The Nordic dataset from the survey Journalistic Roles, Values and Qualifications in the 21st century: How Journalism Educators across the Globe View the Future of a Profession in Transition (2020–2021).

The survey data is available as a SPSS file (.sav) and a comma-separated text file (.csv).

The paper addresses the question why people are entering training programs which disseminate knowledge necessary for becoming part of the journalistic profession and how these motives go along with the intention to become a member of the profession. Therefore it draws on data collected among students in journalism related programs in Austria in 2015 (n=352) and tests the linkage between socioeconomic background of the students, their motives for entering a program and how these affect the intention to work in the field of journalism. Factor analysis allowed the identification of four main motives: political and social agency; employment driven; social benefits; and calling/talent. Results show that a) motives for entering a program differ according to the socioeconomic background of the respondents. And b) the intention to work in the field is higher if motives tied to the ideas of agency and calling are reported and lower if employment driven motives are predominant. This leads to the conclusion that the motivation of students to join the journalistic profession is deeply related to believes and normative aspirations of individuals.

Abstract copyright UK Data Service and data collection copyright owner.

This project investigated a hitherto neglected issue, namely how scientists, journalists and editors, respectively, view the production and coverage of news on nanotechnology. The study was based upon a content analysis of United Kingdom (UK) national newspaper coverage of nanotechnology between 1 April 2003 and 30 June 2004. This was supplemented by an email survey of journalists, editors and scientists, followed by in-depth interviews with a sub-sample of the above. By undertaking an analysis of the framing of nanotechnologies in the British newspaper press during this formative period, the study provides novel insights into how the initial terms of reference were established for much of the ensuing news coverage.


Main Topics:

The dataset includes the following files:

• NN1SPSSNews: content analysis of 18 UK-based newspapers
• NN3SPSSsciencequest: data from an email survey of UK-based scientists working in the nanotechnology field, covering expertise, attitudes to media coverage of nanotechnology, media contributions, futures of nanotechnology, and influence of the public and various groups on research
• NN5SPSSjourquest: data from an email survey of UK-based journalists and editors, covering employment history, publications written for, information sources used on nanotechnology, likely impacts of and interest in nanotechnology and related research, dissemination of information to the public and responsibilities of journalists, and scientific communication

No description was included in this Dataset collected from the OSF

Contains information on child abuse prevention services provided by multiple departments within the City and County of San Francisco, including services run directly by City departments and programs provided by contracted organizations. Information was collected by the Controller’s Office as a first step in creating a county-wide abuse prevention plan, and includes program descriptions, cost information (where available), and categorizations by service area, protective factor, target audience, and level of prevention. This data was originally collected in FY19 for programs run during FY18. For more information please see the Controller's report at http://openbook.sfgov.org/webreports/details3.aspx?id=2778

The dataset is produced within the framework of the HORIZON 2020 project called MEDIADELCOM (Critical Exploration of Media Related Risks and Opportunities for Deliberative Communication: Development Scenarios of the European Media Landscape) in 2021-2022. The dataset is one of the 14 single-country data sets included in the consolidated file of country data sets (with 5623 entries), all in msw.xlsx format. All tables are searchable by 20 variables: full reference, year of publication, nationall/international publication, language, country the publication deals with, time of empirical data gathering, type of publication, open access/not OA, where referenced, focus on journalism domain, focus on media-related competences domain, focus on media usage patterns domain, focus on legal and ethical regulations domain, type of the approach, original key words, main topic, comments, country. As the data has been gathered specifically about the research done in four mentioned domains concerning potential ROs emanating from the news media development for deliberative communication, this database does NOT cover ALL the academic publications in the fields of media and journalism research. Consequently, the above-mentioned conditions limit the generalizations and comparisons based on the current database.

Database consisting of data about media development in Sweden 2000-2020

No description was included in this Dataset collected from the OSF

Data collected in Paikat Akidi village (Angole parish, Awere sub-county, Pader district) throughout the 12-week study period.

This is data collected from journalism students on how they use langauge in assessments

Coronavirus (COVID-19) Data in the United States

[ U.S. State-Level Data (Raw CSV) | U.S. County-Level Data (Raw CSV) ]

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since late January, The Times has tracked cases of coronavirus in real-time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists, and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

United States Data

Data on cumulative coronavirus cases and deaths can be found in two files for states and counties.

Each row of data reports cumulative counts based on our best reporting up to the moment we publish an update. We do our best to revise earlier entries in the data when we receive new information.

Both files contain FIPS codes, a standard geographic identifier, to make it easier for an analyst to combine this data with other data sets like a map file or population data.

Download all the data or clone this repository by clicking the green "Clone or download" button above.

State-Level Data

State-level data can be found in the states.csv file. (Raw CSV file here.)

date,state,fips,cases,deaths
2020-01-21,Washington,53,1,0
...

County-Level Data

County-level data can be found in the counties.csv file. (Raw CSV file here.)

date,county,state,fips,cases,deaths
2020-01-21,Snohomish,Washington,53061,1,0
...

In some cases, the geographies where cases are reported do not map to standard county boundaries. See the list of geographic exceptions for more detail on these.

Methodology and Definitions

The data is the product of dozens of journalists working across several time zones to monitor news conferences, analyze data releases and seek clarification from public officials on how they categorize cases.

It is also a response to a fragmented American public health system in which overwhelmed public servants at the state, county and territorial levels have sometimes struggled to report information accurately, consistently and speedily. On several occasions, officials have corrected information hours or days after first reporting it. At times, cases have disappeared from a local government database, or officials have moved a patient first identified in one state or county to another, often with no explanation. In those instances, which have become more common as the number of cases has grown, our team has made every effort to update the data to reflect the most current, accurate information while ensuring that every known case is counted.

When the information is available, we count patients where they are being treated, not necessarily where they live.

In most instances, the process of recording cases has been straightforward. But because of the patchwork of reporting methods for this data across more than 50 state and territorial governments and hundreds of local health departments, our journalists sometimes had to make difficult interpretations about how to count and record cases.

For those reasons, our data will in some cases not exactly match the information reported by states and counties. Those differences include these cases: When the federal government arranged flights to the United States for Americans exposed to the coronavirus in China and Japan, our team recorded those cases in the states where the patients subsequently were treated, even though local health departments generally did not. When a resident of Florida died in Los Angeles, we recorded her death as having occurred in California rather than Florida, though officials in Florida counted her case in their records. And when officials in some states reported new cases without immediately identifying where the patients were being treated, we attempted to add information about their locations later, once it became available.

• Confirmed Cases

Confirmed cases are patients who test positive for the coronavirus. We consider a case confirmed when it is reported by a federal, state, territorial or local government agency.

• Dates

For each date, we show the cumulative number of confirmed cases and deaths as reported that day in that county or state. All cases and deaths are counted on the date they are first announced.

• Counties

In some instances, we report data from multiple counties or other non-county geographies as a single county. For instance, we report a single value for New York City, comprising the cases for New York, Kings, Queens, Bronx and Richmond Counties. In these instances, the FIPS code field will be empty. (We may assign FIPS codes to these geographies in the future.) See the list of geographic exceptions.

Cities like St. Louis and Baltimore that are administered separately from an adjacent county of the same name are counted separately.

• “Unknown” Counties

Many state health departments choose to report cases separately when the patient’s county of residence is unknown or pending determination. In these instances, we record the county name as “Unknown.” As more information about these cases becomes available, the cumulative number of cases in “Unknown” counties may fluctuate.

Sometimes, cases are first reported in one county and then moved to another county. As a result, the cumulative number of cases may change for a given county.

Geographic Exceptions

• New York City

All cases for the five boroughs of New York City (New York, Kings, Queens, Bronx and Richmond counties) are assigned to a single area called New York City.

• Kansas City, Mo.

Four counties (Cass, Clay, Jackson, and Platte) overlap the municipality of Kansas City, Mo. The cases and deaths that we show for these four counties are only for the portions exclusive of Kansas City. Cases and deaths for Kansas City are reported as their line.

• Alameda, Calif.

Counts for Alameda County include cases and deaths from Berkeley and the Grand Princess cruise ship.

• Chicago

All cases and deaths for Chicago are reported as part of Cook County.

License and Attribution

In general, we are making this data publicly available for broad, noncommercial public use including by medical and public health researchers, policymakers, analysts and local news media.

If you use this data, you must attribute it to “The New York Times” in any publication. If you would like a more expanded description of the data, you could say “Data from The New York Times, based on reports from state and local health agencies.”

If you use it in an online presentation, we would appreciate it if you would link to our U.S. tracking page at https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html.

If you use this data, please let us know at covid-data@nytimes.com and indicate if you would be willing to talk to a reporter about your research.

See our LICENSE for the full terms of use for this data.

This license is co-extensive with the Creative Commons Attribution-NonCommercial 4.0 International license, and licensees should refer to that license (CC BY-NC) if they have questions about the scope of the license.

Contact Us

If you have questions about the data or licensing conditions, please contact us at:

covid-data@nytimes.com

Contributors

Mitch Smith, Karen Yourish, Sarah Almukhtar, Keith Collins, Danielle Ivory, and Amy Harmon have been leading our U.S. data collection efforts.

Data has also been compiled by Jordan Allen, Jeff Arnold, Aliza Aufrichtig, Mike Baker, Robin Berjon, Matthew Bloch, Nicholas Bogel-Burroughs, Maddie Burakoff, Christopher Calabrese, Andrew Chavez, Robert Chiarito, Carmen Cincotti, Alastair Coote, Matt Craig, John Eligon, Tiff Fehr, Andrew Fischer, Matt Furber, Rich Harris, Lauryn Higgins, Jake Holland, Will Houp, Jon Huang, Danya Issawi, Jacob LaGesse, Hugh Mandeville, Patricia Mazzei, Allison McCann, Jesse McKinley, Miles McKinley, Sarah Mervosh, Andrea Michelson, Blacki Migliozzi, Steven Moity, Richard A. Oppel Jr., Jugal K. Patel, Nina Pavlich, Azi Paybarah, Sean Plambeck, Carrie Price, Scott Reinhard, Thomas Rivas, Michael Robles, Alison Saldanha, Alex Schwartz, Libby Seline, Shelly Seroussi, Rachel Shorey, Anjali Singhvi, Charlie Smart, Ben Smithgall, Steven Speicher, Michael Strickland, Albert Sun, Thu Trinh, Tracey Tully, Maura Turcotte, Miles Watkins, Jeremy White, Josh Williams, and Jin Wu.

Context

There's a story behind every dataset and here's your opportunity to share yours.# Coronavirus (Covid-19) Data in the United States

[ U.S. State-Level Data ([Raw

The project "Digital Citizenship and Surveillance Society" investigated the implications of the Snowden revelations for key aspects of digital citizenship across issues regarding the legal and regulatory framework of digital communications; technical infrastructures and technical standards; everyday interactions with digital communication and advocacy regarding communicative rights; and investigative journalism and press freedom.

The research data provided here includes data generated through a combination of qualitative and quantitative methods, in particular: (1) interviews with policy stakeholders, civil society activists, and journalists (transcripts); (2) focus groups with members of the British public (transcripts); (3) content analysis of British press and blogs (SPSS data).

The project "Digital Citizenship and Surveillance Society" examined the governance of digital citizenship - i.e. civic agency reified through the use of digital media - in an era of omnipresent surveillance. Within a cross-disciplinary and practitioner-focused framework, the project analysed the challenges for digital citizenship through four interrelated work-streams: policy, technology, civil society, and news media. These four themes were investigated through a combination of qualitative and quantitative methods as well as participatory action research. The work-streams collected data through desk research and field research that combined policy document analysis, technical and software analysis, focus groups, interviews and content and discourse analysis.

The standard approach for proteomic data acquisition of isobaric-tagged samples by mass spectrometry is data-dependent acquisition. This semistochastic, identification-first paradigm generates a wealth of peptide-level data without regard to relative abundance. We introduce a data acquisition concept called sequential windowed acquisition of reporter masses (SWARM). This approach performs quantitation first, thereby allowing subsequent acquisition decisions to be predicated on user-defined patterns of reporter ion intensities. The efficacy of this approach is validated through experiments with both synthetic mixtures of Escherichia coli ribosomes spiked into human cell lysates at known ratios and the quantitative evaluation of the human proteome’s response to the inhibition of cullin-based protein ubiquitination via the small molecule MLN4924. We find that SWARM-informed parallel reaction monitoring acquisitions display effective acquisition biasing toward analytes displaying quantitative characteristics of interest, resulting in an improvement in the detection of differentially abundant analytes. The SWARM concept provides a flexible platform for the further development of new acquisition methods.

The Maryland Road Closure Reporter application has been established as a unified web-based application for local jurisdictions to capture, publish and consume road closures events across the State of Maryland. This application is a view that consumes all current/active closure events submitted by participating local jurisdictions utilizing Maryland's Road Closure Reporter application.Data Capture Application Users GuideMDOT SHA Website

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

This survey covers China.

Analysis unit

• Household
• Individual

Universe

The WVS for China covers national population, aged 18 years and over, for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

Random sample of Central China, containing 68% of population The sample was designed to be representative of the entire adult population, i.e. 18 years and older, of your country. The lower age cut-off for the sample was 18 and there was not any upper age cut-off for the sample. The sample size for China is N=1500.

Mode of data collection

Face-to-face [f2f]

Research instrument

The WVS questionnaire was in Chinese. Some special variable labels have been included, such as: V 167 Least liked groups: include only categories 2 Capitalist 4 Immigrant, 5 Homosexuals and 6 Criminals. V203/V204 Geographical affinity: 3 stands for China and 4 for Asia. Country Specific variables included are: V208: Ethnic identification: is missing; V209 Language at home: all answers, except 2 are 1 (Chinese); V233 Ethnic group is 100% Chinese (code 4); V234 Region: 1 North, 2 Center, 3 South and 4 East. V235 Language at home is 100% 1 Chinese except 2 cases with code 6. The following variables werent asked: V56, V117 to V124, V135 to V145, V151 to V166, V170, V179 to V191, V210 to V213. V106, V107: do not include category 4 (Free Speech) This is important for those working with post-materialist indexes.

Sampling error estimates

+/- 2,6%

This dataset contains a collection of Twitter rumours and non-rumours posted during breaking news. The five breaking news provided with the dataset are as follows:* Charlie Hebdo: 458 rumours (22.0%) and 1,621 non-rumours (78.0%).* Ferguson: 284 rumours (24.8%) and 859 non-rumours (75.2%).* Germanwings Crash: 238 rumours (50.7%) and 231 non-rumours (49.3%).* Ottawa Shooting: 470 rumours (52.8%) and 420 non-rumours (47.2%).* Sydney Siege: 522 rumours (42.8%) and 699 non-rumours (57.2%).The data is structured as follows. Each event has a directory, with two subfolders, rumours and non-rumours. These two folders have folders named with a tweet ID. The tweet itself can be found on the 'source-tweet' directory of the tweet in question, and the directory 'reactions' has the set of tweets responding to that source tweet.This dataset was used in the paper 'Learning Reporting Dynamics during Breaking News for Rumour Detection in Social Media' for rumour detection. For more details, please refer to the paper.License: The annotations are provided under a CC-BY license, while Twitter retains the ownership and rights of the content of the tweets.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National

Analysis unit

Household Individual

Universe

National Population, Both sexes,18 and more years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 841

a. A random sample of 2000 people was drawn from the New Zealand Electoral Roll; Permanent Residents and Citizens of NZ are required by law to place themselves on the Electoral Roll. The roll contains name, address, electorate, age, gender, occupation, and a Maori identifier.

b. Excluded from the sample were overseas addresses and people over 90 years of age (following past NZSV surveys).

c. People identifying as Maori on the roll were oversampled (as in past NZ Values Surveys) because Maori, as a group, tend to have a lower response rate to such surveys. About 13.6% of the people on the Roll identified as Maori, while the sample that was drawn is about 22.5% identifying as Maori on the Roll. In the results of the survey for the ethnicity question, 16.3% indicated they identified as Maori. They may also have selected other ethnicities, and saying “Maori” in the survey does not necessarily mean they are listed as Maori on the Electoral Roll.

Mode of data collection

Mail Questionnaire [mail]

Research instrument

For each wave, suggestions for questions are solicited by social scientists from all over the world and a final master questionnaire is developed in English. Since the start in 1981 each successive wave has covered a broader range of societies than the previous one. Analysis of the data from each wave has indicated that certain questions tapped interesting and important concepts while others were of little value. This has led to the more useful questions or themes being replicated in future waves while the less useful ones have been dropped making room for new questions.

The questionnaire is translated into the various national languages and in many cases independently translated back to English to check the accuracy of the translation. In most countries, the translated questionnaire is pre-tested to help identify questions for which the translation is problematic. In some cases certain problematic questions are omitted from the national questionnaire.

WVS requires implementation of the common questionnaire fully and faithfully, in all countries included into one wave. Any alteration to the original questionnaire has to be approved by the EC. Omission of no more than a maximum of 12 questions in any given country can be allowed.

Response rate

44.22%

Sampling error estimates

Estimated error: 3.4

Statistics of data collection and structure refinement.

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden. The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones. The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

The Survey covers China.

Analysis unit

• Household
• Individual

Universe

The WVS for China covers national population aged 18 years and over, for both sexes.

Kind of data

Sample survey data [ssd]

Sampling procedure

To meet the requirement of overall coverage of Chinese adults including migrant population, GPS/GIS Assistant Area Sampling 1 was used in this survey. Respondents are sampled through stratified, multi-stage PPS (probability proportional to size) sampling. With careful considerations of representativeness, feasibility, and budgetary constrains, it was decided this project would draw a subsidiary probability sample out of a RCCCs previous national survey Social Inequality and Distributive Justice in China conducted in 2004. The 2004 survey was a national survey conducted through out the country. The target population was the same as the one defined for this survey. In the meanwhile, through the stratification, the proportionally allocated multi-stage PPS technique was employed in order to obtain the self-weighted household samples. Sampling Frames A GIS dataset was established as the sampling frame for this project, which was based on: 1) township level population data from the 2000 Census,2 2) the most recent and detailed (paper and electronic) maps, 3) the highest possible resolution images from Google Earth. Compile all the information above the population density was calculated for each of the HSMs in township level units. Within the target population, there were 3,004 half-square degree (HSD) of latitude and longitude for the first stage sampling. The total population were 1,242,612,226.

Sampling Processes: 1) Out of 3,004 half-square degree(HSD) in China, 40 HSDs were chosen by PPS. 2) Two OSMs were selected by PPS within each of the selected HSD. 3) One HSM was drawn by PPS within each of the selected OSM; The measures of size (MOS) used at these stages were the density of the population per sampling unit. 4)Within each of the selected HSM,the number of SSSs (90m*90m)was calculated based on the population density, and then selected the SSSs simple randomly. 5) Trained surveyors equipped with GPS receivers were then sent to locate and enumerate the sampled spatial square seconds (SSS). For maintaining equal probabilities of selection across households, all dwellings enumerated in the SSSs were included in the sample. Using system sampling, we draw 50 dwellings in each HSM. 6) Respondents were selected from dwellings using the Kish Grid method3.

The sample size for China is N=1991.

Mode of data collection

Face-to-face [f2f]

Response rate

The sample size was determined to be approximately 2,800 eligible individuals are to be drawn out of the above defined target population in all provinces of China. 2,873 Target sample size 2,534 Sample drawn in the field 1,991 Completed, valid interviews 78.6% Response rate

Sampling error estimates

+/- 2,2%

Abstract

The World Values Survey (www.worldvaluessurvey.org) is a global network of social scientists studying changing values and their impact on social and political life, led by an international team of scholars, with the WVS association and secretariat headquartered in Stockholm, Sweden.

The survey, which started in 1981, seeks to use the most rigorous, high-quality research designs in each country. The WVS consists of nationally representative surveys conducted in almost 100 countries which contain almost 90 percent of the world’s population, using a common questionnaire. The WVS is the largest non-commercial, cross-national, time series investigation of human beliefs and values ever executed, currently including interviews with almost 400,000 respondents. Moreover the WVS is the only academic study covering the full range of global variations, from very poor to very rich countries, in all of the world’s major cultural zones.

The WVS seeks to help scientists and policy makers understand changes in the beliefs, values and motivations of people throughout the world. Thousands of political scientists, sociologists, social psychologists, anthropologists and economists have used these data to analyze such topics as economic development, democratization, religion, gender equality, social capital, and subjective well-being. These data have also been widely used by government officials, journalists and students, and groups at the World Bank have analyzed the linkages between cultural factors and economic development.

Geographic coverage

National.

Analysis unit

Household Individual

Universe

National Population, Both sexes,18 and more years.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample size: 1200

Sampling scheme. The Philippines was divided into four study areas: National Capital Region (NCR), Balance Luzon, Visayas, and Mindanao. Multi-stage probability sampling will be used in the selection of sample spots. For the National Capital Region - Stage 1. Selection of Sample Spots (Barangays); Stage 2. Selection of Sample Households; Stage 3. Selection of Sample Adult. For the rest of the Philippines - Stage 1. Allocation and Selection of Sample Provinces; Stage 2. Allocation and selection of sample municipalities; Stage 3. Allocation and Selection of Sample Spots; Stage 4. Selection of Sample Households and; Stage 5. Selection of Sample Respondents. For more information on the sampling procedure refer to the related materials section.

Mode of data collection

Face-to-face [f2f]

Research instrument

For each wave, suggestions for questions are solicited by social scientists from all over the world and a final master questionnaire is developed in English. Since the start in 1981 each successive wave has covered a broader range of societies than the previous one. Analysis of the data from each wave has indicated that certain questions tapped interesting and important concepts while others were of little value. This has led to the more useful questions or themes being replicated in future waves while the less useful ones have been dropped making room for new questions.

The questionnaire is translated into the various national languages and in many cases independently translated back to English to check the accuracy of the translation. In most countries, the translated questionnaire is pre-tested to help identify questions for which the translation is problematic. In some cases certain problematic questions are omitted from the national questionnaire.

WVS requires implementation of the common questionnaire fully and faithfully, in all countries included into one wave. Any alteration to the original questionnaire has to be approved by the EC. Omission of no more than a maximum of 12 questions in any given country can be allowed.

Sampling error estimates

Estimated error: 2.9