Quality of Working Life Module 1972-2014: Cumulative Codebook

Total Page:16

File Type:pdf, Size:1020Kb

Quality of Working Life Module 1972-2014: Cumulative Codebook GENERAL SOCIAL SURVEYS – QUALITY OF WORKING LIFE MODULE 1972-2014: CUMULATIVE CODEBOOK JUNE 2017 ii TABLE OF CONTENTS Introduction ....................................................................................................................................................................... iii Index to Data Set .............................................................................................................................................................. 1 1972-2014 Surveys Quality of Working Life Variables and Other Variables of Interest .......................................... 13 Appendix I: Variables by Year ..................................................................................................................................... 281 iii INTRODUCTION In 2000, the National Institute of Occupational Safety and Health (NIOSH) entered into an interagency agreement with the National Science Foundation to add a special module assessing the quality of work life in America to the 2002 General Social Survey. The General Social Survey is a biennial, nationally representative, personal interview survey of U.S. households conducted by the National Opinion Research Center and mainly funded by the National Science Foundation. Using a small group process with internal and external expert teams, NIOSH selected 76 questions dealing with a wide assortment of work organization issues. These include (but are not limited to) hours of work, workload, worker autonomy, layoffs and job security, job satisfaction/stress, and worker well-being. Half of the questions in the Quality of Working Life module were taken directly from the 1977 Quality of Employment Survey, allowing comparisons of worker responses over a 25-year period. The primary goals of the Quality of Working Life module are to measure how work life and the work experience have changed since the earlier Quality of Employment Surveys and to establish benchmarks for future surveys. Secondary goals include measuring the relationship between job/organizational characteristics and worker health and safety and identifying targets for health and safety preventive interventions. DATA The General Social Surveys have been conducted during February, March, and April of 1972, 1973, 1974, 1975, 1976, 1977, 1978, 1980, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1993, 1994, 1996, 1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, and 2014. For the Quality of Working Life Dataset, only respondents who were currently working full-time, part-time, or temporarily not at work were eligible for inclusion. This was measured using the GSS variable WRKSTAT. There are a total of 36,805 completed interviews (909 in 1972, 816 in 1973, 789 in 1974, 793 in 1975, 778 in 1976, 921 in 1977, 894 in 1978, 859 in 1980, 1,065 in 1982, 945 in 1983, 913 in 1984, 951 in 1985, 875 in 1986, 1,154 in 1987, 925 in 1988, 954 in 1989, 877 in 1990, 912 in 1991, 1,009 in 1993, 1,969 in 1994, 2,003 in 1996, 1,918 in 1998, 1,890 in 2000, 1,796 in 2002, 1,866 in 2004, 2,852 in 2006, 1,267 in 2008, 1,184 in 2010, 1,178 in 2012, and 1,543 in 2014). Each survey from 1972 to 2004 was an independently drawn sample of English-speaking persons 18 years of age or over, living in non-institutional arrangements within the United States. Starting in 2006 Spanish-speakers were added to the target population. Block quota sampling was used in 1972, 1973, and 1974 surveys and for half of the 1975 and 1976 surveys. Full probability sampling was employed in half of the 1975 and 1976 surveys and the 1977, 1978, 1980, 1982-1991, 1993-1998, 2000, 2002, 2004, 2006, 2008, 2010, 2012, and 2014 surveys. Also, the 2004, 2006, 2008, 2010, 2012 and 2014 surveys had sub-sampled non-respondents (see Appendix A of the GSS Cumulative Codebook for documentation). The data from the interviews were processed according to standard NORC procedures. This cumulative data set merges all 4 rounds of the Quality of Working Life module, as well as other variables of interest from 1972-2014. Each year can be taken as a subfile, although only 2002, 2006, 2010 and 2014 contain the complete Quality of Working Life variables. This simplifies the use of the QWL for both trend analysis and pooling. This data set is derived from the GSS Cumulative Datafile, and thus contains several items which are not asked as part of the questionnaire but instead created in the production of the datafile. Additionally, this datafile contains several items never before available, recodes specified by NIOSH and created by NORC staff. To facilitate the use of the codebook, several terms must be explained. The abbreviation "R," which appears throughout the text and appendices, stands for "respondent." The format which we have used in the text of the codebook is as follows: iv The format includes the question exactly as it appears in the questionnaire. For those few questions that were recoded, the symbol [RECODE] appears immediately after the question. "[VAR: HEALTH]" refers to the variable name. A mnemonic was assigned to each question to promote standardization in the use of General Social Survey variable names and also to meet the historical eight character limitation imposed by some computer software systems (e.g., SPSS). Under the heading "RESPONSE," all possible answers to the questions are listed. The questionnaire contains three alternate forms of response as follows: (1) the answers were read to the respondent (if they were included in the question); (2) answers were presented to the respondent on a card (indicated by interviewer instructions); or (3) answers were marked by the interviewer to best correspond to the answer of the respondent (also indicated by interviewer instructions). The term "PUNCH" represents the code or numerical value which was assigned to each response. These are the numbers that the user will find punched in the columns. The frequency of occurrence of each of the punch values appears in the next four columns. The combined marginals across the surveys are in the last column headed "ALL." In most cases, the marginal distributions for all punches are given in the text. For a small number of variables--the two-or-more-column variables--frequencies or marginal distributions appear in the appendices. Responses are mutually exclusive (i.e., only one code can appear for each respondent for each question). The first column under "YEAR," 1972-1982, gives the combined totals for the 1972-1982 cross-sections. In the second column, 1982B, the counts for the 1982 black oversample appear. Blacks who were part of the regular 1982 sample are not part of these figures. The third column, 1983-1987, gives the combined totals for 1983-1987. The fourth column, 1987B, contains the counts for the 1987 black oversample. The fifth column, 1988-1991, gives the combined totals for 1988-1991. The sixth column, 1993-98, gives the combined totals for 1993-98. The seventh column, 2000, contains the counts for the 2000 survey. The eighth column, 2002, contains the counts for the 2002 survey. The ninth column, 2004, contains the counts for the 2004 survey. The tenth column, 2006, contains the counts for the 2006 survey. The eleventh column, 2008, contains the counts for the 2008 survey. The twelfth column, 2010, contains the counts for the 2010 survey. The thirteenth column, 2012, contains the counts for the 2012 survey. The fourteenth column, 2014, contains the counts for the 2014 survey. Lastly, the fifteenth column, ALL, contains the total for the preceding fourteen columns. For a discussion of the use of the black oversample see Appendix A of the GSS Cumulative Codebook. To determine what years or surveys a variable appeared in see Appendix I, beginning on page 281. INDEX TO DATA SET (by Codebook Order) Mnemonic Mnemonic description YEAR GSS YEAR FOR THIS RESPONDENT ID RESPONDNT ID NUMBER WRKSTAT LABOR FORCE STATUS HRS1 NUMBER OF HOURS WORKED LAST WEEK HRS2 NUMBER OF HOURS USUALLY WORK A WEEK WRKSLF R SELF-EMP OR WORKS FOR SOMEBODY WRKGOVT GOVT OR PRIVATE EMPLOYEE OCC80 RS CENSUS OCCUPATION CODE (1980) PRESTG80 RS OCCUPATIONAL PRESTIGE SCORE (1980) INDUS80 RS INDUSTRY CODE (1980) OCC10 RS CENSUS OCCUPATION CODE (2010) INDUS10 RS INDUSTRY CODE (NAICS 2007) MARITAL MARITAL STATUS DIVORCE EVER BEEN DIVORCED OR SEPARATED WIDOWED EVER BEEN WIDOWED SPWRKSTA SPOUSE LABOR FORCE STATUS SPHRS1 NUMBER OF HRS SPOUSE WORKED LAST WEEK SPHRS2 NO. OF HRS SPOUSE USUALLY WORKS A WEEK SPEVWORK SPOUSE EVER WORK AS LONG AS A YEAR SPWRKSLF SPOUSE SELF-EMP. OR WORKS FOR SOMEBODY SPOCC80 SPOUSE CENSUS OCCUPATION CODE (1980) SPPRES80 SPOUSES OCCUPATIONAL PRESTIGE SCORE (1980) SPIND80 SPOUSES INDUSTRY CODE (1980) SPOCC10 SPOUSE CENSUS OCCUPATION CODE (2010) SPIND10 SPOUSES INDUSTRY CODE (NAICS 2007) PAWRKSLF FATHER SELF-EMP. OR WORKED FOR SOMEBODY PAOCC80 FATHERS CENSUS OCCUPATION CODE (1980) PAPRES80 FATHERS OCCUPATIONAL PRESTIGE SCORE (1980) PAIND80 FATHERS INDUSTRY CODE (1980) PAOCC10 FATHERS CENSUS OCCUPATION CODE (2010) PAIND10 FATHERS INDUSTRY CODE (2010) MAOCC80 MOTHERS CENSUS OCCUPATION CODE (1980) MAPRES80 MOTHERS OCCUPATIONAL PRESTIGE SCORE (1980) MAWRKSLF MOTHER SELF-EMP. OR WORKED FOR SOMEBODY MAIND80 MOTHERS INDUSTRY CODE (1980) MAOCC10 MOTHERS CENSUS OCCUPATION CODE (2010) MAIND10 MOTHERS INDUSTRY CODE (NAICS 2007) SIBS NUMBER OF BROTHERS AND SISTERS CHILDS NUMBER OF CHILDREN AGE AGE OF RESPONDENT AGEKDBRN R'S AGE WHEN 1ST CHILD BORN EDUC HIGHEST YEAR OF SCHOOL COMPLETED PAEDUC HIGHEST YEAR SCHOOL COMPLETED, FATHER MAEDUC HIGHEST YEAR SCHOOL COMPLETED, MOTHER
Recommended publications
  • A Critical Review of Studies Investigating the Quality of Data Obtained with Online Panels Based on Probability and Nonprobability Samples1
    Callegaro c02.tex V1 - 01/16/2014 6:25 P.M. Page 23 2 A critical review of studies investigating the quality of data obtained with online panels based on probability and nonprobability samples1 Mario Callegaro1, Ana Villar2, David Yeager3,and Jon A. Krosnick4 1Google, UK 2City University, London, UK 3University of Texas at Austin, USA 4Stanford University, USA 2.1 Introduction Online panels have been used in survey research as data collection tools since the late 1990s (Postoaca, 2006). The potential great cost and time reduction of using these tools have made research companies enthusiastically pursue this new mode of data collection. However, 1 We would like to thank Reg Baker and Anja Göritz, Part editors, for their useful comments on preliminary versions of this chapter. Online Panel Research, First Edition. Edited by Mario Callegaro, Reg Baker, Jelke Bethlehem, Anja S. Göritz, Jon A. Krosnick and Paul J. Lavrakas. © 2014 John Wiley & Sons, Ltd. Published 2014 by John Wiley & Sons, Ltd. Callegaro c02.tex V1 - 01/16/2014 6:25 P.M. Page 24 24 ONLINE PANEL RESEARCH the vast majority of these online panels were built by sampling and recruiting respondents through nonprobability methods such as snowball sampling, banner ads, direct enrollment, and other strategies to obtain large enough samples at a lower cost (see Chapter 1). Only a few companies and research teams chose to build online panels based on probability samples of the general population. During the 1990s, two probability-based online panels were documented: the CentER data Panel in the Netherlands and the Knowledge Networks Panel in the United States.
    [Show full text]
  • SAMPLING DESIGN & WEIGHTING in the Original
    Appendix A 2096 APPENDIX A: SAMPLING DESIGN & WEIGHTING In the original National Science Foundation grant, support was given for a modified probability sample. Samples for the 1972 through 1974 surveys followed this design. This modified probability design, described below, introduces the quota element at the block level. The NSF renewal grant, awarded for the 1975-1977 surveys, provided funds for a full probability sample design, a design which is acknowledged to be superior. Thus, having the wherewithal to shift to a full probability sample with predesignated respondents, the 1975 and 1976 studies were conducted with a transitional sample design, viz., one-half full probability and one-half block quota. The sample was divided into two parts for several reasons: 1) to provide data for possibly interesting methodological comparisons; and 2) on the chance that there are some differences over time, that it would be possible to assign these differences to either shifts in sample designs, or changes in response patterns. For example, if the percentage of respondents who indicated that they were "very happy" increased by 10 percent between 1974 and 1976, it would be possible to determine whether it was due to changes in sample design, or an actual increase in happiness. There is considerable controversy and ambiguity about the merits of these two samples. Text book tests of significance assume full rather than modified probability samples, and simple random rather than clustered random samples. In general, the question of what to do with a mixture of samples is no easier solved than the question of what to do with the "pure" types.
    [Show full text]
  • Trends in Voluntary Group Membership: Comments on Baumgartner and Walker
    Trends in Voluntary Group Membership: Comments on Baumgartner and Walker Tom w. Smith NORC University of Chicago GSS Methodological Report No. 60 February, 1989 This research was done for the General Social survey project directed by James A. Davis and Tom W. Smith. The project is funded by the National Science Foundation Grant SES-8745227. I would like to thank Jane Junn for data runs from the 1967 Verba­ Nie study, Mary E. Morris and P. Luevano for questionnaires from the 1952 and 1985 American National Election studies (ANES) , Santa Traugott for an ANES memo, and the Roper Center for the 1952 AIPO study. I would also like to thank Jane Junn, David Knoke, James A. Davis, Richard Niemi, Christopher Walsh, and Roger Tourangeau for comments on an earlier draft on this paper. Baumgartner and Walker ( 1988) argue that participation in voluntary associations has increased since the 1950s and that flaws in what they refer to as the Standard Question on group membership distort the time series and prevent the true expansion of group membership from being detected. This note examines the evidence on trends in voluntary group memberships and evaluates their critique of the standard Question. Baumgartner and Walker present three pieces of evidence in support of the notion that voluntary group membership has increased: 1) many new groups have formed and grown rapidly during recent decades, 2) national surveys of group membership show a rise in memberships from 1952 to 1974, and 3) inadequacies in the Standard Question mask further rises in membership since 1974. Case Studies of Group Membership First, they argue that monographic studies of membership growth indicate "the rise and development during the past half century of movements promoting new political causes (p.
    [Show full text]
  • Non-Response in Probability Sample Surveys in the Czech Republic*
    Non-Response in Probability Sample Surveys in the Czech Republic* JINDŘICH KREJČÍ** Institute of Sociology, Academy of Sciences of the Czech Republic, Prague Abstract: In this article the problem of survey non-response is examined with special reference to probability sampling in the Czech Republic. Non-response rates among Czech respondents in ISSP surveys between 1995 and 2005 were almost twice the rate recorded between 1991 and 1995 (25%). Such trends point to a decline in the ‘survey climate’. While non-contacts and refusals in surveys are a signifi cant problem, issues relating to how fi eldwork is under- taken are equally important. The large fl uctuations in non-contact rates and the relative success of the Czech Statistical Offi ce in attenuating non-response rates demonstrates that prudent surveying strategies can be effective. An ex- amination of two waves of the European Social Survey (ESS) reveals both the problems and potential strategies available for response rate enhancement. In this respect, all survey designers face the dilemma of balancing the benefi ts of data accuracy with increasing logistical costs. Improvement in survey qual- ity necessitates consideration of many issues and the ability to make sensible trade-offs between competing research objectives. Keywords: survey research in the Czech Republic, response rates, non-re- sponse trends, fi eldwork strategy Sociologický časopis/Czech Sociological Review, 2007, Vol. 43, No. 3: 561–587 Introduction This article deals with the issue of non-response rates in social survey research in the Czech Republic. It examines current trends and provides an in-depth analysis of this issue using the fi rst two waves of the European Social Survey (ESS) in the Czech Republic.
    [Show full text]
  • Access to Czech Social Survey Data
    www.ssoar.info Access to Czech Social Survey Data Krejci, Jindrich Veröffentlichungsversion / Published Version Zeitschriftenartikel / journal article Empfohlene Zitierung / Suggested Citation: Krejci, J. (2002). Access to Czech Social Survey Data. Sociologický časopis / Czech Sociological Review, 38(6), 809-826. https://nbn-resolving.org/urn:nbn:de:0168-ssoar-56299 Nutzungsbedingungen: Terms of use: Dieser Text wird unter einer Deposit-Lizenz (Keine This document is made available under Deposit Licence (No Weiterverbreitung - keine Bearbeitung) zur Verfügung gestellt. Redistribution - no modifications). We grant a non-exclusive, non- Gewährt wird ein nicht exklusives, nicht übertragbares, transferable, individual and limited right to using this document. persönliches und beschränktes Recht auf Nutzung dieses This document is solely intended for your personal, non- Dokuments. Dieses Dokument ist ausschließlich für commercial use. All of the copies of this documents must retain den persönlichen, nicht-kommerziellen Gebrauch bestimmt. all copyright information and other information regarding legal Auf sämtlichen Kopien dieses Dokuments müssen alle protection. You are not allowed to alter this document in any Urheberrechtshinweise und sonstigen Hinweise auf gesetzlichen way, to copy it for public or commercial purposes, to exhibit the Schutz beibehalten werden. Sie dürfen dieses Dokument document in public, to perform, distribute or otherwise use the nicht in irgendeiner Weise abändern, noch dürfen Sie document in public. dieses Dokument
    [Show full text]
  • The General Social Survey: an Overview How to Obtain More Information
    Catalogue no. 89F0115XIE The General Social Survey: An Overview How to obtain more information Specific inquiries about this product and related statistics or services should be directed to: Social and Aboriginal Statistics Division, Statistics Canada, Ottawa, Ontario, K1A 0T6 (telephone: (613) 951-5979, by fax at (613) 951-0387 or by e-mail at [email protected]). For information on the wide range of data available from Statistics Canada, you can contact us by calling one of our toll-free numbers. You can also contact us by e-mail or by visiting our website. National inquiries line 1 800 263-1136 National telecommunications device for the hearing impaired 1 800 363-7629 Depository Services Program inquiries 1 800 700-1033 Fax line for Depository Services Program 1 800 889-9734 E-mail inquiries [email protected] Website www.statcan.ca Information to access the product This product, catalogue no. 89F0115XIE, is available for free. To obtain a single issue, visit our website at www.statcan.ca and select Our Products and Services. Standards of service to the public Statistics Canada is committed to serving its clients in a prompt, reliable and courteous manner and in the official language of their choice. To this end, the Agency has developed standards of service that its employees observe in serving its clients. To obtain a copy of these service standards, please contact Statistics Canada toll free at 1 800 263-1136. The service standards are also published on www.statcan.ca under About Statistics Canada > Providing services to Canadians. Statistics Canada Social and Aboriginal Statistics Division The General Social Survey: An Overview Published by authority of the Minister responsible for Statistics Canada © Minister of Industry, 2006 All rights reserved.
    [Show full text]
  • Esomar Guideline for Conducting Survey Research
    ESOMAR GUIDELINE FOR CONDUCTING SURVEY RESEARCH VIA MOBILE PHONE World Research Codes and Guidelines 1 | World Research Codes and Guidelines All ESOMAR world research codes and guidelines, including latest updates, are available online at www.esomar.org © 2011 ESOMAR. All rights reserved. Issued June 2011 No part of this publication may be reproduced or copied in any form or by any means, or translated, without the prior permission in writing of ESOMAR. ESOMAR codes and guidelines are drafted in English and the English texts are the definitive versions. 2 | World Research Codes and Guidelines ESOMAR GUIDELINE FOR CONDUCTING SURVEY RESEARCH VIA MOBILE PHONE CONTENTS 1. INTRODUCTION 3 2. SCOPE 3 3. KEY PRINCIPLES 3 4. RESPONDENT COSTS 4 5. RESPONDENT SAFETY AND CONFIDENTIALITY 4 6. CONTACT TIMES 5 7. INTERVIEW DURATION 5 8. AUTOMATED DIALLING AND CALLING EQUIPMENT 5 9. LOCATION DATA 5 10. CALLING PROTOCOLS 6 11. FURTHER INFORMATION 6 APPENDIX – KEY FUNDAMENTALS OF THE ICC/ESOMAR CODE 7 3 | World Research Codes and Guidelines 1. INTRODUCTION As mobile phones become the preferred mode of telephone communication on a global scale, it is critical for ESOMAR to establish clear guidance on the conduct of market, social and opinion research via mobile phone. The aim is to promote professional standards, best practices, and respectful relationships with the individuals being called and to assist researchers in addressing legal, ethical, and practical considerations when conducting research via mobile phone. Mobile phone technology and communications have grown rapidly in some countries and at a slower pace in others, and mobile communication laws and regulations are still evolving.
    [Show full text]
  • Research Highlights
    General Social Survey NORC at the University of Chicago Research Highlights www.norc.org | [email protected] December 2016 General Social Survey Jodie Smylie and colleagues, 2016 The General Social Survey (GSS) is a biennial, nationally representative survey that has been conducted by NORC to monitor societal change and study the growing complexity of American society since 1972. Funded in large part by the National Science Foundation, the GSS is NORC’s longest running project, and one of its most influential. Except for U.S. Census data, the GSS is the most frequently analyzed source of information in the social sciences. GSS data are used in numerous newspaper, magazine, and journal articles, by legislators, policy makers, and educators. The GSS is also a major teaching tool in colleges and universities: more than 27,000 journal articles, books, reports, and Ph.D. dissertations are based on the GSS, and about 400,000 students use the GSS in their classes each year. The GSS is the only full-probability, personal-interview survey designed to monitor changes in both social characteristics and attitudes currently being conducted in the United States. Over 1,000 trends have been tracked since 1972 by the GSS. Since the GSS adopted questions from earlier surveys, trends can be followed for up to 75 years. Among the topics covered are civil liberties, crime and violence, intergroup tolerance, morality, national spending priorities, psychological well-being, social mobility, and stress and traumatic events. Altogether the GSS is the single best source for sociological and attitudinal trend data covering the United States.
    [Show full text]
  • 1 Social-Science Research and the General Social Surveys Tom W
    Social-Science Research and the General Social Surveys Tom W. Smith, Jibum Kim, Achim Koch, and Alison Park GSS Project Report No. 27 The GSS Model of Social-Science Research During the last generation a new measurement instrument has emerged in the social sciences, the general social survey (GSS)(Davis, Mohler, and Smith, 1994; Smith, 1997). Traditionally, empirical research in the social sciences had been intermittent, varied greatly in data quality and generalizability, focused on a narrow set of issues and/or hypotheses, and led by a senior researcher or principal investigator pursuing his or her own research agenda. The GSSs embraced a new model of social-science research. This article discusses 1) the GSS-model of social-science research including a) the creating of a social-science infrastructure, b) reliable, valid, and generalizable measurement, c) broad coverage of topics, d) a collective, community focus, and e) equal and widespread access and use; 2) the initial development of the GSS-model in the United States, Germany, Great Britain, and Australia, and 3) recent developments, especially in East Asia. First, GSSs are on-going research programs building a social-science infrastructure, not one- shot endeavors. GSSs are designed to be repeated at regular intervals. This serves several purposes: 1) allowing the monitoring and modeling of societal change via repeated measurements, 2) permitting the study of sub-groups by pooling cases across replicating cross-sections, 3) facilitating the replication of scientific findings by allowing results from earlier rounds to be retested in subsequent rounds, 4) assisting the refinement of models by providing a set of core, replicating measures that could be augmented by additional items based on developing theory and earlier empirical results, and 5) providing an infrastructure for the social sciences and avoiding repeated, start-up costs and the continual reorganization of research efforts.
    [Show full text]
  • Little Things Matter: a Sampler of How Differences in Questionnaire
    Little Things Matter: A Sampler of How Differences in Questionnaire Format Can Affect Survey Responses Tom W. Smith National Opinion Research Center University of Chicago GSS Methodological Report No. 78 July, 1993 This research was done for the General Social Survey project directed by James A. Davis and Tom w. Smith. The project is supported by the National Science Foundation, Grant No. SES- 9122462. I would like to thank Woody Carter and David Mingay for comments on drafts of this paper. It is well known that seemingly minor changes in question wording, response format, and context can appreciably alter response distributions. What is less appreciated is that non-verbal aspects of surveys such as physical layout and visual presentations can also notably influence answers. Below we cite five examples where variations in such matters affected how interviewers, respondents, or both handled and responded to questions: 1) Misalignment of Response Categories 2) Dutch Ladders 3) Placement of Follow-up Questions 4) Overly Compact Question Formats 5) Open-ended Questions and Wide Open Spaces Misalignment of Response Categories The 1993 International Social Survey Program (ISSP) study on the environment was administered as a self-completion supplement to NORC's General Social Survey (GSS) (Davis and Smith, 1992). Due to a font problem the final master of the questionnaire misaligned the response boxes to Q.21b. The boxes were pushed one tab to the right so that the left-hand box appeared where the right-hand box should have been and the right-hand box was shifted into the right margin (See Figure 1).
    [Show full text]
  • Description of Global Database on Intergenerational Mobility (GDIM)1
    Description of Global Database on Intergenerational Mobility (GDIM)1 Development Research Group, World Bank (Version 1, May 2018) Coverage of economies: 148 Coverage of birth cohorts: 1940-1989 Survey years: 1991-2016 World population coverage: 96 percent Downloads: GDIM dataset – May 2018 (CSV file, 4.0 mb) GDIM province-level dataset – May 2018 (CSV file, 0.03 mb) Description of GDIM dataset – May 2018 (PDF file, 1.1 mb) How to cite this database? The users should refer to the database as GDIM (abbreviation of Global Database on Intergenerational Mobility) database; and cite as, “GDIM. 2018. Global Database on Intergenerational Mobility. Development Research Group, World Bank. Washington, D.C.: World Bank Group.” Users should also cite the report: “Narayan, Ambar; Van der Weide, Roy; Cojocaru, Alexandru; Lakner, Christoph; Redaelli, Silvia; Mahler, Daniel Gerszon; Ramasubbaiah, Rakesh Gupta N.; Thewissen, Stefan. 2018. Fair Progress? : Economic Mobility Across Generations Around the World. Equity and Development. Washington, DC: World Bank. https://openknowledge.worldbank.org/handle/10986/28428 License: CC BY 3.0 IGO. 1 For questions, please contact: [email protected] 1 Table of Contents 1. What is the Global Database on Intergenerational Mobility (GDIM)? ................................................. 3 2. Country and population coverage of the GDIM .................................................................................... 4 3. Survey identification ............................................................................................................................
    [Show full text]
  • A Coding of Social Class for the General Social Survey *
    A Coding of Social Class for the General Social Survey * Stephen L. Morgan Johns Hopkins University GSS Methodological Report No. 125 August 2017 * I thank Minhyoung Kang and Jiwon Lee for their research assistance, as well as Tom Smith and Jeremy Freese for their comments and suggestions. Tables of Contents 1. Introduction: Jobs, Occupations, and Social Class in the GSS . 1 1.1. Prestige Ratings and SEI Scores . 1 1.2. A Coding of Social Class . 1 2. The Rationale and Strategy for Coding Social Class . 3 2.1. The Original EGP Class Schema . 3 2.2. Why Code to EGP? . 4 2.3. Orienting Decisions for the Coding Strategy . 5 2.4. A Coding Strategy Based Only on the ACS, SOC, and ONET . 7 3. The New Coding of Occupations . 11 3.1. Classes IIIa and V: A Natural Evolution of the Original EGP Classes? . 11 3.2. New Class Descriptions with Illustrative Occupations . 12 4. Characteristics of the New EGP Classes . 16 4.1. Characteristics of the Classes, Based on the ACS and ONET . 16 4.2. A Comparison with SOC MaJor and Minor Groups of Occupations . 21 4.3. Characteristics of the Classes in the GSS and a (Plausibly) Aligned ACS Sample . 25 5. Sample Stata Code for Merging the .csv File and the GSS Cumulative File . 37 6. Conclusions . 39 7. References Cited . 40 8. Appendix Tables . 41 A1: GSS Occupational Distributions for the 10-Class Version of EGP . 41 A2: GSS Occupational Distributions for the 11-Class Version of EGP . 58 A3: GSS Occupational Distributions for the 12-Class Version of EGP .
    [Show full text]