuresdistracted drivingdriving behaviordriving operation areae-commerceeconomic determinants of open dataESP32 microcontrollerfeature extractionforensic intelligencefractal dimensiongeoinformation technologygovernance and social institutionshumanitiesICTinformation systemsinterdisciplinary researchinternet of thingsioCOVID19journalistslinked open dataLoRaWANmachine learningmedia analyticsmedia criticismmultimedia document retrievaln/aneural networksnews mediaopen government dataprediction by partial matchingpublic healthrough setsrule based systemsSARS-CoV-2script Pythonsemantic information retrievalsmart homessocial sciencesspatio-temporalterritorial road networktext miningtextbook researchThe Things NetworkWeb IntelligenceWebGISComputer scienceInformation technology industriesPortela Filipeedt1268012Portela FilipeothBOOK9910576878103321Data Science and Knowledge Discovery3021749UNINA