Comparison Between Census Software Packages in the Context of Data Dissemination Prepared by Devinfo Support Group (DSG) and UN Statistics Division (DESA/UNSD)

Total Page:16

File Type:pdf, Size:1020Kb

Comparison Between Census Software Packages in the Context of Data Dissemination Prepared by Devinfo Support Group (DSG) and UN Statistics Division (DESA/UNSD) Comparison between Census software packages in the context of data dissemination Prepared by DevInfo Support Group (DSG) and UN Statistics Division (DESA/UNSD) For more information or comments please contact: [email protected] CsPro (Census and Survey Redatam (REtrieval of DATa for CensusInfo DevInfo* SPSS SAS Application Characteristics Processing System) small Areas by Microcomputer) License Owned by UN, distributed royalty-free to Owned by UN, distributed royalty-free to CSPro is in the public domain. It is Version free of charge for Download Properitery license Properitery license all end-users all end-users available at no cost and may be freely distributed. It is available for download at www.census.gov/ipc/www/cspro DATABASE MANAGEMENT Type of data Aggregated data. Aggregated data. Individual data. Individual data. Individual and aggregated data. Individual and aggregated data. Data processing Easily handles data disaggregated by Easily handles data disaggregated by CSPro lets you create, modify, and run Using Process module allows processing It allows entering primary data, define It lets you interact with your data using geographical area and subgroups. geographical area and subgroups. data entry, batch editing, and tabulation data with programs written in Redatam variables and perform statistical data integrated tools for data entry, applications command language or limited Assisstants processing computation, editing, and retrieval. Data consistency checks Yes, Database administration application Yes, Database administration application CSPro contains a common procedure Create module allows creating/editing Provides various data editing options Using integrated tools for editing and allows editing of indicator values. Does allows editing of indicator values. Does language to implement data entry control proprietary format R+SP databases from from within the system and also validation not facilitate consistency edits for not facilitate consistency edits for and edit rules ASCII or xBase format files externally microdata microdata On-line data entry Yes, through database administration Yes, through database administration No. It creates a stand-alone data entry No Yes, SPSS Data Entry builder makes data No application application environment entry easy. The data entry forms can be deployed online System user defined data/indicator Yes, based on database template Yes, based on database template Data is defined as cases (questionnaires), Microdata defined in proprietary format One or more variables can be used to Yes methodology methodology variables are defined to represents the can be used to generate data/indicator define indicators cases, variables are selected to tabulate Metadata storage Yes with admin-defined tags. In Yes with admin-defined tags. In DevInfo All data is recorded as text defined by All data is recorded as text defined by Metadata is stored seperately as primary Additional module required: SAS Metadata CensusInfo Admin application Admin application variables. Metadata can also be recorded variables. Metadata can also be recorded data Server as text as text Common database elements across Yes, supports SDMX-compliant registry to Yes, supports SDMX-compliant registry to Data defined as variables and cases are Data is organized through entities/levels The structure of the database including Via additional module SAS Enterprise Data databases normalize database dimensions. normalize database dimensions. DevInfo database specific and entity elements. its elements are defined by user. Hence Integration Server CensusInfo Registry allows for importable Registry allows for importable global the database elements across databases global database elements database elements may vary. DATA PRESENATION Tables Yes, user-defined content for rows and Yes, user-defined content for rows and Yes, using table viewer view the results of Yes Various tables can be generated based on Yes columns. Instant table preview as well as columns. Instant table preview as well as tabulations. Tables can be saved as primary data including frequency, cross- customizable table editing customizable table editing HTML, RTF, TAB delimited formats tab, general, custom, multiple response features,Includes frequency tables, cross- features,Includes frequency tables, cross- etc. tabs and histograms tabs and histograms Graphs Yes, editing features available for Yes, editing features available for No Yes Various graphs can be generated based Yes customization. Includes pyramid charts customization. Includes pyramid charts on primary data including Bar, Line, Pie, as well as standard bar, column, line and as well as standard bar, column, line and Area, Scatter etc. pie charts pie charts Maps Yes, basic map editing features allow Yes, basic map editing features allow Yes, Using map viewer generate a Yes No, presenting data on Geo-spatial maps No, presenting data on Geo-spatial maps is users to change labelling, colours, legend users to change labelling, colours, legend thematic map of selected variable. Allows is not available. not available. Only provides a bridge for and display multiple themes. Contains and display multiple themes. Contains editing colors, titles and legends. Save the ESRI features including drill-down, time series features including drill-down, time series map as .GIF format maps, raster maps, etc. maps, raster maps, etc. Custom report builder Yes with user-defined content. Formatted both User defined and Advance Reports Tabulation is used to tabulate selected Using block programming or assisstants Using interactive table preview builder to Yes, programming using SAS Enterprise tables can be saved as report layouts options are available variables with values and weights. formatted tabulations can be created create customized reports guide Tabulations can be formatted for viewing and printing Allows creation of interactive web- Yes, including searching gallery, profiles Yes, including searching gallery, profiles No, needs programming or application No, needs programming or application No, needs programming or application No, needs programming or application enabled animated presentation using and data visualizers. di Book, di Video and data visualizers. di Book, di Video development development development development database and di Visualizer all allow for animated and di Visualizer all allow for animated data display and visualization data display and visualization Page 1 CsPro (Census and Survey Redatam (REtrieval of DATa for CensusInfo DevInfo* SPSS SAS Application Characteristics Processing System) small Areas by Microcomputer) Interactive representation of data on Yes. Tables can easily be saved to a Yes. Tables can easily be saved to a No No No, needs programming or application No CD-ROM Gallery Gallery development Interactive representation of data on Yes (cross-browser-compatibility). Tables Yes (cross-browser-compatibility). Tables No Using WebServer based on Redatam No, needs programming or application No the web can easily be saved to an online Gallery, can easily be saved to an online Gallery, statistical engine is used to request development database can be uploaded online database can be uploaded online information on intranet, extranet or the Internet DATA IMPORT CAPABILITY SPSS Yes, from SPO, CSV, XLS. Via specialized Yes, from SPO, CSV, XLS. Via specialized No Files should be converted into .DBF or - yes, .sav file data exchange utility data exchange utility ASCII to use for database creation SAS Yes, using standardized data format. Via Yes, using standardized data format. Via No Files should be converted into .DBF or Yes - specialized data exchange utility specialized data exchange utility ASCII to use for database creation CsPro Yes, from HTML. Via specialized data Yes, from HTML. Via specialized data - Files should be converted into .DBF or .CSV files only No exchange utility exchange utility ASCII to use for database creation Microsoft Excel Yes, using standardized data format. New Yes, using standardized data format. No Files should be converted into .DBF or Yes Yes utility allows for seamless import of CSV ASCII to use for database creation data into CensusInfo Redatam Yes Yes No - .CSV files only No DATA EXPORT CAPABILITY SPSS Yes, using standardized data format Yes, using standardized data format Yes No - Yes, to .sav file SAS Yes, using standardized data format Yes, using standardized data format Yes No Yes - PDF Yes Yes No No Yes Yes Microsoft Excel Yes, using standardized data format Yes, using standardized data format Yes, .CSV files No Yes Yes PUBLISHING UTILITIES Standard Profiles Yes, using di profiles No Multi-Media di Books, di Video, side bar, PPT output di Books, di Video, side bar, PPT output No Print posters, brochures posters, brochures No KNOWLEDGE AND SUPPORT Help desk availability Yes 24x7 in English, French and Spanish Yes 24x7 in English, French and Spanish Q&A center is available on US Census Not available Yes, only for registered users (clients with Yes, online knowledgebase available Bureau web site licenses) Expertise required to develop Basic desktop computer literacy (non-IT Basic desktop computer literacy (non-IT Database management, programming Database management, programming Database management and statistical Database management and statistical database specialist) with e-learning courses specialist) with e-learning courses expertise are required expertise are required expertise required expertise required available and extensive technical available and extensive
Recommended publications
  • ICT in the Kosovo National Statistical System - Baseline Review and Recommendations for Development
    UNDP Kosovo UNKT Technical assistance to the IT department of the Kosovo Agency of Statistics (KAS) Technical analysis of information technology in the national statistical system ICT in the Kosovo National Statistical System - Baseline review and Recommendations for development April 2013 by Arij Dekker, Consultant in statistical data processing and management [email protected] ICT in the Kosovo National Statistical System - Baseline review and Recommendations for development 1 Contents List of Acronyms ...................................................................................................................................... 3 Executive Summary ................................................................................................................................. 5 Chapter 1. Introduction ..................................................................................................................... 7 Chapter 2. Methods of information gathering .................................................................................... 9 2.1 Description of interview partners and question clusters ........................................................... 9 2.2 Other information sources ..................................................................................................... 12 Chapter 3. The present state of ICT in the Kosovo national statistical system ................................... 14 3.1 Summary of information gathered from the interviews .........................................................
    [Show full text]
  • On New Data Sources for the Production of Official Statistics
    On new data sources for the production of official statistics David Salgado1,2 and Bogdan Oancea3 1Dept. Methodology and Development of Statistical Production, Statistics Spain (INE), Spain 2Dept. Statistics and Operations Research, Complutense University of Madrid, Spain 3Dept. Business Administration, University of Bucharest, Romania February 7, 2020 Abstract In the past years we have witnessed the rise of new data sources for the potential production of official statistics, which, by and large, can be classified as survey, administrative, and digital data. Apart from the differences in their generation and collection, we claim that their lack of statistical metadata, their economic value, and their lack of ownership by data holders pose several entangled challenges lurking the incorporation of new data into the routinely production of official statistics. We argue that every challenge must be duly overcome in the international community to bring new statistical products based on these sources. These challenges can be naturally classified into different entangled issues regarding access to data, statistical methodology, quality, information technologies, and management. We identify the most relevant to be necessarily tackled before new data sources can be definitively considered fully incorporated into the production of official statistics. Contents 1 Introduction 2 2 Data: survey, administrative, digital 3 2.1 Somedefinitions ..................................... .... 3 2.2 Statisticalmetadata ................................ ....... 4 2.3 Economicvalue.....................................
    [Show full text]
  • Software Developer
    PINKY MONONYANE SOFTWARE DEVELOPER https://www.pinkymononyane.info PROFILE English, Sotho, Tsonga, Tswana, Venda, N. Sotho 33 Years old, Black Female with no disability I have 9 years’ programming experience with professional skills that could fill a South African Citizen, ID Number: 871020 0461 08 1 bucket 10 times over, with few honorable mentions such as HTML, B – Light Vehicles 750kg to 3500kg CSS3, Python (I have more than 5 years Single of Experience in Django framework. I have been developing small to medium projects even before my latest position ADDRESS & CONTACT INFO at BCM), Php and Java Script with keen attention to details, Phone Number: +27 78 968 2362 plus a well dynamic personality that appeals to most that I have had a Home Address Recent / Previous pleasure working/collaborating with. Work Address 684 Lievaart Point to note... Challenges is what I live, Street 145 Second Street breath and seek, for it's in those that's Proclamation Hill Parkmore where personal growth is found. Pretoria, Gauteng Sandton 0183 2052 Furthermore I constantly look for more knowledge related to my field; as such I Email Address: [email protected] have enrolled in Computer Science BSc Degree at UNISA, as they say knowledge CAREER STATUS is like an endless river flow. Can't have 2013-2019 Data Developer: 7 Years’ Experience enough: P. Languages:- So when I'm nowhere to be found rest Python, CSpro, SSRS, SQL Server, R-Statistics, SAS, Server assured you can find me programming a interaction, security and management under various software on my friendly computer or out environments (Linux, Windows and Windows server) on a hunt for further knowledge and if not I’m probably out travelling and 2020-2020 Software Developer: 9 Months Formal Experience spending time with my loved ones.
    [Show full text]
  • Research; *Electronic Data Processing; Information Processing; Information Systems; *Manpower Utilization; *Personnel Data; Personnel Management; Questionnaires
    DOCUMENT RESUME ED 084 382 CE 000 533 AUTHOR Bayhylle, J. E., Ed.; Hersleb, A., Ed. TITLE The Development of Electronic Data Processing in Manpower Areas; A Comparative Study of Personnel Information Systems and their Implications in Six European Countries. INSTITUTION Organisation for Economic Cooperation and Development, Paris (France) . PUB DATE 73 NOTE 366p. AVAILABLE FROMOECD Publications Center, Suite 1207, 1750 Pennsylvania Ave., N.W., Washington, DC 20006 ($8.50) EDRS PRICE MF-$0.65 HC- $13.16 DESCRIPTORS Case Studies; Data Bases; Data Processing; *Ecqnomic .Research; *Electronic Data Processing; Information Processing; Information Systems; *Manpower Utilization; *Personnel Data; Personnel Management; Questionnaires ABSTRACT Usable data about human resources in the ecqnqmy are fundamentally important, but present methods of obtaining, organizing, and using such information are increasingly unsatisfactory. The application of electronic data processing to manpower and social concerns should be improved and increased. This could stimulate closer exchange between government, institutions, and business enterprises in the collection and dissemination of manpower data. The first phase of the study was a broad-scope questionnaire of 38 companies in Austria, France, Germany, Great Britain, Sweden, and Switzerland which have developed, or are planning to develop, computer-based personnel information, systems. The second phase consisted of depth study of eight of the companies. Case study investigations were concerned with the content and function of the system and with the administrative and personnel consequences of the introduction of such systems. A set of key.points which emerged from the study is developed. A model demonstrates the need for coordination to increase communication vertically and horizontally.
    [Show full text]
  • Applied Accounting and Automatic Data-Processing Systems." (1962)
    Louisiana State University LSU Digital Commons LSU Historical Dissertations and Theses Graduate School 1962 Applied Accounting and Automatic Data- Processing Systems. William Elwood Swyers Louisiana State University and Agricultural & Mechanical College Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_disstheses Recommended Citation Swyers, William Elwood, "Applied Accounting and Automatic Data-Processing Systems." (1962). LSU Historical Dissertations and Theses. 745. https://digitalcommons.lsu.edu/gradschool_disstheses/745 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Historical Dissertations and Theses by an authorized administrator of LSU Digital Commons. For more information, please contact [email protected]. This dissertation has been 62—3671 microfilmed exactly as received SWYERS, William Elwood, 1922- APPLIED ACCOUNTING AND AUTOMATIC DATA-PRO CESSING SYSTEMS. Louisiana State University, Ph.D., 1962 Economics, commerce—business University Microfilms, Inc., Ann Arbor, Michigan APPLIED ACCOUNTING AND AUTOMATIC DATA-PROCESSING SYSTEMS A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Accounting by William Eiu<Swyers B.S., Centenary College, 1942 M.B.A. t Louisiana State University, 1948 January, 1962 ACKNOWLEDGMENTS The writer wishes to express appreciation to Dr. Robert H. Van Voorhis, Professor of Accounting, Louisiana State University, for his valuable assistance and guidance in the preparation of this dissertation. The writer wishes to acknowledge, also, the helpful suggestions made by Dr. W. D. Ross, Dean of the College of Business Administration, Dr.
    [Show full text]
  • STANDARDS and GUIDELINES for STATISTICAL SURVEYS September 2006
    OFFICE OF MANAGEMENT AND BUDGET STANDARDS AND GUIDELINES FOR STATISTICAL SURVEYS September 2006 Table of Contents LIST OF STANDARDS FOR STATISTICAL SURVEYS ....................................................... i INTRODUCTION......................................................................................................................... 1 SECTION 1 DEVELOPMENT OF CONCEPTS, METHODS, AND DESIGN .................. 5 Section 1.1 Survey Planning..................................................................................................... 5 Section 1.2 Survey Design........................................................................................................ 7 Section 1.3 Survey Response Rates.......................................................................................... 8 Section 1.4 Pretesting Survey Systems..................................................................................... 9 SECTION 2 COLLECTION OF DATA................................................................................... 9 Section 2.1 Developing Sampling Frames................................................................................ 9 Section 2.2 Required Notifications to Potential Survey Respondents.................................... 10 Section 2.3 Data Collection Methodology.............................................................................. 11 SECTION 3 PROCESSING AND EDITING OF DATA...................................................... 13 Section 3.1 Data Editing ........................................................................................................
    [Show full text]
  • What Can a Computer Do? a Computer Is an Electronic Device
    You have learnt various methods of data processing and representation that you can use to analyse the geographical phenomena in the preceding chapters. You must have observed that these methods are time consuming and tedious. Have you ever thought of a method of data processing and their graphical representation that can save time and improve efficiency? If you have used a computer for word processing, then you must have noticed that the computer is more versatile as it facilitates the onscreen editing of the text, copy and move it from one place to another, or even delete the unwanted text. Similarly, the computer may also be used for data processing, preparation of diagrams/graphs and drawing of maps, provided you have an access to the related application software. In other words, a computer can be used for a wide range of applications. It must, however, be clearly understood that a computer carries out the instructions it receives from the users. In other words, it cannot perform any function on its own. In the present chapter, we will discuss the use of computers in data processing and mapping. What can a Computer do? A computer is an electronic device. It consists of various sub-systems, like memory, micro-processor, input system and output system. All these sub- systems work together to make it an integrated system. It is an extremely powerful device, which is apt to have an important effect on the systems of data processing, mapping and analysis. A computer is a fast and a versatile machine that can perform simple arithmetic operations, such as, addition, subtraction, multiplication and division, and can also solve complex mathematical, formulae.
    [Show full text]
  • 14. Data Processing, Evaluation, and Analysis
    In: R.P. Higgins & H. 'I'hi,el (Eds.) Introduction to the study of Meiofauna. ~vashington and London', Sml't11sonian Institution Press, 1988, pp. 197-231. Communication no. 418 Delta Institute for Hydrobiological Research, Vierstraat 28 Yerseke, The Netherlands. 14. Data Processing, Evaluation, and Analysis Carlo Heip, Peter M.J. Herman, and Karlien Soetaert This chapter aims at introducing a number of and evenness indices in part 5, and temporal pattern methods for the post-hoc interpretation of field in part 6. Each of these topics is discussed data. In many ecological studies a vast amount of independently and each topic can be consulted information is gathered, often in the form of without having to read the others. For this reason, numbers of different species. The processing of these each part will be preceded by its own introduction. data is possible on different levels of sophistication and requires the use of tools varying from pencil Part 1. Data Storage and Retrieval and paper to a mini computer. However, some "number crunching" is nearly always necessary and The existence of many software packages, useful with the increasing availability and decreasing prices in ecology, will not be unknown to most ecologists. ,of the personal computer, even in developing Many computer centers provide their users with countries, there is little point in avoiding the more routines which facilitate the input, transformation and advanced statistical techniques. There is also a more appropriate output of the data, and the linking of fundamental reason: ecological data are often of a available software packages into one flexible system.
    [Show full text]
  • Course Title: Fundermentals of Data Processing
    NATIONAL OPEN UNIVERSITY OF NIGERIA SCHOOL OF EDUCATION COURSE CODE: BED 212: COURSE TITLE: FUNDERMENTALS OF DATA PROCESSING BED 212: FUNDERMENTALS OF DATA PROCESSING COURSE DEVELOPER & WRITER: DR. OPATEYE JOHNSON AYODELE School of Education National Open University of Nigeria 14/16 Ahmadu Bello Way, Victoria Island Lagos. Nigeria. COURSE CORDINATOR: DR. INEGBEDION, JULIET O. School of Education National Open University of Nigeria 14/16 Ahmadu Bello Way, Victoria Island Lagos. Nigeria. INTRODUCTION BED 212: FUNDERMENTALS OF DATA PROCESSING This course is designed to equip the students with knowledge of the data processing in technical and vocational education (TVE) especially Business Education research. WHAT YOU WILL LEARN You will learn the components of data processing, hardware and software components, file management and organization in Business Education- based data. It will also interest you to learn about basics of research, approaches and designs with data gathering techniques. Relevant statistical tools you can use to analyse your data would be across and how to write your research reports. COURSE AIMS This course aims at producing competent business educators who will be versed in organizational and research data processing in order to foster time and effective information that will be used in decision making. In order to enable you meet the above aims, modules constituting of units have been produced for your study. Apart from meeting the aims of the course as a whole, each course unit consists of learning objectives which are intended to ensure your learning effectiveness. COURSE OBJECTIVES The course objectives are meant to enable you achieve/acquire the following: 1) Gain in-depth knowledge of data processing and its functions in business organisations and educational settings.
    [Show full text]
  • Hyperspectral Data Processing. Algorithm Design and Analysis
    Brochure More information from http://www.researchandmarkets.com/reports/2293144/ Hyperspectral Data Processing. Algorithm Design and Analysis Description: Hyperspectral Data Processing: Algorithm Design and Analysis is a culmination of the research conducted in the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County. Specifically, it treats hyperspectral image processing and hyperspectral signal processing as separate subjects in two different categories. Most materials covered in this book can be used in conjunction with the author’s first book, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, without much overlap. Many results in this book are either new or have not been explored, presented, or published in the public domain. These include various aspects of endmember extraction, unsupervised linear spectral mixture analysis, hyperspectral information compression, hyperspectral signal coding and characterization, as well as applications to conceal target detection, multispectral imaging, and magnetic resonance imaging. Hyperspectral Data Processing contains eight major sections: - Part I: provides fundamentals of hyperspectral data processing - Part II: offers various algorithm designs for endmember extraction - Part III: derives theory for supervised linear spectral mixture analysis - Part IV: designs unsupervised methods for hyperspectral image analysis - Part V: explores new concepts on hyperspectral information compression - Parts VI & VII: develops
    [Show full text]
  • Saidou Hamadou
    SAIDOU HAMADOU Contact address: P.O.Box : 707 Yaoundé (Cameroon) Telephone: Cameroon : (237) 677 71 94 98 / 697 42 42 32 Email: [email protected] [email protected] Summary Over 11 years of experience in managing data, conducting health and/or demographic surveys in many countries in Central and West Africa Over 08 years of experiences in implementing and evaluating result-based financing in Cameroon, Burkina-Faso, Liberia, Republic of Congo, Democratic Republic of Congo, Chad, Djibouti and Haïti ; 03 years of experiences with Service Delivery Indicators (SDI) surveys Member of many research projects in Africa and in the World Fluent in French and speaks enough English Education University of Paris-Dauphine (FRANCE) 2018 PhD dissertation : „Poverty, Malaria and Health System Reforms in Africa: Three Studies Applied in Cameroon’ Doctoral advisors: Pr. Sandrine MESPLE-SOMPS and Dr. Anne-Sophie ROBILLIARD Institute for Training and Demographic Research (IFORD)(CAMEROUN) 2007-2009 Professional master in Demography, Master‟s Thesis: Dynamics of the relationship between standard of living of households and diarrhea- related morbidity in children of less than three years in Cameroon University of YAOUNDÉ I (CAMEROUN) 2005-2006 Master's degree in computer science - Option: Calculation scientific, Master‟s degree thesis: The securing of data circulation in a local network of enterprise by the CRYPTOGRAPHY University of NGAOUNDÉRÉ (CAMEROUN) 2004-2005 Bachelor of science and technical information (STI) - Option: Calculation scientific,
    [Show full text]
  • Cit 213 Course Title: Elementary Data Processing
    NATIONAL OP EN UNIVERSITY OF NIGERIA SCHOOL OF SCIENCE AND TECHNOLOGY COURSE CODE: CIT 213 COURSE TITLE: ELEMENTARY DATA PROCESSING CO URSE GUIDE CIT 213 ELEMENTARY DATA PROCESSING Course Developer Dr. Ikhu-Omoregbe N. A. Course Editor Course Co-ordinator Afolorunso, A. A. National Open University of Nigeria Lagos. NATIONAL OPEN UNIVERSITY OF NIGERIA National Open University of Nigeria Headquarters 14/16 Ahmadu Bello Way Victoria Island Lagos Abuja Annex 245 Samuel Adesujo Ademulegun Street Central Business District Opposite Arewa Suites Abuja e-mail: [email protected] URL: www.nou.edu.ng National Open University of Nigeria 2008 First Printed 2008 ISBN All Rights Reserved Printed by .. For National Open University of Nigeria TABLE OF CONTENTS PAGE Introduction.............................................................................. 1 - 2 What you will learn in this Course..................................... 2 Course Aims............................................................................... 2 Course Objectives...................................................................... 2 3 Working through this Course.................................................... 3 Course Materials...........................................................................3 Study Units ............................................................................... 3 - 4 Textbooks and References ........................................................ 4 - 5 Assignment File.......................................................................
    [Show full text]