===========================================================================

   COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) - MODULE 6 (2021-2026)

                      CODEBOOK PART 1: INTRODUCTION
                          
                 SECOND ADVANCE RELEASE - DECEMBER 16, 2025
 
                             CSES Secretariat
                               www.cses.org

===========================================================================

HOW TO CITE THE STUDY:

The Comparative Study of Electoral Systems (www.cses.org). CSES MODULE 6
SECOND ADVANCE RELEASE [dataset and documentation]. December 16, 2025 
version. doi:10.7804/cses.module6.2025-12-16. 

These materials are based on work supported by the American National
Science Foundation (www.nsf.gov) under grant numbers SES-1760058 and
SES-2214278, the GESIS - Leibniz Institute for the Social Sciences, 
the University of Michigan, in-kind support of participating election 
studies, the many organizations that sponsor planning meetings and 
conferences, and the numerous organizations that fund national 
election studies by CSES Collaborators.

Any opinions, findings and conclusions, or recommendations expressed
in these materials are those of the author(s) and do not necessarily
reflect the views of the funding organizations.

===========================================================================


===========================================================================
TABLE OF CONTENTS
===========================================================================

))) CSES ADVANCE RELEASE - WHAT USERS NEED TO KNOW


))) CSES DESIGN, DOCUMENTATION, & WEIGHTS - ADVICE TO USERS


))) OVERVIEW OF "CODEBOOK PART 1: INTRODUCTION" 


))) HOW TO NAVIGATE THE CSES MODULE 6 CODEBOOK


))) LIST OF TABLES IN CODEBOOK PART 1


))) THE COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) PROJECT OVERVIEW
    >>> CSES PROJECT PROFILE
    >>> CSES MODULE 6 STUDY DESCRIPTION - ABSTRACT
    >>> CSES MODULE 6 PLANNING COMMITTEE
    >>> CSES MODULE 7 PLANNING COMMITTEE
    >>> CSES MODULE 6 COLLABORATORS
    >>> CSES SECRETARIAT


))) CSES MODULE 6 - HOW TO ACCESS?
    >>> THE CSES CODEBOOK
    >>> THE CSES DATA FILES


))) CSES MODULE 6 STUDY
    >>> OVERVIEW OF CSES MODULE 6 DATA FILE PARTICULARS
    >>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 6
    >>> MICRO-LEVEL (SURVEY) COMPONENT
    >>> CSES MODULE 6 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION
        OF THE CSES QUESTIONNAIRE
    >>> DISTRICT-LEVEL COMPONENT
    >>> MACRO-LEVEL COMPONENT


))) CSES MODULE 6 DOCUMENTATION - WHAT'S AVAILABLE AND HOW TO USE?      
    >>> CSES CODEBOOK OVERVIEW
    >>> CSES CODEBOOK CONVENTIONS
    >>> CSES CODEBOOK - VARIABLE NOTES AND ELECTION STUDY NOTES
    >>> CSES ORIGINAL QUESTIONNAIRE FOR MODULE 6
    >>> CSES - ADDITIONAL DOCUMENTATION

    
))) CSES MODULE 6 STUDY DATA AND CODEBOOK: ADDITIONAL INFORMATION
    >>> CODING OF PARTIES/COALITIONS & LEADERS 
    >>> CSES DATA BRIDGING: NEW FRONTIERS IN DATA LINKAGE
    >>> DERIVATIVE VARIABLES   
    >>> IDENTIFICATION VARIABLES
    >>> MISSING DATA
    >>> WEIGHTS
    >>> FREEDOM STATUS OF ELECTIONS  
    >>> PROCESSING CHECKS OF MODULE 6 DATASET BY THE CSES SECRETARIAT


))) CSES MODULE 6 BIBLIOGRAPHY


===========================================================================
))) CSES ADVANCE RELEASE - WHAT USERS NEED TO KNOW
===========================================================================

This dataset and all accompanying documentation is the "Second Advance 
Release" of CSES Module 6 (2021-2026).

An Advance Release is a preliminary version of this CSES product. It thus 
lacks some of the checking, cleaning, processing, documentation, data, and 
variables that we anticipate in the Full Release of this product. The 
product is still in development, and data will be added gradually. Many 
election studies and variables that will eventually be present in the CSES 
Module 6 Full Release are unavailable in this file. Advance Releases are 
provided as a service to the CSES user community for those analysts who find 
it valuable to work with preliminary versions of the dataset. 

Users should anticipate future changes and improvements to the naming, data, 
and documentation of variables and election studies that appear in an 
advanced release file. If users wish to re-use their programming syntax/code 
on a future release of this product, we recommend that the code be written 
to accommodate these potential changes.

Users of the Advance Release may also wish to monitor the errata for CSES 
Module 6 on the CSES website to check for known errors that may impact their 
analyses. To view errata for CSES Module 6, go to Data Download on the CSES 
website, navigate to the CSES Module 6 download page, and click on the 
Errata link in the white box to the right of the page.

We hope that until the Full Release of CSES Module 6 is available, users 
will find this and future CSES Module 6 Advance Releases helpful in their 
work.


===========================================================================
))) CSES DESIGN, DOCUMENTATION, & WEIGHTS - ADVICE TO USERS
===========================================================================

We recommend that researchers become familiar with the CSES design, units 
of analysis, documentation, and dataset weights before beginning their 
investigations. For instance, while the set of respondents appearing within
each election study represents their respective nations, the group of 
nations that appear within CSES is not a random sample of countries 
worldwide. Furthermore, while many election studies include 1,000 or so 
respondents, other election studies may consist of over 10,000 respondents. 
Some nations will have studies of more than one election in a CSES module,
and occasionally there will be two independent studies of a single 
election. Last, some election studies include over samples of specific 
sub-populations or would otherwise benefit from use of the included weight
variables. We hope you find our website and documentation useful as you 
proceed with your work, and welcome any questions or suggestions you have.


===========================================================================
))) OVERVIEW OF "CODEBOOK PART 1: INTRODUCTION"
===========================================================================

Part 1 of the Codebook provides an extensive overview of the CSES MODULE 6
study. It includes general details about the project, the project's 
governing board (the Planning Committee), information on the national 
Collaborators who administered CSES MODULE 6 in their national election 
study, and on the activities of the CSES Secretariat - the operational hub
of the project. 

Further, extensive information about the CSES MODULE 6 datafile particulars,
how to access CSES data, CSES documentation conventions, and CSES coding 
conventions are also provided. In addition, Codebook Part 1 offers guidance
on the different components of a CSES dataset (micro, district, and macro-
level data), and derivative variables and data bridging variables available 
to users. Part 1 of the Codebook closes with the project bibliography, a 
non-exhaustive list of references consulted by the CSES Secretariat for 
processing CSES MODULE 6. 


===========================================================================
))) HOW TO NAVIGATE THE CSES MODULE 6 CODEBOOK
===========================================================================

In the CSES MODULE 6 dataset, all variables begin with the letter "F" 
(F being the sixth letter of the English alphabet and thus signifying 
MODULE 6).

The CSES Codebook is especially extensive and users are advised that the 
best way to navigate it is electronically. It is a .txt format which 
allows it to be accessed via a variety of programs. 

The CSES Codebook can be navigated quickly in the electronic files, with 
the following commands allowing for quick searching:

))) = Section Header. 

>>> = Sub-section Header 1.

<<>> = Sub-section Header 2. 

+++ = Tables.

CSES QUESTION CLASSIFICATION = For survey level variables only, CSES  
Question Classification details whether the variable is part of the CSES  
Core component, which are questions asked repeatedly in CSES Modules, 
whether a variable is part of the CSES Module Theme component, which are  
questions specific to the Module Theme under exploration and might not be 
included in CSES repeatedly, or whether a variable is a Derivative Variable, 
which is explained below. 

VARIABLE NOTES = Notes for particular variables.

ELECTION STUDY NOTES = Notes for a particular election study.

DERIVATIVE VARIABLE = Highlights a variable derived from another 
variable or variables within the CSES.

POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER = 
Highlights a variable that may be used for data bridging at polity level.

POTENTIAL REGIONAL LEVEL BRIDGING IDENTIFIER = 
Highlights a variable that may be used for data bridging at regional level.

POTENTIAL TIME BRIDGING IDENTIFIER = 
Highlights a variable that may be used for data bridging by time.

POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER = Highlights a variable 
that may be used for data bridging at party/coalition level.

POTENTIAL CSES PRODUCT BRIDGING IDENTIFIER = Highlights a variable 
that may be used for data bridging with other CSES products.


===========================================================================
))) LIST OF TABLES IN CODEBOOK PART 1
===========================================================================

Below, we list the Tables located in Codebook Part 1. Tables can be 
accessed in the electronic version of the CSES Codebook by searching for
"+++". 

   - OVERVIEW OF ELECTION STUDIES INCLUDED IN CSES MODULE 6 WITH NUMBER OF 
     OBSERVATIONS, MODE OF DATA COLLECTION, AND FIELDWORK DATES


===========================================================================
))) THE COMPARATIVE STUDY OF ELECTORAL SYSTEMS (CSES) PROJECT OVERVIEW
===========================================================================

---------------------------------------------------------------------------
>>> CSES PROJECT PROFILE
---------------------------------------------------------------------------

The Comparative Study of Electoral Systems (CSES) is a collaborative
program of research among election study teams from around the world.
Participating polities include a common module of survey questions
in their post-election studies. The resulting data are deposited along
with voting, demographic, district, and macro variables. The studies are
then merged into a single, free, public dataset for use in comparative
study and cross-level analysis.

The CSES project focuses on respondents' behavior and attitudes during 
the time of a national election, with a particular emphasis on voting and 
turnout. Each CSES Module consists of a nationally-representative 
post-election survey and additional variables about the context of the 
overall polity and electoral system within which the respondents find 
themselves. Every five years a new CSES Module is designed with a 
different substantive theme selected to address essential questions 
in electoral studies and social science. 

An international committee of leading scholars of electoral politics and 
political science develop the research agenda, questionnaires, and study 
design. The design is implemented in each polity by their foremost 
social scientists. By collaborating in this way, the CSES community hopes 
to advance scientific inquiry into the relationship between electoral
institutions and political behavior.

The work of the CSES Secretariat is funded by the American National 
Science Foundation, the GESIS - Leibniz Institute for the Social 
Sciences, and the University of Michigan's Center for Political Studies. 
Details of particular grants that provided funding for MODULE 6 are 
available under the "HOW TO CITE THE CSES MODULE 6 STUDY". 
The project also receives in-kind support from participating election 
studies, additional organizations that sponsor Planning Committee (PC) 
meetings and conferences, and the many organizations that fund national 
election studies that participate in CSES. 

This is the sixth iteration of CSES known as CSES MODULE 6. The remainder
of the project description relates specifically to CSES MODULE 6. 


---------------------------------------------------------------------------
>>> CSES MODULE 6 STUDY DESCRIPTION - ABSTRACT
---------------------------------------------------------------------------

CSES MODULE 6 is scheduled to officially be in data collection from 2021 to 
2026.

CSES MODULE 6 focuses on the theme "Representative Democracy Under Pressure" 
with questions tapping citizens' views on the functioning of the democratic 
system and perceptions of system outputs, gender representation, 
preferences for government and the impact of the COVID-19 pandemic.

More information regarding the theme of MODULE 6 can be found in the
CSES MODULE 6 Stimulus Paper available on the CSES website in the "About"
section ("Planning Committee"). 


---------------------------------------------------------------------------
>>> CSES MODULE 6 PLANNING COMMITTEE
---------------------------------------------------------------------------

The CSES MODULE 6 Planning Committee (PC) was responsible for the design of
CSES MODULE 6 and took initial responsibility for its implementation.
Besides the Chair, Planning Committee Members are listed alphabetically by 
surname. The following persons were members of the CSES MODULE 6 Planning 
Committee:

ELIZABETH ZECHMEISTER (MODULE 6 Planning Committee Chair)
Vanderbilt University, United States

EVA ANDUIZA
Universitat Autonoma de Barcelona, Spain

ALI CARKOGLU
Koc University, Turkey

MARINA COSTA LOBO
University of Lisbon, Portugal

DAVID HOWELL, ex officio
University of Michigan, United States

ORIT KEDAR
The Hebrew University of Jerusalem, Israel

GEORG LUTZ
University of Lausanne, Switzerland

IRFAN NOORUDDIN
Georgetown University, United States

HENRIK OSCARSSON
University of Gothenburg, Sweden

STEPHEN QUINLAN, ex officio
GESIS - Leibniz Institute for the Social Sciences, Germany

RUDIGER SCHMITT-BECK
University of Mannheim, Germany

CARLOS SHENGA
Higher Institute of Public Administration, Mozambique

JILL SHEPPARD
Australian National University, Australia

ALBERTO SIMPSER
ITAM (Instituto Tecnologico Autonomo de Mexico), Mexico

LAURA STEPHENSON
Western University, Canada

DAVID SULMONT
Pontifical Catholic University of Peru, Peru

JOSHUA TUCKER
New York University, United States

WOUTER VAN DER BRUG
University of Amsterdam, The Netherlands

MARKUS WAGNER
University of Vienna, Austria

MASAHIRO YAMADA
Kwansei Gakuin University, Japan

ERIC YU
National Chengchi University, Taiwan R.O.C.


Past members of the CSES MODULE 6 Planning Committee include:

CATHERINE E. DE VRIES
Free University Amsterdam, Netherlands

AIDA JUST
Bilkent University, Turkey


---------------------------------------------------------------------------
>>> CSES MODULE 7 PLANNING COMMITTEE
---------------------------------------------------------------------------

The CSES MODULE 7 Planning Committee (PC) takes responsibility not only for 
the design and implementation of MODULE 7 but also the responsibility for
the remainder of CSES MODULE 6 until its completion. 
The following persons are members of the CSES MODULE 7 Planning Committee: 

RUTH DASSONNEVILLE (MODULE 7 Planning Committee Chair)
KU Leuven, Belgium

SELIM ERDEM AYTAC
Koc University, Turkey

THORSTEN FAAS
Free University Berlin, Germany

LIRAN HARSGOR
University of Haifa, Israel

AIRO HIRO
Waseda University, Japan

DAVID HOWELL, ex officio
University of Michigan, United States

LUKAS LINEK
Czech Academy of Sciences, Czechia

NOAM LUPU
Vanderbilt University, United States

AMENI MEHREZ
Central European University, Hungary

IRFAN NOORUDDIN
Georgetown University, United States

EVA H. ONNUDOTTIR
University of Iceland, Iceland

ROSARIO QUEIROLO
Universidad Catolica del Uruguay, Uruguay

MARIANA RODRIGUEZ, ex officio
Vanderbilt University, United States

COLLETTE SCHULZ-HERZENBERG
Stellenbosch University, South Africa

LAURA STEPHENSON
Western University, Canada

DAVID SULMONT
Pontifical Catholic University of Peru, Peru

JOSHUA TUCKER
New York University, United States

ASA VON SCHOULTZ
University of Helsinki, Finland

ERIC YU
National Chengchi University, Taiwan R.O.C.


Past members of the CSES MODULE 7 Planning Committee include:

STEPHEN QUINLAN
GESIS - Leibniz Institute for the Social Sciences, Germany

MARINA COSTA LOBO (Former Chair of the PC)
University of Lisbon, Portugal

JILL SHEPPARD
Australian National University, Australia


---------------------------------------------------------------------------
>>> CSES MODULE 6 COLLABORATORS
---------------------------------------------------------------------------

The CSES project is extremely grateful to our MODULE 6 Collaborators, who
raised their own funds to include CSES MODULE 6 in a nationally
representative post-election study in their polity or province.

Listed Collaborators are those who appear in the Design Report for the
respective study - they are not necessarily the actors who collected
the data, and they are not necessarily the only investigators on each
study. Most election studies benefited from the scientific input and data
preparation skills of additional persons not listed here.

Within each election study, Collaborators are presented in the order in
which they are listed in the Design Report deposited by each Collaborator
team. The affiliations listed are current as of the date when each
election study's Design Report was deposited with CSES. The polities are
listed in alphabetical order. 


- AUSTRALIA (2022)       IAN MCALLISTER
                         Australian National University, Australia 

                         SARAH CAMERON
                         Griffith University, Australia

                         SIMON JACKMAN
                         Sydney University, Australia

                         JILL SHEPPARD
                         Australian National University, Australia


- AUSTRIA (2024)         SYLVIA KRITZINGER
                         University of Vienna, Austria

                         KATHARINA PFAFF
                         University of Vienna, Austria

                         JULIA PARTHEYMULLER
                         University of Vienna, Austria


- BRAZIL (2022)          RACHEL MENEGUELLO
                         State University of Campinas (UNICAMP), Brazil


- DENMARK (2022)         KASPER M. HANSEN
                         Department of Political Science, 
                         University of Copenhagen, Denmark

                         RUNE STUBAGER
                         Department of Political Science, 
                         Aarhus University, Denmark


- FRANCE (2022)          NICOLAS SAUGER
                         Centre de donnees socio-politiques
                         Sciences Po, Paris, France


- MONTENEGRO (2023)      OLIVERA KOMAR
                         De Facto Consultancy & Faculty of Political 
                         Science, University of Montenegro, Montenegro

                         SLAVEN ZIVKOVIC 
                         De Facto Consultancy, Montenegro

                         NEMANJA BATRICEVIC
                         Faculty of Political Science, University of 
                         Montenegro, Montenegro  

                         NEMANJA STANKOV
                         Faculty of Political Science, University of 
                         Montenegro, Montenegro


- NEW ZEALAND (2023)     JACK VOWLES
                         Victoria University of Wellington, New Zealand


- NORTH MACEDONIA (2024) JOVAN BLIZNAKOVSKI
                         Ss. Cyril and Methodius University in Skopje, 
                         Institute for Sociological, Political and Juridical
                         Research, North Macedonia

                         ANETA CEKIKJ
                         Ss. Cyril and Methodius University in Skopje, 
                         Institute for Sociological, Political and Juridical
                         Research, North Macedonia


- POLAND (2023)          MIKOLAJ CZESNIK
                         SWPS University, Poland

                         RADOSLAW MARKOWSKI
                         SWPS University, Poland

                         MACIEJ SYCHOWIEC
                         SWPS University, Poland

                         OLIWIA SZCZUPSKA
                         SWPS University, Poland


- PORTUGAL (2022)        MARINA COSTA LOBO
                         Institute of Social Sciences, University of Lisbon,
                         Portugal

                         PEDRO MAGALHAES 
                         Institute of Social Sciences, University of Lisbon,
                         Portugal


- PORTUGAL (2024)        MARINA COSTA LOBO
                         Institute of Social Sciences, University of Lisbon,
                         Portugal

                         PEDRO MAGALHAES 
                         Institute of Social Sciences, University of Lisbon,
                         Portugal


- SLOVAKIA (2023)        OLGA GYARFASOVA
                         Comenius University, in Bratislava, Slovakia 

                         MILOSLAV BAHNA
                         Sociological Institute, Slovak Academy of Sciences, 
                         Slovakia


- SLOVENIA (2022)        META NOVAK
                         University of Ljubljana, Faculty of Social Sciences
                         Slovenia

                         ZIVA BRODER
                         University of Ljubljana, Faculty of Social Sciences
                         Slovenia


- SWEDEN (2022)          HENRIK OSCARSSON
                         Department of Political Science, University of 
                         Gothenburg, Sweden


- SWITZERLAND (2023)     ANKE TRESCH
                         FORS/ University of Lausanne, Switzerland

                         LINE RENNWALD
                         FORS, Switzerland

                         LUKAS LAUENER
                         FORS, Switzerland


- TAIWAN (2024)          CHEN LU-HUEI
                         Election Study Center, National Chengchi University
                         (NCCU), Taiwan, R.O.C.


- TURKIYE (2023)         SELIM ERDEM AYTAC
                         Koc University, Istanbul, Turkiye

                         ALI CARKOGLU
                         Koc University, Istanbul, Turkiye
                     
                         ERSIN KALAYCIOGLU
                         Sabanci University, Istanbul, Turkiye

                         MERT MORAL
                         Sabanci University, Istanbul, Turkiye                    

                         SUSAN BANDUCCI
                         University of Exeter, United Kingdom


- UNITED STATES (2024)   NICHOLAS A. VALENTINO
                         University of Michigan, United States

                         SHANTO IYENGAR
                         Stanford University, United States

                         D. SUNSHINE HILLYGUS
                         Duke University, United States

                         DARON SHAW
                         University of Texas Austin, United States


---------------------------------------------------------------------------
>>> CSES SECRETARIAT
---------------------------------------------------------------------------

The CSES Secretariat comprises the central staffing and operational hub for 
the CSES project, under the leadership of the Chair of the CSES Planning 
Committee, PC - listed above). Since June 2011, the Secretariat has been
a collaboration between the GESIS - Leibniz Institute for the Social
Sciences, Germany, and the University of Michigan's Center for Political
Studies in the United States. 
Professor Elizabeth Zechmeister of the Vanderbilt University, and Chair of
the CSES MODULE 6 Planning Committee, and Professor Marina Costa Lobo of 
the University of Lisbon, Chair of the CSES MODULE 7 Planning Committee, 
have overseen the operations of CSES MODULE 6 during their respective 
terms as Chair.

Various persons have staffed the CSES Secretariat throughout the MODULE 6
period. David Howell served as the Director of Studies for the first two 
advance releases of MODULE 6. Dr. Stephen Quinlan served as the Project 
Manager for the first two advance releases of MODULE 6. Katharina Blinzler, 
Dr. Klara Dentler, Dr. Mariana Rodriguez, Dr. Bojan Todosijevic, Dr. Rob 
Vidigal, & Dr. Slaven Zivkovic were responsible for research support, 
documentation, preparation, communications, and other services. Additional 
support to the Secretariat was provided by several research assistants from 
the GESIS - Leibniz Institute for the Social Sciences.  

Support was received from various sources for the activities of the CSES
Secretariat during the period of CSES MODULE 6:

1. American National Science Foundation (NSF) grant SES-1760058, 
   "The Sixth Module of the Comparative Study of Electoral Systems (CSES)"
   with Principal Investigators Ken Kollman (University of Michigan), John 
   Aldrich (Duke University), and Elizabeth Zechmeister (Vanderbilt
   University) supported CSES Secretariat activities at the University of 
   Michigan beginning in 2018.

2. American National Science Foundation (NSF) grant SES-2214278, 
   "The Seventh Module of the Comparative Study of Electoral Systems (CSES)"
   with Principal Investigators Ken Kollman (University of Michigan) and 
   Elizabeth Zechmeister (Vanderbilt University) supported CSES Secretariat
   activities at the University of Michigan beginning in 2023.

3. The CSES Secretariat activities at the GESIS - Leibniz Institute for the
   Social Sciences, Germany are funded by the GESIS - Leibniz Institute.

4. The Center for Political Studies (CPS) at the University of Michigan 
   provides additional financial support.


===========================================================================
))) CSES MODULE 6 - HOW TO ACCESS?
===========================================================================

---------------------------------------------------------------------------
>>> THE CSES CODEBOOK
---------------------------------------------------------------------------

Users are advised to first download the CSES Codebook file:

  cses6_codebook.zip  Contains the five Codebook files, including this 
                      one, in text format.
                   
The Codebook can also be navigated online the CSES MODULE 6 study page at: 
        https://cses.org/data-download/cses-module-6-2021-2026/       

---------------------------------------------------------------------------
>>> THE CSES DATA FILES
---------------------------------------------------------------------------

The following ZIP files, which contain the CSES data are available to 
download from the CSES MODULE 6 study page at: 
        https://cses.org/data-download/cses-module-6-2021-2026/ 

Users can download the data in a variety of formats depending on which 
statistical packages they intend to use with the data:

  cses6_csv.zip       Contains a .CSV file with variables names as column 
                      headers but no additional metadata (for instance,
                      no code labels are included).
                                      
  cses6_r.zip         Contains a R Workplace system file (.rdata), with
                      the dataset already prepared and ready to be loaded
                      into R. Missing data statements are not applied.
  
  cses6_sas.zip       Contains a SAS 7-8 system file (.sas7bdat), with
                      the dataset already prepared and ready to be loaded
                      into SAS. Missing data statements are not applied.
  
  cses6_spss.zip      Contains a SPSS system file (.sav), with the dataset
                      already prepared and ready to be loaded into SPSS.
                      Missing data statements are not applied.
  
  cses6_stata.zip     Contains a STATA 18 system file (.dta), with the
                      dataset already prepared and ready to be loaded
                      into STATA. Missing data statements are not applied.
                      Users of STATA 13 or earlier versions of this
                      program are advised to use the "cses_syntax.zip"
                      files to load the dataset into their package. 

Please note that all above packages will need a File Extractor 
program downloaded to their computer to be able to Unzip and open the
above files. 

We recommend that PC users create the following directory on their hard
drive, and to download their files from this MODULE 6 release to that 
location:
                 "c:/cses/module6/20251216/"                        

The sub-directory value "20251216" represents the version (release date) of 
the dataset - this being 2025, and the December 16 version of CSES MODULE 6.
This file structure is compatible with how the "cses6_syntax.zip" file
(detailed above) is organized. The method allows users with multiple CSES
datasets and/or versions to stay organized and not over-write their other 
files. Users of other computer types (Macs, Unix, etc.) are recommended to 
use a similar directory structure to organize their CSES files.


===========================================================================
))) CSES MODULE 6 STUDY
===========================================================================


---------------------------------------------------------------------------
>>> OVERVIEW OF CSES MODULE 6 DATA FILE PARTICULARS
---------------------------------------------------------------------------

The particulars of the Second Advance Release of CSES MODULE 6 are: 

Type of study:                CROSS-SECTIONAL
Kind of data:                 SURVEY DATA FUSED WITH CONTEXTUAL MACRO DATA
Primary Unit of Analysis:     INDIVIDUALS 
Universe:                     ALL PERSONS OF ELIGIBLE VOTING AGE AND 
                              ELIGIBLE TO VOTE IN THE NATIONAL ELECTION
Geographic Coverage:          GLOBAL (Europe, parts of Asia and South 
                              America, Australia)
Total Geographic Regions:     6 (as defined by the UN Geographic regions)
File Structure:               RECTANGULAR 
Total Case Count:             33,871
Total Variable Count:         676      
Total Polities:               17               
Total Election Studies:       18         


Users are advised that the above information relates to this Advance 
Release. The product is still in development, and data will be added 
gradually. Many election studies and variables that will eventually be 
present in the CSES Module 6 Full Release are unavailable in this version 
of the file. 


---------------------------------------------------------------------------
>>> LIST OF ELECTION STUDIES INCLUDED IN CSES MODULE 6
---------------------------------------------------------------------------

The Second Advance Release of CSES MODULE 6 contains data from the following 
18 election studies in 17 polities. They are listed below in alphabetic
order with an overview of some particulars of each election study. 

    | +++ TABLE: OVERVIEW OF ELECTION STUDIES INCLUDED IN CSES MODULE 6 WITH
    |            NUMBER OF OBSERVATIONS, MODE OF DATA COLLECTION, AND
    |            FIELDWORK DATES
    |
    | POLITY (ELEC YEAR)       N of      Mode of    Dates of Fieldwork
    |                      Observations Interview    (Start-End date)     
    | ---------------------------------------------------------------------
    | AUSTRALIA (2022)        3,269        MX     May 23, 2022-Jun 05, 2022
    | AUSTRIA (2024)          1,569       INT     Sep 30, 2024-Oct 21, 2024
    | BRAZIL (2022)           2,001       F2F     Nov 19, 2022-Dec 04, 2022
    | DENMARK (2022)          1,549        MX     Nov 02, 2022-Feb 01, 2023
    | FRANCE (2022)           1,575       INT     Apr 28, 2022-May 26, 2022
    | MONTENEGRO (2023)       1,200       F2F     Oct 14, 2023-Oct 30, 2023
    | NEW ZEALAND (2023)        910        MX     Oct 18, 2023-Mar 09, 2024
    | NORTH MACEDONIA (2024)  1,055       F2F     Oct 25, 2024-Dec 04, 2024
    | POLAND (2023)           1,500       F2F     Nov 07, 2023-Dec 16, 2023
    | PORTUGAL (2022)         1,010       F2F     Feb 11, 2022-Mar 07, 2022
    | PORTUGAL (2024)         1,001       F2F     Apr 27, 2024-May 07, 2024
    | SLOVAKIA (2023)         1,021       F2F     Jan 31, 2024-Feb 26, 2024
    | SLOVENIA (2022)           855        MX     Sep 26, 2022-Dec 03, 2022
    | SWEDEN (2022)           2,845        MX     Sep 13, 2022-Jan 04, 2023
    | SWITZERLAND (2023)      5,033        MX     Oct 23, 2023-Jan 11, 2024
    | TAIWAN (2024)           1,206       F2F     Jan 15, 2024-May 31, 2024
    | TURKIYE (2023)          1,508       F2F     Aug 25, 2023-Oct 04, 2023
    | UNITED STATES (2024)    4,764        MX     Nov 07, 2024-Feb 19, 2025
    | ---------------------------------------------------------------------
    | TOTAL                  33,871  
    | 
    | Key:  F2F=Face-to-face.
    |       TP=Telephone.  
    |       INT=Internet/Online.
    |       MX=Mixed. 
    |
    | Users are advised to consult the VARIABLE NOTES for Variables F1019_
    | in Codebook Part 2 concerning fieldwork date classifications.

Users are advised that the above information relates to this Advance 
Release. The product is still in development, and data will be added 
gradually. Many election studies and variables that will eventually be 
present in the CSES Module 6 Full Release are unavailable in this version 
of the file. 


---------------------------------------------------------------------------
>>> MICRO-LEVEL (SURVEY) COMPONENT
---------------------------------------------------------------------------

The core questionnaire ("Module") of CSES MODULE 6 was intended to be
administered as a single, uninterrupted block of questions in a nationally
representative post-election survey in each polity.

A) The question text is included in the variable documentation of this
   Codebook. The questions are reported in the order in which they appear
   in the CSES questionnaire. For some questions, Collaborator instructions
   for administering the CSES Questionnaire were important. These are 
   reported in the next section.

B) Where there are known differences in the way a particular question was
   administered in an election study, this is noted in the "Election Study
   Notes" following the documentation of the corresponding variable.

C) There are several sets of party and leader evaluation items included
   in the module. These correspond to parties labeled A-F, in descending
   order of vote share, of the six most popular parties in the main 
   election (unless stated otherwise). Where respondents were asked to 
   evaluate other parties, these evaluations have been included where 
   possible and are labeled parties G-I, regardless of their vote shares. 
   The parties and leaders to which these evaluations apply are identified
   in Codebook Part 3.

D) There are several questions (including the vote choice and party
   identification items) that ask the respondents to specify a political
   party. The codes for these items are also reported in Codebook Part 3.


---------------------------------------------------------------------------
>>> CSES MODULE 6 COLLABORATOR INSTRUCTIONS FOR THE ADMINISTRATION OF THE
    CSES QUESTIONNAIRE
---------------------------------------------------------------------------

The following instructions appeared in the header to the questionnaire for
CSES MODULE 6, as instructions to Collaborators regarding the implementation
of the questionnaire:

  ( 1)  Following these collaborator instructions, this document is 
        comprised of three sections:

        ))) CSES MODULE 6 QUESTIONNAIRE: ADMINISTRATIVE VARIABLES

        The "Administrative Variables" section is a list of common
        administrative variables that, if possible, should be provided at
        the time data are deposited with the CSES Secretariat.

        ))) CSES MODULE 6 QUESTIONNAIRE: CSES MODULE

        This is the CSES Module itself, a common module of survey questions
        for researchers to include in their national post-election survey.
        The CSES Module is intended to be administered exactly as it is
        specified in this document.

        ))) CSES MODULE 6 QUESTIONNAIRE: DEMOGRAPHIC VARIABLES

        Collaborators are asked to provide data on background (demographic)
        characteristics of respondents, coded to an agreed upon set of
        standards as indicated in this section. There is great
        international variation in the ways that collaborators will go
        about soliciting information on the background characteristics of
        their respondents. The objective here is not standardization of the
        way collaborators ask these background questions, but instead,
        standardization to a common, cross-national scheme for coding each
        variable.

  ( 2)  The CSES Module (consisting of the questions which are named 
        beginning with the letter "Q") is intended to be administered in
        its entirety as a single, uninterrupted block of questions, unless 
        noted otherwise for particular questions. In most cases, the CSES 
        Module is included as part of a larger study. For reliable 
        comparisons to be made, it is important that any additional items
        investigators may wish to include do not interrupt the CSES Module.

  ( 3)  The CSES module should be administered as a post-election
        interview.

  ( 4)  Where the CSES module is included in a larger study, to ensure that
        question-ordering effects are minimized, collaborators should be
        sensitive to the effects questions asked immediately prior to the
        module may have.

  ( 5)  NOTES often precede the question TEXT, and provide instructions for
        the administration of the item. Where no question TEXT is provided,
        collaborators should provide documentation of the question used.

  ( 6)  Showcards may be helpful for the administration of some questions.
        For this reason, a Respondent Booklet is available for download
        from the CSES website. The Respondent Booklet contains showcards
        for select questions. It is indicated in the NOTES when a showcard
        is available for a question.
        
  ( 7)  The response options that should be read to the respondent are
        contained in the body of the question TEXT.

  ( 8)  Where lower-case words appear in brackets [ ] collaborators should
        select the words that are most appropriate.

        For example:
        [party/presidential candidate]
        ...indicates that either the word "party" or the phrase
        "presidential candidate" should be read, but not both.

  ( 9)  Where upper-case words appear in brackets [ ] collaborators should
        substitute the words that are most appropriate.

        For example:
        [COUNTRY]
        ...should be replaced with the name of the country where the
        election was held (perhaps "Canada" or "the Philippines").

        Another example:
        [NUMBER OF YEARS BETWEEN THE PREVIOUS AND THE PRESENT ELECTION
        OR CHANGE IN GOVERNMENT]
        ...should be replaced with a number that indicates the amount of
        years that have passed between the previous election and either the
        current election or recent change in government.

  (10)  Phrases that appear in parentheses ( ) contain words that are
        optional - that collaborators (or their interviewers) can decide to
        read or not read to respondents as needed.

  (11)  Words in question text that are in upper-case but NOT within 
        brackets [ ] should be emphasized by the interviewer when reading
        the question text. 
        
        For example, the word "COUNTRY" would be emphasized in the
        following question when the interviewer reads the question to the
        respondent:
        
        What COUNTRY do you live in?
        
        But in this next example, the interviewer does not emphasize the
        word "[COUNTRY]". Instead, this is an instruction for the
        collaborator to substitute the name of the respondent's country
        into the question text (for more information, see the eighth
        Collaborator Instruction above):
        
        How long have you lived in [COUNTRY]?
                        
  (12)  Interviewer instructions are available for some questions. These
        interviewer instructions, labeled as HELP, are intended to
        provide advice to the interviewers to assist in administering the
        question. It is also useful to discuss the interviewer instructions
        as part of interviewer training. The interviewer instructions, 
        where available, appear after the question TEXT. In 
        interviewer-administered surveys, interviewer instructions should
        be available to the interviewer, but not to the respondent. For
        example, in a computer-assisted interview, the interviewer
        instructions might appear on the screen in a special color, and
        interviewers trained to make use of those instructions as
        necessary, but the interviewer should NOT read the interviewer
        instructions to the respondent.
        
  (13)  Some response options are followed by an arrow (->) and a skip
        pattern instruction. If the respondent selects that response 
        option, the skip pattern instruction after the arrow is to be
        executed.

  (14)  Respondents who volunteer the response "DON'T KNOW" (or who have
        REFUSED to answer a question) should be coded as such. Interviewers
        should accept these responses and should NOT probe for additional
        information or force a respondent to use one of the response
        options provided in the text of the question.

  (15)  Special care should be taken in the administration of the Vote 
        Choice items (Q10 and Q14 question series).
        
        Wording for the Q10 and Q14 question series, which is to record
        vote choice in the elections, should follow national standards. 
       
        Collaborators are invited to compare their own national instrument
        with other instruments of countries that are part of the CSES and
        look for convergence where this is possible.
        
        For Q14 (previous election), ask about the previous national 
        election of the same type (whether legislative or presidential).
        For countries where more than one institution is being currently
        elected on the same day (e.g., president and legislature), please 
        consider asking about the previous lower house election if votes
        have been recorded for the current lower house election. 
        
        For Q10 (current election), for countries where more than one 
        institution is elected on the same day (e.g., president and 
        legislature) using different votes, please ensure that all votes
        are supplied. Consider including all national elections having been
        held within three months before the study's data collection period.
        
        Please ensure all vote choices are supplied as separate variables
        in the dataset that you deposit.
        
        For countries where voters have two votes for the same institution
        (e.g. parallel and mixed member proportional systems; double
        ballot systems), please ensure that both/all votes are supplied.
        
        For countries using preferential systems (e.g., STV, AV) please
        provide first and second preference vote.
          
  (16)  For questions asking about parties, collaborators should be advised
        that they may add one or several party blocs to a list of
        individual parties if they feel that it will be difficult for
        respondents to recognize individual parties.   
        

---------------------------------------------------------------------------
>>> DISTRICT-LEVEL COMPONENT
---------------------------------------------------------------------------

The district-level variables report relevant election result data (mostly
pertaining to the lower house elections) for each respondent's district. 
Wherever possible, these data were collected from official sources (see
CSES MODULE 6 Codebook Part 2 and Bibliography in Part 1 for details). 
In other cases, CSES has been grateful for the compilation of these data 
provided by third-party sources.

Parts 2 and 4 of the CSES MODULE 6 Codebook provide more information on 
the district data, including details of any polities where we deviate from 
the CSES conventions as well as the sources of the data for each polity. 


---------------------------------------------------------------------------
>>> MACRO-LEVEL COMPONENT
---------------------------------------------------------------------------

To supplement the micro (individual survey level) data, CSES augments this 
data with macro and contextual data. CSES has been a pioneer in this field 
having included a macro data component in its products since its inception 
in 1996. There are two types of macro data included in CSES: 
   -  System/polity macro data 
   -  Aggregated macro data 

System/polity level data refers to data about the polity or contextual 
characteristics. These are often sourced from official documents like 
constitutions, electoral laws, government information pages, or expert 
judgments.  

Aggregated macro data summarizes data about lower-level units into a 
higher-level unit. Economic indicators such as gross domestic product (GDP) 
or unemployment data for a country fall into this classification. 

The CSES Planning Committee, the project governing board, specifies the 
specific macro data to collect for each CSES Module after consultation with 
the CSES Secretariat. The rationale for collecting specific macro variables 
is usually specified in CSES Planning Committee reports on the particular
module. 

CSES macro data is principally collated from two sources, namely: 
-   The CSES Macro Report 
-   The CSES Secretariat 

The CSES Macro Report is a detailed questionnaire completed by national 
Collaborators who field the CSES study. This Report allows CSES to collect 
certain macro information consistently from national-level experts. 
Moreover, as polities participating in CSES are only sometimes available 
from other comparative datasets, it ensures macro data is available for all 
elections and polities. The CSES Secretariat reviews Macro Reports as 
provided by Collaborators before publication. These reports can be accessed 
on the CSES website in the "CSES Module 6 Election Study Archive" at the 
bottom of the CSES Module 6 Download page.

The CSES Secretariat is comprised of macro experts - individuals who have 
substantial expertise (usually at the post-doctoral level) in the political 
dynamics and electoral systems of many of the polities in CSES. They are 
tasked with collating macro data from other sources, including comparative 
databases such as the World Bank and Freedom House, and bringing their 
expertise to classifying election results. They are also tasked with 
harmonizing these data and providing additional user guidance where 
necessary. Sources consulted for these macro level data are listed as 
appropriate in the Bibliography section at the end of this part of the 
CSES Codebook.
 

===========================================================================
))) CSES MODULE 6 DOCUMENTATION - WHAT'S AVAILABLE AND HOW TO USE?
===========================================================================

There are several components to the CSES documentation. We detail each form 
below: 

---------------------------------------------------------------------------
>>> CSES CODEBOOK OVERVIEW
---------------------------------------------------------------------------

The primary documentation component is the CSES MODULE 6 Codebook. 
The Codebook consists of five components, namely: 

1) PART 1: INTRODUCTION 
   (file name: cses6_codebook_part1_introduction.txt)
   Part 1 (This file) overview of the CSES study and data, information  
   about how to use the files, information on the CSES data file, the 
   checks the CSES Secretariat conducts on the data file and information on
   the national Collaborators of the CSES project for each polity.  

2) PART 2: CSES VARIABLES DESCRIPTION
   (file name: cses6_codebook_part2_variables.txt)
   Part 2 is the Variable Description file and includes the survey 
   questions, code frames, general variable notes, election study notes, 
   and details about sources for macro data. 

3) PART 3: PARTIES AND LEADERS BY POLITY 
   (file name: cses6_codebook_part3_parties_and_leaders.txt)
   Part 3 details the party/coalition and leader numerical and alphabetical
   classifications for each polity included in the CSES MODULE 6 dataset. 

4) PART 4: PRIMARY ELECTORAL DISTRICTS RESPONDENTS BY POLITY
   (file name: cses6_codebook_part4_primary_electoral_districts.txt)
   Part 4 details the primary electoral district by polity for each 
   respondent included in the CSES MODULE 6 dataset. 

5) PART 5: STUDY DESIGN AND WEIGHTS OVERVIEW BY POLITY
   (file name: cses6_codebook_part5_designs_and_weights.txt)
   Part 5 contains overviews of the design of each election study included 
   in CSES MODULE 6. It also provides analysts with details regarding the 
   polity weights provided by each election study. 

The CSES MODULE 6 questionnaire is also available from the website or
by referencing the corresponding variables in this Codebook.

For all election studies included in CSES, Collaborators have provided 
documentation to accompany their election studies. These documents, 
where available, can be found on the CSES MODULE 6 download page.

Analysts will also want to become familiar with the CSES MODULE 6 errata
page. It is accessible from the CSES MODULE 6 download page on the CSES 
website in the white box to the right of the page. Information, updates, 
and error notifications and corrections are posted there, in real time, 
as they become available. Please regularly check for errata notifications 
to keep up to date.


---------------------------------------------------------------------------
>>> CSES CODEBOOK CONVENTIONS
---------------------------------------------------------------------------

The CSES project uses American English language and date standards 
(MM-DD-YYYY). In the CSES MODULE 6 dataset, all variables begin with the 
letter "F" (F being the sixth letter of the English alphabet and thus 
signifying MODULE 6). This convention helps reduce the possibility of 
overwriting data when merging with other CSES datasets.

Variables are presented in six groupings:

1) F1001-F1999 Identification, weight, and election study variables

2) F2001-F2999 Demographic data

3) F3001-F3999 Micro-level (survey) data (the CSES MODULE 6 questionnaire)

4) F4001-F4999 District-level data

5) F5000-F5999 Macro-level data

6) F6000-F6999 IMD bridging Variables

In the Variable Descriptions portion of the CSES MODULE 6 Codebook (Part 2),
the headers for individual variables are surrounded by two lines of dashes. 
Variable names do not exceed eight characters in length.


---------------------------------------------------------------------------
>>> CSES CODEBOOK - VARIABLE NOTES AND ELECTION STUDY NOTES
---------------------------------------------------------------------------

<<>> VARIABLE NOTES

Variable Notes provide information on the rationale of a variable 
as well as source information for that variable. It also details the 
polities for which no data for that particular variable are available. 
VARIABLE NOTES are listed below the descriptive information for the said
variable and can be navigated in the Codebook by searching for 
"VARIABLE NOTES" in Part 2 of the CSES Codebook. 


<<>> ELECTION STUDY NOTES

A unique dimension of the CSES are the inclusion of ELECTION STUDY NOTES. 
They are notes which are attached to each variable included in the dataset
and refer to case specific information regarding a particular variable. 
Their purpose is to provide users with more detailed information on the 
case or explain important deviations specific to cases from CSES 
conventions. They are also used to provide source data information for 
users. Where applicable, ELECTION STUDY NOTES are listed below a particular
variable and any VARIABLE NOTES in Parts 2 and 3 of the CSES Codebook. 
They can be navigated in the Codebook by searching for "ELECTION STUDY 
NOTES" in Parts 2 and 3 of the CSES MODULE 6 Codebook.


---------------------------------------------------------------------------
>>> CSES ORIGINAL QUESTIONNAIRE FOR MODULE 6
---------------------------------------------------------------------------

The CSES MODULE 6 original questionnaire is available from the CSES Module 
6 study page at: 
         https://cses.org/data-download/cses-module-6-2021-2026/   
         
or by referencing the corresponding Variable Descriptions in this Codebook 
(see Part 2).


---------------------------------------------------------------------------
>>> CSES - ADDITIONAL DOCUMENTATION
---------------------------------------------------------------------------

All election studies included in CSES provide numerous source material. 
These documents include the following: 
      - Macro Reports. 
      - Design Reports. 
      - Original questionnaires including in the language of origin. 

We describe each in turn below. 


<<>> MACRO REPORT

Collaborators submit a Macro Report to the CSES Secretariat when depositing
their national data. Its purpose is to provide a coherent link between 
national level specialists and data specific to the election and polity 
in question. It provides information on the election, the composition of 
cabinet before and after election, expert assessments of the parties, 
information on electoral rules operating in the polity, as well as original
sources for the polity level data. It aids the CSES Secretariat in 
collating some of the macro level data for each polity included in the 
study. Where available, Macro Reports can be found on the CSES MODULE 6 
download page under "CSES MODULE 6 Election Study Archive" at:
https://cses.org/data-download/cses-module-6-2021-2026/


<<>> DESIGN REPORT

Collaborators also submit a Design Report to the CSES Secretariat when 
depositing their national data. It provides all information on the 
implementation of each individual election study including details
regarding fieldwork dates, mode of interview, sampling procedures, 
sampling frame, response and refusal rates, information on translation
procedures, and weights. Some of this data is included directly in the
CSES data in variables F1001-F1106. Where available, Design Reports can 
be found on the CSES MODULE 6 download page under "CSES MODULE 6 Election
Study Archive" at: https://cses.org/data-download/cses-module-6-2021-2026/

Further, Part 5 of the CSES MODULE 6 Codebook provides overviews of each 
polity's study design and polity level weights. It draws heavily on
information from each polity's Design Report.


<<>> ORIGINAL QUESTIONNAIRES

Where available, CSES provides the original language questionnaires from 
each polity's national election study. Further, CSES requests that all 
studies included provide the English language questionnaire used as the 
basis for translation of the CSES questionnaire into a polity's native
tongue(s). Where available, the questionnaires can be found on the CSES 
MODULE 6 download page under "CSES MODULE 6 Election Study Archive" at:
https://cses.org/data-download/cses-module-6-2021-2026/


===========================================================================
))) CSES MODULE 6 STUDY DATA AND CODEBOOK: ADDITIONAL INFORMATION
===========================================================================

---------------------------------------------------------------------------
>>> CODING OF PARTIES/COALITIONS & LEADERS
---------------------------------------------------------------------------

CSES classifies parties/coalitions in its dataset numerically and
alphabetically. Below we provide explanations of both of these coding
schemes. The details of each party/leader classification are available in  
Part 3 of the CSES MODULE 6 Codebook. 

<<>> CSES NUMERICAL PARTY/COALITION CODING

Each party/coalition is assigned a unique numerical code which consists of  
two components and six digits in total:
    - the first three digits indicate the numerical country UN code
    - the latter three digits indicate the numerical party code within
      the given election study.

All parties/coalitions or Presidential candidates, where applicable,
participating in the election or the previous election receive a numerical
code. These codes are used to identify the following: 
    - who a respondent voted for in the current election (variables F3011_).
    - who the respondent voted for in the previous election 
      (variables F3016_).
    - the respondent's party identification (variable F3023_3).
      
The numerical coding is also used to identify macro level information about
the parties/coalitions, namely:
    - numeric party code identifiers for relational data (variables F5000_)
    - numeric party code identifiers for leaders' party affiliations
      (variables F5000_L_)   
    - which party/coalition held the Presidency before and after the
      elections (variable F5019_1 and F5019_2).
    - which party/coalition held the Prime Ministership before and after
      the elections (variable F5020_1 and F5020_2).
    - which party/coalition held the ministry of finance before and after
      the elections (variable F5023_1 and F5023_2).
    - which party/coalition held the foreign ministry before and after
      the elections (variable F5023_3 and F5023_4).
    - which party/coalition held the health ministry before and after
      the elections (variable F5023_5 and F5023_6).
     
Numerical codes assigned to parties/coalitions are consistent for the 
current and previous election.  

<<>> CSES ALPHABETICAL PARTY/COALITION CODING
 
Parties/coalitions A through F are the six most popular parties/coalitions, 
ordered in descending order of their share of the popular vote in the 
main election (unless otherwise stated). Thus, Party A is the 
party/coalition that received the most votes in the election, party B the 
second most votes, etc...

Parties/coalitions who achieve at least 1% of the vote nationally are
eligible for an alphabetical A-F assignment. In countries with multiple
electoral tiers and where one vote is cast, parties are ordered according
to their vote share in tier 1 (the lowest tier), unless otherwise stated.
In countries where voters have two votes (i.e.: a constituency and a list
vote) simultaneously, for example Germany, parties are ordered by the
national share of the party list vote (tier 2) unless stated otherwise.

Parties G, H, and I are supplemental parties. They may, but do not have to,
accord with how parties A-F are ordered, that is ordered on the popular 
share of the vote in a polity. More often, they are codified in no 
particular order. These parties are voluntarily provided by each polity's
election study and often reflect important or notable parties within a 
polity. They may also include data about individual parties within a 
coalition, where data about the coalition and the individual parties, 
or some of these parties that make it up, are provided.
These codes are used to identify the following in the micro component of 
the CSES dataset: 
    - Respondent's likeability of the party/coalition (variable F3018).
    - Respondent's left-right placement of the party/coalition (variable 
      F3020).
    - Respondent's placement of the party/coalition on an alternative 
      scale, if applicable (variable F3021).

These alphabetical codes are used to identify district and macro level
information about these said parties/coalitions, namely:
    - The said party/coalition's vote share in the respondent's electoral
      district (variable F4004).
    - the said party/coalition's share of the seats in the election in the
      respondent's electoral district (variable F4005).
    - the said party/coalition's share of the vote in the election 
      (variables F5001, F5003, F5005, and F5006).
    - the said party/coalition's share of the seats in the election 
      (variables F5002 and F5004).
    - the said party/coalition's share of cabinet portfolios before and 
      after the election (variables F5021 and F5022).
    - expert judgments by the national Collaborators of the said party/
      coalition's ideological family (variable F5028).
    - expert judgments by the national Collaborators of the said party/
      coalition's left-right placement (variable F5029).
    - expert judgments by the national Collaborators of the said party/
      coalition's placement on an alternative scale, if applicable 
      (variable F5030).
    - expert judgments by the national Collaborators of the said party/
      coalition's level of populism (variable F5031).
    - The said party/coalition's Manifesto Research on Political 
      Representation (MARPOR/CMP) Identifier (variable F5200).
    - The said party/coalition's Parliaments and Government Database
      (ParlGov) Identifier (variable F5201).
    - The said party/coalition's Chapel Hill Expert Survey (CHES) 
      Identifier (variable F5202).
    - The said party/coalition's Party Facts Identifier (variable F5203). 


<<>> CSES ALPHABETICAL LEADER CODING
         
Leaders A through F tend to be the leaders of the six most popular parties/
coalitions or the Presidential candidates of these parties. In most 
instances, they correspond to parties/coalitions A-F (i.e.: Leader A will 
be related to Party A in some way, Leader B will be related to 
Party B, etc.).

Leaders G, H, and I are supplemental leaders. They may be related to
parties G, H, I but they do not have to be. These leaders are voluntarily
provided by each polity's election study and often include data about
additional personalities of interest. For example, in a parliamentary
system, data about a President might be provided, even if the Presidency
is not being contested. On many occasions, slots Leader G, H, and I will
include additional data for parties/coalitions that have multiple leaders.
These codes are used to identify the following in the micro and macro
components of the CSES dataset: 
    - Respondent's likeability of the leader/personality in question
      (variable F3019).
    - the said leader/personality's biological sex (F5000_L_ABS-IBS).


---------------------------------------------------------------------------
>>> CSES DATA BRIDGING: NEW FRONTIERS IN DATA LINKAGE
---------------------------------------------------------------------------

Data Bridging enables users to bring together information from CSES with 
other data sources. The concept is part of CSES Data Linkage efforts. CSES
has been a pioneer of Data Linkage with the inclusion of various 
macro-level data originating from other sources (e.g., The World Bank, 
the IDEA) directly in CSES data products, including in CSES MODULE 6. These 
macro data classify the political system's characteristics and contextual 
conditions of a polity at the election time.  
Data Bridging gives users the power to build on the direct data linkage 
in CSES products by enabling users to easily link other data with CSES 
products. CSES MODULE 6 enables users to bridge data with other prominent 
datasets in political science by including standard identifiers at the
polity, year, and party level used by other projects to facilitate 
merging.

CSES MODULE 6 facilitates data bridging with other datasets at the polity 
level with the following variables:
    - F1006_UN       ID COMPONENT - POLITY UN ISO_3166-1 NUMERIC CODE
    - F1006_UNALPHA2 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC
                                    TWO LETTER CODE
    - F1006_UNALPHA3 ID COMPONENT - POLITY UN ISO_3166-1 ALPHABETIC
                                    THREE LETTER CODE
    - F1006_NAM      ID COMPONENT - POLITY NAME
    - F1007_VDEM     ID COMPONENT - V-Dem POLITY IDENTIFIER
    
More details can be found on all these variables in CSES Codebook Part 2
by searching for the variable name (e.g., "F1006_UN") or using the search
term "POTENTIAL POLITY LEVEL BRIDGING IDENTIFIER". 


CSES MODULE 6 facilitates data bridging with other datasets at the regional 
level through the following variables:  
    - F1007_REG      ID COMPONENT - POLITY UN GEOGRAPHIC REGIONS NUMERIC
                                    CODES
More details can be found on all these variables in CSES Codebook Part 2
by searching for the variable name (e.g., "F1007_REG") or using the search
term "POTENTIAL REGIONAL LEVEL BRIDGING IDENTIFIER". 


CSES MODULE 6 facilitates data bridging with other datasets by date through 
the following variables:  
    - F1009          ID COMPONENT - ELECTION YEAR
    - F1010_M        DATE 1ST ROUND ELECTION BEGAN - MONTH
    - F1010_D        DATE 1ST ROUND ELECTION BEGAN - DAY
    - F1010_Y        DATE 1ST ROUND ELECTION BEGAN - YEAR
    - F1010_1        DATE 1ST ROUND ELECTION BEGAN - YYYY-MM-DD
    - F1010_2        DATE 1ST ROUND ELECTION BEGAN - YYYYMM
    - F1011_M        DATE 2ND ROUND ELECTION BEGAN - MONTH
    - F1011_D        DATE 2ND ROUND ELECTION BEGAN - DAY
    - F1011_Y        DATE 2ND ROUND ELECTION BEGAN - YEAR
    - F1011_1        DATE 2ND ROUND ELECTION BEGAN - YYYY-MM-DD
    - F1011_2        DATE 2ND ROUND ELECTION BEGAN - YYYYMM                 

More details can be found on all these variables in CSES Codebook Part 2
by searching for the variable name (e.g., "F1009") or using the search
term "POTENTIAL TIME BRIDGING IDENTIFIER". 


CSES MODULE 6 facilitates data bridging with other datasets at the
party/coalition level with the following variables: 
    - F5200_A-I      MANIFESTO RESEARCH ON POLITICAL REPRESENTATION 
                     (MARPOR/CMP) IDENTIFIER - PARTY A-I
    - F5201_A-I      PARLIAMENTS AND GOVERNMENT DATABASE (PARLGOV) 
                     IDENTIFIER - PARTY A-I
    - F5202_A-I      CHAPEL HILL EXPERT SURVEY (CHES) IDENTIFIER - 
                     PARTY A-I
    - F5203_A-I      PARTY FACTS IDENTIFIER - PARTY A-I     
   
More details can be found on all these variables in CSES Codebook Part 2
by searching for the variable name (e.g., "F5200_A") or using the search
term "POTENTIAL PARTY/COALITION LEVEL BRIDGING IDENTIFIER."
Users can also see the specific bridging codes for each party/coalition
assigned an alphabetical code in CSES by other projects in Part 3 of the
CSES MODULE 6 Codebook.


CSES MODULE 6 facilitates data bridging with other CSES products at the
party/coalition level with the following variables:  
    - F6000_PR_1     IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION:
                     VOTE CHOICE - 1ST ROUND
    - F6000_PR_2     IMD BRIDGING VARIABLE: CURRENT PRESIDENTIAL ELECTION:
                     VOTE CHOICE - 2ND ROUND
    - F6000_LH_PL    IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION:
                     VOTE CHOICE: PARTY LIST
    - F6000_LH_DC    IMD BRIDGING VARIABLE: CURRENT LOWER HOUSE ELECTION:
                     VOTE CHOICE: DISTRICT CANDIDATE               
     
More details can be found on all these variables in CSES Codebook Part 2
by searching for the variable name (e.g., "E6000_PR_1") or using the search
term "POTENTIAL CSES PRODUCT BRIDGING IDENTIFIER". 


---------------------------------------------------------------------------
>>> DERIVATIVE VARIABLES
---------------------------------------------------------------------------

CSES MODULE 6 includes several Derivative Variables. A Derivative Variable 
is a variable that is derived from another variable or variables within the 
CSES. Their purpose is to facilitate speedier analysis for users with 
derivative variables capturing some of the most common analytical concepts 
in the discipline.

A list of the DERIVATIVE VARIABLES are below this explanation and can be
navigated in the Codebook by searching for DERIVATIVE VARIABLES in
Part 2 of the CSES MODULE 6 Codebook.
      
  - F2001_A         AGE OF RESPONDENT (IN YEARS) 
  - F2001_GG        BIRTH GENERATION: GREATEST GENERATION
                    (BORN 1927 OR BEFORE)  
  - F2001_GS        BIRTH GENERATION: SILENT GENERATION
                    (BORN FROM 1928 TO 1945)
  - F2001_GBB       BIRTH GENERATION: BABY BOOMERS
                    (BORN FROM 1946 TO 1964)
  - F2001_GX        BIRTH GENERATION: GENERATION X
                    (BORN FROM 1965 TO 1980)
  - F2001_GY        BIRTH GENERATION: GENERATION Y
                    (BORN FROM 1981 TO 1996)
  - F2001_GZ        BIRTH GENERATION: GENERATION Z
                    (BORN FROM 1997 ONWARDS) 
  - F3010_TS        TURNOUT SWITCHER BETWEEN CURRENT ELECTION AND
                    PREVIOUS ELECTION   
  - F3010_FTV       FIRST-TIME VOTER IN CURRENT MAIN ELECTION
  - F3011_OUTGOV    CURRENT MAIN ELECTION: VOTE CHOICE -  
                    OUTGOING GOVERNMENT (INCUMBENT)
  - F3011_VS_1      VOTE SWITCHER BETWEEN CURRENT ELECTION AND 
                    PREVIOUS ELECTION          
  - F3011_LR_CSES   CURRENT MAIN ELECTION - 
                    VOTE FOR LEFTIST/CENTER/RIGHTIST - CSES
  - F3011_LR_MARPOR CURRENT MAIN ELECTION - VOTE FOR LEFTIST/RIGHTIST (RILE)
                    - MARPOR/CMP
  - F3011_IF_CSES   CURRENT MAIN ELECTION - VOTE CHOICE BY
                    IDEOLOGICAL FAMILY CLASSIFICATION - CSES
  - F3100_LR_CSES   CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH
                    CSES COLLABORATOR EXPERT JUDGMENT L-R
  - F3100_LR_MARPOR CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH
                    MARPOR/CMP RILE  
  - F3100_POP_CSES  CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH
                    CSES COLLABORATOR EXPERT JUDGMENT ON POPULISM       
  - F3100_IF_CSES   CURRENT MAIN ELECTION - VOTE CHOICE LINKED WITH
                    CSES COLLABORATOR EXPERT JUDGMENT IDEOLOGICAL FAMILY
  - F5019_C         PARTY OF THE PRESIDENT CHANGED
  - F5020_C         PARTY OF THE PRIME MINISTER CHANGED
          

---------------------------------------------------------------------------
>>> IDENTIFICATION VARIABLES
---------------------------------------------------------------------------

There are several Identification Variables in CSES MODULE 6 which allow
users to not only identify an individual respondent, but election studies, 
and polities. 


<<>> ELECTION STUDY IDENTIFIERS

Each Election Study in CSES MODULE 6 is uniquely identified by two 
variables, namely: 

   - variable F1004 ID VARIABLE - ELECTION STUDY (ALPHABETIC POLITY)
     This variable is an alphanumerical code constructed from two
     components: the alpha-3 country codes assigned by the United Nations
     Statistics Divisions. The remaining characters correspond 
     to the year of the election. 
     E.g., TUR_2023

   - variable F1005 ID VARIABLE - ELECTION STUDY (NUMERIC POLITY)
     This variable is an eight-digit numerical code constructed from two
     components: the CSES polity code (variable F1006) and the 
     year in which the election took place (F1009). The first three digits
     represent the country codes assigned by the United Nations Statistics
     Division. The fourth digit distinguishes between multiple election
     studies within a single country for the same election. The final 
     four digits represent the year of the election. 
     E.g., 03602022. AUSTRALIA (2022)


<<>> POLITY IDENTIFIERS

Each Polity in CSES MODULE 6 is uniquely identified by four variables, 
namely: 

   - variable F1006_UN ID COMPONENT - POLITY UN ISO_3166-1 NUMERIC CODE
     This variable consists of the three-digit numerical country codes 
     assigned by the United Nations Statistics Division to polities
     in line with the International Organization for Standardization (ISO).
     The numerical codes are maintained by the United Nations Statistics 
     Division and are based on the M49 UN framework. 
     E.g., 036. AUSTRALIA

   - variable F1006_UNALPHA2 ID COMPONENT - POLITY UN ISO_3166-1 
     ALPHABETIC TWO LETTER CODE
     This variable consists of the two-letter country codes assigned by 
     the United Nations Statistics Division to polities based on the 
     International Organization for Standardization (ISO). The lettered
     codes are maintained by the ISO as part of their ISO3166-1 standard. 
     E.g., DK. Denmark (DK=Denmark)

   - variable F1006_UNALPHA3 ID COMPONENT - POLITY UN ISO_3166-1 
     ALPHABETIC THREE LETTER CODE
     This variable consists of the three-letter country codes assigned by 
     the United Nations Statistics Division to polities based on the 
     International Organization for Standardization (ISO). The lettered
     codes are maintained by the ISO as part of their ISO3166-1 standard. 
     E.g., PRT. Portugal (PRT=Portugal)

   - variable F1006_NAM ID COMPONENT - POLITY NAME
     This variable consists of polity names based on those used by the
     United Nations Statistics Division. 
     E.g., France

These polity identifiers allow for easy data bridging with other macro
data sources such as the World Bank. 


<<>> POLITY GEOGRAPHIC IDENTIFIERS

   - variable F1007_REG ID COMPONENT - POLITY UN GEOGRAPHIC REGIONS NUMERIC
                                       CODES
     This variable consists of a two-digit numerical code assigned by the
     United Nations Statistics Division to polities based on their 
     geographic (continental) region. Each polity is shown in one 
     region only. 


<<>> POLITY MEMBERSHIP IDENTIFIERS

CSES MODULE 6 classifies whether each polity was a member of two 
international organizations at the time of the election, namely the  
Organization for Economic Cooperation and Development (OECD) and the  
European Union (EU).

   - variable F1007_OECD ID COMPONENT - POLITY MEMBER OF OECD
     This variable classifies whether polity was a member of the 
     Organization for Economic Cooperation and Development (OECD) at the
     time of the election. 

   - variable F1007_EU ID COMPONENT - POLITY MEMBER OF EU
     This variable classifies whether polity was a member of the European
     Union at the time of the election. 


<<>> RESPONDENT IDENTIFIER

Respondents can be uniquely identified in the dataset by variable F1003_1. 
It is an 18-character identifier. The first three characters are the numeric
version of the country codes assigned by the United Nations Statistics
Division. If applicable, the fourth character distinguishes between 
multiple studies conducted within a single country, for the same election. 
If only one study is in place for the election, this digit is 0. The fifth
through eighth characters correspond to the election year (see variable
F1009). The last ten characters are the respondent identifier from F1003_2,
which is unique within each election study.


<<>> COVID-19 PANDEMIC IDENTIFIER

Some studies were conducted either partially or completely during the 
COVID-19 pandemic. A pandemic is an epidemic of infectious disease that has 
spread across a large region or multiple or worldwide and affecting a
substantial number of individuals.                   
At the time of writing, COVID-19 was first discovered in November
2019. Prior to the onset of CSES MODULE 6, the World Health Organization
classified COVID-19 as a pandemic on March 11, 2020.
On May 5, 2023, the WHO assessed that given the disease was by now well 
established and ongoing, it no longer fit the definition of a Public Health
Emergency of International Concern (PHEIC) and hence the state of a global
emergency.
An election (or election study) in CSES MODULE 6 is classified as taking
place during the COVID-19 pandemic if the election itself took place and/or
the entire study fieldwork was administered before May 5, 2023, the end
date of the WHO PHEIC classification. CSES classifies whether the election
took place after, partially, or fully during the pandemic - this is 
identified in the dataset by variable F1012_2.


---------------------------------------------------------------------------
>>> MISSING DATA
---------------------------------------------------------------------------

Multiple response categories can relate to missing data relating from 
not applicable to a respondent refusing to answer or failing to answer 
a question. Users should consult individual variables for the specific
missing designations assigned to each variable. 

For some election studies in which we could not distinguish among various
answers, the code "missing" may include cases where respondents refused 
to answer the question, "don't know" responses, and cases where there
a particular question went unanswered for other reasons.
Moreover, while CSES guidelines request that the response categories 
"Refused" and "Don't Know" be volunteered responses, this was not always 
consistently applied. For instance, sometimes the options were offered 
explicitly to respondents in mail-back surveys, which do not have the 
benefit of an interviewer being present. To identify whether the response 
options were volunteered (or not) in a particular election study, users 
should refer to the original questionnaires of each polity. These are
available on the MODULE 6 page. 

While there is no consistent CSES convention regarding the application of
missing values, some commonalities exist, namely: 
- Not applicable values are commonly designated as 7, 97, 997, 9997 etc...
- Don't know values are commonly designated as 8, 98, 998, 9998 etc... 
- Missing values are commonly designated as 9, 99, 999, 9999 etc...

However, users are advised that the commonalities do not always hold
and they are advised to consult individual variables for the specific
missing designations assigned to the variable in question. 


---------------------------------------------------------------------------
>>> WEIGHTS
---------------------------------------------------------------------------

CSES provides several weight measures in the CSES data (see variables 
F1101-F1105 inclusive). There is a strong degree of variance in the sample 
designs used in the national election studies included in CSES. Hence, the
weights provided by Collaborators vary significantly. Users are advised
to read carefully about the different weights in CSES to ascertain
whether their analyses should be subjected to weighting and if so which
kind. 

CSES provides users with up to three original weights from each national
election study (see variable F1101_) namely:

  - SAMPLE WEIGHT (variable F1101_1): 
    intended to correct for unequal selection probabilities resulting from 
    booster samples procedures for selection within the household, 
    non-response, or other sample design features 

  - DEMOGRAPHIC WEIGHT (variable F1101_2): 
    intended to adjust sample distributions of socio-demographic 
    characteristics to more closely resemble the characteristics of the 
    population

  - POLITICAL WEIGHT (variable F1101_3): 
    intended to reconcile discrepancies in the reported electoral behavior
    of respondents' vis-a-vis official electoral counts. 

For more information on polity weights, users are advised to consult Part 5
of the CSES Codebook or the individual design reports of each study. 

The remainder of the weight variables in the dataset are derivative
weights, constructed from the original weights. They are: 
 
  - FACTOR WEIGHTS (variable F1102)
    These variables report the mean weight of each type, within each 
    polity. The resulting factors are then used to create the derivative 
    Polity Weights (variable F1103 explained below). 

  - POLITY WEIGHTS (variable F1103)
    These variables report standardized versions (with a mean 1 within the 
    polity) of the original weights provided with the component election 
    studies, described in F1101. They are the ratio of each weighting 
    factor to the mean weight (F1102) of each type, calculated within each
    polity.

  - SAMPLE SIZE ADJUSTMENT WEIGHT (variable F1104)
    This variable reports the ratio of the average sample size to each 
    election study sample. The resulting factor is then used to create the
    derivative Dataset Weights, see variable F1105. 

  - DATASET WEIGHTS (variable F1105)
    These variables are intended for micro-level analyses involving the 
    entire CSES sample. Using the sample size adjustment (F1104), the 
    centered weights (F1103) are corrected such that each election study
    component contributes equally to the analysis, regardless of the 
    original sample size. 

Details of the calculation of the above derivative weights, including 
the precise STATA code used to create the weights, can be found in the 
variable notes for variables F1102, F1103, F1104, and F1105.     

Analysts are advised to read the weight documentation carefully to ensure
their analyses are weighted appropriately (if applicable). The CSES 
project does not provide advice as to which weights are appropriate to 
use in particular circumstances. This is best left to analysts to decide 
based on their detailed knowledge of the research question under 
investigation. We advise analysts to consult variable notes F1101-F1105
for more specific information on each polities weight and the derivative 
weights calculated for the Cross-National Dataset.


---------------------------------------------------------------------------
>>> FREEDOM STATUS OF ELECTIONS
---------------------------------------------------------------------------

The majority of studies that comprise CSES are collected in countries that
have free or partly free elections. However, sometimes a Collaborator will
include the CSES module in a study of a polity that is a developing
democracy or that is considered not free. If the data collection is judged
to be of sufficiently high quality, the study is included in CSES datasets
even if the polity is considered to be not free. The decision regarding
inclusion of particular polities in an analysis is thus left to users. 

To assist users in making appropriate decisions concerning their 
analysis, CSES MODULE 6 includes two measures about the freedom 
and liberty of a polity in the year the election was held (and indeed
the two preceding years), namely: 

   - FREEDOM HOUSE RATING (variables F5070_)
     Freedom House assigns a numerical rating of a polity on a scale of 
     1 to 7 providing an indication of freedom. 

   - POLITY IV DEMOCRACY-AUTOCRACY RATING (variables F5071_)
     Polity IV assigns a numerical rating to a polity on a scale of -10 
     to 10 indicating whether the polity is strongly democratic or strongly
     autocratic. These data are last available for the years 2016-2018. 

Freedom House and Polity IV are not affiliated with the CSES project.


---------------------------------------------------------------------------
>>> PROCESSING CHECKS OF MODULE 6 DATASET BY THE CSES SECRETARIAT
---------------------------------------------------------------------------

Besides processing MODULE 6 studies from individual polities to ensure they
are fit for comparative analysis, which involves detailed checking of the 
individual studies' data, a key role of the CSES Secretariat is to perform
several checks on the MODULE 6 Dataset before it is released. These checks
include (but are not confined to): 

   - CHECK OF DUPLICATE IDs
     Identification of respondents with corresponding answers to all 
     questions or respondent identification data that are similar. 

   - DERIVATIVE VARIABLES CHECKS
     To identify all derivative variables created by the CSES Secretariat
     are coded in line with original variables and documented in the CSES
     Codebook comprehensively. 

   - INCONSISTENCY CHECKS
     To identify sets of variables which are inconsistent, or could be 
     perceived as inconsistent (e.g., strange skip pattern, incompatible
     answers to related questions). The CSES convention is not to change 
     data that we receive from national Collaborators. Instead, 
     inconsistencies are noted in the CSES Codebook under the appropriate
     variable and the data are left unchanged. This allows users to make
     the final determination on whether inconsistencies may affect their
     analyses.  

   - IRREGULAR AND EXTRAORDINARY CODE CHECKS 
     To identify irregular and extraordinary codes in the CSES MODULE 6 
     Dataset. Sometimes these irregular or extraordinary codes are 
     legitimate in the sense that they may be accounted for by a polity
     deviation on a particular variable.

   - THEORETICAL CHECKS  
     These checks explore expected relationships between variables that 
     we might expect to occur (e.g., correlation between Political Efficacy
     and Satisfaction with Democracy). We do this by exploring 
     distributions, correlation analysis, and regression analysis. 

   - VARIABLE AND VALUE LABEL CHECKS
     Checking all variables in the CSES MODULE 6 Dataset to ensure they
     are appropriately assigned labels and documented in the CSES Codebook. 

   - INTERVIEW(ER) VALIDATION CHECKS
     Review performed at the respondent and interviewer levels using 
     various statistical techniques to identify anomalous response 
     patterns in the data (e.g., identification of highly similar 
     interviews, straightlining, unusually high proportion of interviews 
     conducted by an individual interviewer on a single day).

If you identify any potential issue with the CSES MODULE 6 data, 
please contact the CSES Secretariat by e-mail at: cses@umich.edu 


===========================================================================
))) CSES MODULE 6 BIBLIOGRAPHY
===========================================================================

The below list constitutes a list of the primary sources that the CSES 
Secretariat has consulted in the development of CSES MODULE 6 Codebook and
Data. The list is not exhaustive. 

Please note: Period symbol at end of URL addresses may be considered a full
stop or could be part of the URL address.

Aylott, N. and N. Bolin. 2023. "A new right: the Swedish parliamentary
election of September 2022". West European Politics 46(5): 1049-1062. 
DOI: 10.1080/01402382.2022.2156199

Bendjaballah, S. and N. Sauger. 2023. France: Political developments
and data for 2022: Back to normal?. European Journal of Political Research
Political Data Yearbook (62) 1:, 167-189. DOI: 10.1111/2047-8852.12403 

Delivorias, A. and E. Lazarou. 2023. "Brazilian democracy in the aftermath
of 8 January". European Parliament Briefing PE 739.354 - February 2023. 
Available at: 
https://www.europarl.europa.eu/RegData/etudes/BRIE/2023/739354/EPRS_BRI
(2023)739354_EN.pdf (Date accessed: August 9, 2024).

Doctor, M. 2022. "What Happens in Brazil Won't Stay in Brazil: The 2022 
Brazilian Elections." Political Insight 13(3): 8-11. 
DOI: 10.1177/20419058221127464 

Enns, Peter K. et al. (2025). "Understanding Bidens Exit and the 2024
Election: The State Presidential Approval/State Economy Model."
PS: Political Science & Politics. April 2025, pp. 298 - 305.
DOI: https://doi.org/10.1017/S1049096524000994 

Hansen, K. M. and R. Stubager. 2023. "The Danish National Election Study 
2022". CVAP Working Paper Series 5, Copenhagen: Department of Political
Science, University of Copenhagen. Available at: 
https://digidata.rigsarkivet.dk/aflevering/51035 
(Date accessed: May 14, 2024).

Jacobson, Gary C. (2025). "The 2024 Presidential and Congressional
Elections: Small Wave, Seismic Effects." Political Science Quarterly,
Volume 140, Issue 3, Fall 2025, Pages 439473.
DOI: 10.1093/psquar/qqaf050

Krasovec, A. 2023. "Slovenia: Political Developments and Data in 2022
A Year of Elections and Political Changes." European Journal of Political
Research. Political Data Yearbook. 62 (1): 448-471. 
DOI: 10.1111/2047-8852.12409.

Lajh, D. Novak, M. 2024. "Politicization of the European Union in Slovenia
in the Twenty Years of its Membership." Politics in Central Europe. 20 (3)
331.353. DOI: 10.2478/pce-2024-0015.

Lavrelashvili, T. 2020. "Party Passport: North Macedonia". European Party 
Monitor, Brussels/Leuven, available at: https://soc.kuleuven.be/io/english/
european-party-monitor/north-macedonia/north-macedonia 
(Date accessed: June 27, 2025).

Lindskog, H., S. Dahlberg, R. Ohrvall and H. Oscarsson. 2024. "The Voter 
Next Door: Stigma Effects on Advance Voting for Radical Right Parties". 
Political Studies 72(4): 1591-1608. DOI: 10.1177/00323217231216305

Lopes, H. F. 2023. "An unexpected Socialist majority: the 2022 Portuguese
general elections." West European Politics 46 (2): 437-450. 
DOI: 10.1080/01402382.2022.2070983.

Lopes, H. F. 2025. "Radical right advance and party system change: the 2024
Portuguese snap elections." West European Politics 48 (1): 228-245. 
DOI: 10.1080/01402382.2024.2372752.

Magone, J. M. 2022. "Portugal: Political Developments and Data in 2021
An Election Year and the Dismissal of the Costa II Government." European
Journal of Political Research 61 (1): 374-384.
DOI: 10.1111/2047-8852.12383.

Markowski, R. 2006. "The polish elections of 2005: Pure chaos or a 
restructuring of the party system?". West European Politics 29(4): 814-832.
DOI: 10.1080/01402380600842452.

OSCE. Office for Democratic Institutions and Human Rights (ODIHR). 2024.
"Republic of North Macedonia. Presidential and Parliamentary Elections 24 
April and 8 May 2024. ODIHR Election Observation Mission Final Report."
https://www.osce.org/files/f/documents/5/e/576648.pdf
(Date accessed: June 27, 2025).

Santana-Pereira, J. & Rogerio Nina, S. "The relevance and resilience of the
cordon sanitaire in Portugal: the March 2024 legislative elections." TFO
Collections (The Radical Right in Southern Europe): 243-268.
DOI: 10.1080/13608746.2024.2413857.

Superior Electoral Court Brazil (TSE), International Affairs Unit. 2022.
Practical Guide: 2022 Brazilian Elections. Brasilia: Tribunal Superior 
Eleitoral. https://international.tse.jus.br/en/assuntos-internacionais/
guia-pratico-para-pessoas-estrangeiras_ingles_digital-1.pdf 
(Date accessed: October 14, 2024).

Tarouco, G. 2023. Brazilian 2022 general elections: process, 
results, and implications. Revista Uruguaya de Ciencia Politica 32(1): 
153-168. DOI:10.26851/rucp.32.1.7 

Treneska, J., T. Smilevski, G. Hadzi Janev and A. Sofeska. 2024. "Handbook
on 2024 Parliamentary Elections in the Republic of North Macedonia". 
Handbook by Konrad Adenauer Foundation, Office in Skopje (KAS) and the 
Institute for Democracy "Societas Civilis" (IDSCS). Available at: 
https://www.kas.de/en/web/nordmazedonien/single-title/-/content/
handbook-on-2024-parliamentary-elections-in-the-republic-of-north-macedonia
(Date accessed: June 27, 2025).

Tworzecki, H. 2019. "Poland: A Case of Top-Down Polarization". The ANNALS 
of the American Academy of Political and Social Science 681(1): 97-119. 
DOI: 10.1177/0002716218809322.

Vujovic, Z. and A. Nenezic. 2023. "Montenegro in Crises: Navigating 
Political Turmoil and the Path to European Integration". Suedosteuropa 
Mitteilungen 63 (2): 25-44. Available at: 
https://www.sogde.org/site/assets/files/27497/vujovic_23046_sog_mitteilungen
_02-2023_internet-4.pdf (Date accessed: June 26, 2024).

Walker, N. 2022. "Brazil: 2022 presidential election." Research Briefing, 
House of Commons Library. Available at: 
https://researchbriefings.files.parliament.uk/documents/CBP-9653/
CBP-9653.pdf (Date accessed: August 9, 2024).

Wojnicki, J. 2023. "The 2023 Elections in Montenegro - A Real Political 
Breakthrough?" In Poland's Experience in Combating Disinformation: 
Inspirations for the Western Balkans, edited by A. Adamczyk, G. Ilik, M. 
Tahirovic, and K. Zajaczkowski, 199-209. Oficyna Wydawnicza ASPRA-JR. 
DOI: 10.33067/978-83-8209-282-0

Zajc, D. 2023. "2022: A Super Election Year in Slovenia." European
Perspectives. 14 (1). 21-38. DOI: 10.60073/euper.2023.4.03


//END OF FILE