ISS REPORT NO. 75 MEDIA SYSTEMS AND THE CHARACTER OF NEWS A CROSS-NATIONAL CONTENT ANALYSIS Project...

ISS REPORT NO. 75 ISBN 978-82-90217-48-3

MEDIA SYSTEMS AND THE CHARACTER OF NEWS A CROSS-NATIONAL CONTENT ANALYSIS

Project description, coding guide, code sheet and codebook

Tove Brekken & Toril Aalberg

2010

Department of Sociology and Political Science

Norwegian University of Science and Technology (NTNU)

Trondheim, Norway

Contents: Project description…………………………………………………………..……………………………..……..2 Coding guide…………………………………………………………………..……………………………….…… 4 Code sheet……………………………………………………………………………………………………….……22 Reliability ………………………………………………………………………………………………………….….40 Frequency distributions………………………………………………………………………………………...44

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Project description The content analysis presented here was initiated by the project “Media Systems, news

content and public perception of political reality” directed by Toril Aalberg and funded by

the Research Council of Norway. The aim of the overall project, in which this content

analysis is an important part, is to study the information given by the news media to the

public, and how this information influences public’s knowledge and perception of political

reality. The content analysis will let us study between and within country variations in news

content, including important factors such as hard versus soft news, thematic versus episodic

news frames, domestic versus international focus, use of actors and sources as well as main

arguments presented on a few selected topics. The battery of variables included in the

content analysis also refers to important background information including the news items

size, placement etc. This content analysis was followed by an extensive survey of the public

measuring among other things media use, public affairs knowledge, political interest and

perceptions of political realities (see Strabac and Aalberg 2009 for details).1

The content

analysis include news media output from 3 non-consecutive weeks in the end of 2008 and

early 2009.

Six countries are included in this study. These are the US, UK, Norway, Sweden, Belgium

(Flandern) and The Netherlands. The country experts are represented by six research

associates affiliated with the project. These include Shanto Iyengar (United States), James

Curran (United Kingdom), Kees Aarts (the Netherlands), Peter van Aelst (Belgium/Flandern),

Jesper Strömbäck (Sweden) and Anders Todal Jenssen (Norway). Tove Brekken, Audun

Fladmoe, Egbert Leppink and Toril Aalberg (all at NTNU, Trondheim) have been responsible

for the coordination of the content analysis. We have also received valuable assistance from

a numbers of other coders including Nils Erik Bjørge, Berit Kvaløy and Ron van Blokland.

The news output in the six countries was collected by the country experts based on an

agreed sample procedure. Information about the selection of news media is provided in the

Coding guide. A team of coders with the required language skills, all located in Trondheim,

1 Zan Strabac and Toril Aalberg (2009) “Media use, political knowledge and perception of reality. A Cross-National survey. Project description, questionnaires and codebook” ISS Report no. 74 Trondheim: Department of Sociology and Political Science, NTNU.

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analysed the news content manually and entered the data into SPSS. The final sample from

the six countries equals a total of 44,921 units, where one unit is the individual news story.

Each item is also linked to audience ratings and population figures, so that researchers more

easily can create desired weights variables.

Trondheim February 26th 2010

Tove Brekken and Toril Aalberg

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Coding Guide Six-Nation Study on Media Systems, News Content and Perceptions of Reality

This Coding Guide is part of the comparative research project ”Media Systems, News Content and Public Perception of Political Reality” directed by Toril Aalberg, NTNU. The purpose of the project is to investigate differences in news content within and across various media systems and how the news content can influence public knowledge and perceptions of reality. In addition to surveys of the public the project will include content analysis of main news sources in various countries. The content analysis will be quantitative, and the purpose of this Coding Guide is to provide the instructions for how to code the news stories in a way that makes direct comparisons possible and reliable. In order to do that, the same Coding Guide will be applied universally in studies of both different media (print versus broadcast) and different countries. The only exception applies to V48 –V66: Issues related to education, which are only to be coded in Norway and Sweden (and Finland)

News content are to be selected from major print and broadcast media in Belgium (Wallonia), The Netherlands, Norway, Sweden, the United Kingdom and the United States. The sample should consist of the main (largest) “elite/prestige” newspaper, the main “tabloid/popular” newspaper as well as a selected regional newspaper. Also included are the main daily news programme on the two biggest television channels (based on audience rating – and preferably 1 PBS and 1 commercial channel if possible). See table 1 for details on which news media are to be included in the various countries. Print and Broadcast media to be included in content analysis Belgium Netherlands Norway Sweden UK US Print Elite

De Standard

Volkskrant Aftenposten Dagens Nyheter

The Telegraph

New York Times

Print Tabloid Het Laatste Nieuws

Telegraaf VG Aftonbladet The Sun USA Today

Print Regional

Gazet van Antwerpen

De Twente Courant Tubantia

Adresseavisen Göteborgs Posten

Glasgow Herald

Acron Beakon Journal

Broadcast Public (Except NBC in USA)

VRT: Het Journaal (1900)

Ned1: NOS 8 uur journaal (2000)

NRK1: Dagsrevyen (1900)

SVT1: Rapport (1930)

BBC1: BBC News (2200)

NBC Nightly news (1830)

Broadcast Commercial

VTM: Het Nieuws (1900)

RTL4: RTL4 Journaal (1930)

TV2: Nyhetene (2100)

TV4: Nyheterna (1900)

ITV: News at ten (2200)

ABC World News (1830)

The unit of analysis are individual news stories (also including very short news articles/items). All the news contained in the main sections of the newspaper (including all regular units) should be coded. Special magazines and supplements that are attached on a non daily basis should not be included). Service features with real news in them is to be coded – e.g. a review with an interview with the author, actor etc. which goes beyond just reviewing the play, book, music etc. Editorials, opinion pieces, or other articles that does not constitute news journalism, should be excluded. Service features like horoscopes, games, tv listings, weather forecast and other supplements (not news journalism) should also be excluded. The time frame for the content analysis will be three non-consecutive weeks in the end of 2008 and early 2009. Within this period a total number of 21 days are to be sampled, including week 47, week 2 and week 4. One week runs from Monday trough Sunday, but Newspapers should not be sampled on Sundays).

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V1 News item identification number Each news item is to be uniquely identified. Belgian news items should start with 1xxxxxx, Dutch news items with 2xxxxxxx, Norwegian news items with 3xxxxxxx, Swedish news items with 4xxxxxxx, UK news items with 5xxxxxxx and finally US news items with 6xxxxxxx. The second digit should refer to the news medium (se values 1 to 5 in V4). Hence, a news item from Norwegian PBS should have an id number that starts with 41xxxxx, a news item from the Norwegian tabloid should start with 44xxxxx. The next digit should refer to the coder id number. V2A Country Countries included in the study. V2B Population Population of each country is reported in absolute numbers. V2C Coder identification number Each coder are given a coder id number. This is specified in the code sheet. V3 Date Four numbers - the first two marks the month and the second two the day. November the seventeenth is written 1117. V4A Medium Coders should identify which media category the news item originates from. Public TV or the TV that has the highest ranking should be given value 1, commercial TV or the channel with the second highest ranking should be given value 2. Elite news papers should be given value 3 and tabloid newspapers should be given value 4. Regional newspapers are coded as 5. V4B Circulation, Newspapers Circulation figures from 2008 included in content analysis: Belgium Netherlands Norway Sweden UK US Print Elite

102 280 263204

247 556 335 600 845,167 * 1,000,665

Print Tabloid 340 899 695635

284 414 368 200 3,073,106 * 2,293,310 Print Regional

127 960 116513 77 044 242 400 62290** 110,999

Circulation refers to the number of sold, reduced price and free copies of a title distributed on an average day over the stated period of time. Figures include weekdays only (not Sunday editions). Sources for daily newspaper circulations Belgium http://www.cim.be/auth/nl/d/dp.html Average circulation for 2007. Netherlands https://www.hoi-online.nl/en Average circulation for 2008. Norway Medienorge / Avisåret (årlig rapport) /Landslaget for Lokalaviser (LLA) /Mediebedriftenes Landsforening (MBL) http://www.medienorge.uib.no/ Average circulation for 2008.

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Sweden Swedish Newspapers' Publishers' Association / dagspress.se (http://www.dagspress.se/index.jsp) Average circulation for 2008. UK * Source: ABC (Audit Bureau of Circulations) Average July – December 2008) (http://www.guardian.co.uk/media/table/2009/jan/09/abc-december-national-newspapers) ** Newspaper Society database average july – december 2008 (http://www.nsdatabase.co.uk/) USA ABC (Audit Bureau of Circulations) Average circulation March trough september 2008 http://www.burrellesluce.com/top100/2009_Top_100List.pdf V4C Viewer ratings, Television Average viewer statistic from 2007 Belgium Netherlands Norway Sweden UK US* Broadcast Public

756000 1630000 706000 1023000 4850000 8400000


630000 101000 494000 491000 3750000 8300000

*Except NBC in USA. V5 Placement of news item Coders should identify where the news item is placed in the programme or in the newspaper. Numeric codes should be used that indicate page number or entry number for broadcast news. A news story on page 10 are to be coded as 10 while a news item that is broadcasted as the third news story should be coded as 3.

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V5A Newspaper unit This extra variable is to be coded for newspapers only. And should indicate in which newspaper unit the article is printed. Only units that are a regular part of the newspaper should be included in the analysis. Special magazines and supplements that are attached on a non daily basis should not be included. Supplements included in the study: Belgium Netherlands Norway Sweden UK US 3. Print Elite De Standard

1. Main

2. Economy, Sports

Volkskrant

1: Main

2: Culture, sports

Aftenposten

1.Main

2. Culture

3. Economy

Dagens Nyheter

1. Main

2. Culture

3.Economy / Sports

The Telegraph

1. Main

2. Business

3. Sports

New York Times

1. Main(A)

2. Business(B)

3. Arts (C)

4. Various(D) 4. Print Tabloid

Het Laatste Nieuws

1. Main

2. Economy, Sports, Culture

De Telegraaf

1: Main

2: Culture, Sports, Economy

VG

1. Main

2. Sports

Aftonbladet

1. Main

2. Sports

3. Entertainm. / Lifestyle*

The Sun

1. Main

2. TVBiz

USAToday

1. Main(A)

2. Money(B)

3. Sports(C)

4. Life(D) 5. Print Regional

Gazet van Antwerpen

1: Main

2: Sports, culture

3: Region

De Twente Courant Tubantia

1: Main

2: Region

3: Sports

Adresseavisen

1. Main

2. Culture

3. Economy

Göteborgs Posten

1. Main

Glasgow Herald

1. Main

2. Sports

Acron Beakon Journal

1. Main

2. Community News(B)

3. Sports (C) * Only Fridays and Saturdays – other days included in the main section. V6 Status of News item Coders should identify if news items are to be considered as headline/frontpage news. When it comes to TV the top-3 TV news are to be considered Headline and the rest are to be coded “does not apply”. HOWEVER if a story has been mentioned in the teasers or one of the top-3 stories is mentioned later in the program it is still to be coded as Headline. E.g. the teaser introduces Iraq, global warming and the US election. And then starts with a couple of stories on Iraq. When the global warming story comes up it is still a headline story. And the same goes for the US election when it comes up after the two other themes it is still a headline code. On the other hand any other story is a “does not apply”. For newspaper coding the “Headline/front page item” and “Other item on front page” system is similar to the broadcast coding. Headline/front page item are to be coded for the large and medium headlines on the front page. And again when those stories appear in the paper they are to be coded as “headline/front page item”. “Other item on front page” is for the small news

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on the front page e.g. sports results, mentioning of special sections/features in the paper or just odd little stories on the front page. And again when those stories reappear in the paper they are to be coded “other item on front page”. “Does not apply” goes for every other story in the paper V7A Size of news item TV TV news items are to be coded in seconds, so that a one and a half minute news item is given the value of 90 seconds. V7B Size of news item TV, recoded TV news items length should be recoded into categories. The categories range from extra small to extra large. News items up to ten seconds are given the value 1, news items with a duration from 11 to 30 seconds are given the value 2, news items with a duration from 31 to 90 seconds are given the value 3, news items with a duration from 91 to 150 seconds are given the value 4 and finally news items with a duration longer than 150 seconds are given the value 5. V7C Size of news item Newspapers For newspapers the size should be established with respect to the newspaper size, and indicated the percentage of a newspaper page (including pictures, charts and “boxes” with facts). If the pictures etc. serves as an illustration of several related articles, the picture should be linked to whatever is considered the main article. The sizes range from extra small to extra large based on a logarithmic principle. Small notes under 10 % of a page is give value 1, small articles between 10-30 % of a page is given code 2, medium sized articles that covers 30-70 percent of a newspage is given code 3, and large articles that covers 70 -150 percent of a page should be given a value 4. Extra large articles that is larger then one and a half page (or 150%) is given the value 5. V8 News section Coders should identify what type of news section that best describes where the news item is placed. Coders should separate between 1) General news (incl. frontpage or sections with no specific heading). Most TV news would also be placed under general news. 2) Domestic news, 3) Economy and trade, 4) Foreign news, 5) Regional/local news, 6) Culture, 7) Sport, 8) Entertainment, 9) Lifestyle, 10) Traffic and transportation, 11) Crime, 12) Consumer news, 13) IT and computers, 14) Weather, 15) Children, 16) Other V9 Contextualised or decontextualised news (Thematic vs Episodic frame) Coders should identify if the news item is contextualised and thematic or if it is decontextualised and episodic. The contextualised and thematic code 1 should be used if the news item highlights causes or consequences that may be related to the public good (concerning public issues in general). This thematic framing position the news story in a broader context that deals with its meaning or implications for society, a trend that goes beyond a single event/incident. The story places public issues in a broad or abstract context. Alternatively the news item may be decontextualised and episodic with a narrow framing in terms of topic or individual reference, not related to the public good/issues. Episodic framing refers to a particular event or incident. Typical examples are personified and/or single out stories, or stories that does not go much beyond that specific event (rather it takes the form of a case-study). V10, V11 & V12 Countries mentioned (only if V8 is given code 1 through 5) If the news refers to a country or several countries, coders should identify which are mentioned in the news story. Name first, second and third country mentioned – including ones own county. These variables are only to be coded if the news item is placed in sections including general news, domestic news, economy and trade, foreign news or regional/local news.

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V13 & V14 Issue of news item (Primary and secondary) Coders should identify the primary (and secondary) issue of the news item. The categories are meant to be mutually exclusive, which means that, for example, whatever concerns electoral campaigns goes under “political campaign and election” and NOT under “party politics”. Likewise, a love story between celebrities goes under “sex/love/romance” and NOT under “other human interest/celebrities”… The headline and lead should be given extra weight in the judgment of what category that applies for news story. “99 – other/non of the above” category has been added but is only to be used, in the unlikely case that the article cannot fit in any of the other categories. Do not code more then one item per theme in V13+V14 in sum. This indicates that if the primarily issue in V13 is poverty, social and welfare issues and housing urban affairs seem to be a second issue in the news item, this is not to be coded in V14. However, if the primary issue in V13 is poverty, social and welfare issues and immigration, regugees and border issues seem to be a second issue, this is to be coded 03 in V14.

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NEXT SECTIONS TO BE CODED ONLY IF ISSUE OF NEWS ITEM IS 1) IMMIGRATION OR INTEGRATION, 2) GOVERNMENT REGULATION 3) EDUCATION.

V15A-V18A Story actor Who is the story about? The idea is to register whom the news story is about. This variable assesses the actors in the story, and importance is indicated by a combination of the amount of time, or frequency, or order in which they appear. If it is possible to single out the most important story actor, that actor should be coded first. If it is hard to differentiate between the importance of different story actors, just code story actors in order of appearance. Story actors number 2, 3 and 4 should be coded in order of appearance for all cases. If the news story consists of fewer than four story actors, just code the actors present in the story and assign value 99 to the other variables concerning story actors. If the news story consists of more than four story actors, code the most important story actor and three others in order of appearance or code all four story actors in order of appearance. Story actors appearing after these four, shall not be coded. If an actor has different official roles (for instance being both a cabinet minister and a deputy leader of a specific Party coders should pay attention to the main role the actor is taking/being presented as in the news item. If he/she appears as a representative for the government code 1 should be used. If the main focus is on his/her role in the party rather than in cabinet, coders should assign code 2-7. If the news story uses just one of the persons titles or refers to only one role that indicates what code to assign. If the news story is not clear or both roles are referred to, coders should use their best judgement to try to decide which role is the most dominant or important. Journalists are only to be coded as actors if the story is about their role as journalists. If the news story is about journalists in general, the role of the media or about cutting jobs in newspapers, then a journalist being interviewed about that subject, could also be considered an actor. Example of coding from the tv-clip viewed during meeting on November 26th. Who is the story about? The story is about the consequences of the financial crisis for the car industry. The main actor is the car companies. Clues are that they are mentioned first (both visually with their logos displayed and by the news anchor talking about them in the intro and at the beginning of the actual news story) and the car companies are followed through out the news story. So main actor will be coded 12 – “business leader or private companies”. The other actors in this story are the different congress/senate members being shown in the news story. The story is about their views on the bailout plan for the car industry. The congress/senate members will be coded in order of appearance and should be coded with values depending on their party affiliation (value 2-6). If party affiliation is not possible to determine, assign code 7 – “Other party or representatives”. V15B-V18B Gender of story actor Coders should identify gender of the story actor if possible. 1 indicate that the story actor is female, 2 indicates that the story actor is male. Code 3 if this does not apply (for instance if the story actor is an organization or a company) or if it is impossible to tell.

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V19A-V22A Sources for quotes There is often considerable overlap between the main actors in the story, and those who are quoted or who are seen speaking (soundbites on TV) in the story. But there is not necessarily a direct correspondence. Who is quoted or speaking as a source in the story? If the news story consists of fewer than four sources for quotes, just code the sources present in the story and assign value 99 to the other variables concerning sources for quotes. If the news story consists of more than four sources for quotes, code all four sources in order of appearance. Sources for quotes appearing after these four, will not be coded. If a source has different official roles (for instance being both a cabinet minister and a deputy leader of a specific Party, coders should pay attention to the main role the actor is taking/being presented as in the news item. If he/she appears as a representative for the government code 1 should be used. If the main focus is on his/her role in the party rather than in cabinet, coders should assign code 2-7. If the news story uses just one of the persons titles or refers to only one role that indicates what code to assign. If the news story is not clear or both roles are referred to, coders should use their best judgement to try to decide which role is the most dominant or important. Journalists are only to be coded as sources if they are being interviewed or quoted in the news item. For a journalist to be considered a source, the journalist must go beyond his or her role as a conveyor. If the journalist interviews someone, speaks to make transitions from one segment of the news story to another or otherwise acts as someone who lets others pass on their knowledge, the journalist should not be considered a source. If the journalist disseminates knowledge about the issue, the journalist should be coded as a source. If a journalist is a foreign correspondent and makes a comment of some length or if a journalist talks about an issue as an “expert” or is portrayed as knowledgeable about the issue (must also be of some length), the journalist should be considered a source. In newspapers a quote is sufficient for the person or organization to be considered a source. Anchors should never be coded as sources in any cases. The same goes for the journalist(s) writing the article in newspapers. Example of coding from the tv-clip viewed during meeting on November 26th. Who gets to speak and to be quoted? In this news story the first source would be the journalist interviewed/talking to/making a comment to the anchor. (The journalist would not be an actor because the story is not about him). So, the first source in the news clip would be the journalist, assigned code 14 – journalist/media representative/media. The next sources would be the first three congress/senate members because they get to speak/be quoted in the news story. Coders should assign code 2-7 (depending on party affiliation) to the next three sources. V19B-V22B Gender of source Coders should identify gender of the source if possible. 1 indicates that the source is female, 2 indicates that the source is male. Code 3 if this does not apply (for instance if the source is referred to as an organization or a company or if it is an anonymous source) or if it is impossible to tell.

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Immigration (If V13/V14 = code 03 or 12) The next section is only to be coded for news items about immigration or integration V23 Main argument towards immigration Coders should type 1 if the news story contains considerable negative evaluations or criticism towards immigration or immigrants, and 2 if the main argument in the news story seem favorable towards immigration/immigrants. If the news story seems neutral and just presents facts with no arguments or evaluation attached to these facts it should also be coded as 1 (neutral). If the news story includes both positive and negative statements about immigration/immigrants the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. V24 Is there a reference to economic arguments? Coders should type 1 if the news story contains statements that indicate that immigrants exploit economic system or benefits and, and 2 if the story includes statements that point to the economic benefits related to immigrants/immigration. If the news story seems neutral and just presents facts with no arguments or evaluation attached to these facts it should be coded as 2. If the news story includes both negative and positive statements about immigration and the economy the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If there is no reference to economic arguments the article should be coded as 0. V25 Is there a reference to cultural arguments? Coders should type 1 if the news story contains statements that indicate that immigrants represent a threat to national/local culture, and 2 if the story includes statements that point to the cultural benefits related to immigrants/immigration. If the news story seems neutral and just presents facts with no arguments or evaluation attached to these facts it should be coded as 2. If the news story includes both negative and positive statements about immigration and culture the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If there is no reference to cultural arguments the article should be coded as 0. V26 Is there a reference to crime? Coders should type 1 if the news story contains statements that indicate that immigrants perform crime/increase crime and 2 if the story includes statements that indicate that immigrants are victims of crime. If the news story seems neutral and just presents facts with no arguments or evaluation attached to these facts it should be coded as 2. If the news story includes both types of statements the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If there is no reference to crime related arguments the article should be coded as 0. V27 Is there a reference to laws that regulate immigration? Coders should type 1 if the news story contains statements related to laws to reduce immigration or limit immigrant rights and 2 if the story includes statements that point to the need to prevent immigrant discrimination. If the news story seems neutral and just presents facts with no arguments or evaluation attached to these facts it should be coded as 2. If the news story includes both types of statements the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If there is no reference to laws that regulate immigration the article should be coded as 0.

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V28 Are immigrants mainly framed as a problem or a resource in the news story? Coders should type 1 if the news story generally frames immigrants/immigration/integration as a problem and 2 if the story generally frames immigrants as a resource/deserved group. If the news story includes both types of statements equally the news item should be given the code 3. If it is impossible to say how immigrants are framed the news item should be coded as 0 (cannot say). V29 Is there a geographical reference to where immigrants originate from? Coders should type 0 if no geographical reference is made as to where immigrants originate from. Code 1 for reference to Western immigrants, 2 for reference to East European immigrants and 3 for immigrants from South America, Africa and Asia. If the news story includes references to different geographical locations the main reference should be identified according to the amount of time, frequency and\order of appearance of the various references (including pictures). V30 Is there an explicit reference to main religious background of immigrants? By explicit reference we mean direct mentioning of immigrants as being Muslims, Christians, etc., or mentioning that they are of Islamic, Muslim, etc. background. Typically, a word or words identifying religion would be in the article / newscast. Coders should type 0 if no reference to religious background of immigrants. Code 1 for reference to Christian immigrants, 2 for reference to Muslim immigrants and 3 for reference to any other religion. If the news story includes references to different religious backgrounds the main reference should be identified according to the amount of time, frequency and\order of appearance of the various references (including pictures). V30 Is there an implicit reference to main religious background of immigrants? By implicit reference we means other clues that might lead a reader/viewer to identify the religion of immigrants with a reasonable degree of certainty. Clues may be applied to mentioning nationality/country of origin that clearly has one dominant religion. These countries are generally considered muslim: Afghanistan, Algeria, Azerbaijan, Djibouti, Egypt, Gaza strip (Palestine), Indonesia, Iran, Iraq, Jordan, Kuwait, Libya, Mauritania, Morocco, Oman, Pakistan, Quatar, Saudi Arabia, Senegal, Somalia, Syria, Tajikistan, Tunisia, Turkey, United Arab Emirates and Yemen. Most European and American countries are considered Christian. One should not use skin complexity to determine religion if no other clue is provided. Coders should type 0 if no reference to religious background of immigrants. Code 1 for reference to Christian immigrants, 2 for reference to Muslim immigrants and 3 for reference to any other religion. If the news story includes references to different religious backgrounds the main reference should be identified according to the amount of time, frequency and\order of appearance of the various references (including pictures). V31 Does the news story present picture(s) of immigrants that reflect skin complexion? Coders should type 0 if no picture of immigrants. Code 1 if picture reflects immigrants with (mainly) dark skin complexion (non-white), 2 if equal reference to immigrants with dark and white skin complexion and 3 for reference to immigrants with white skin complexion only.

V32 Immigrant sources (text) Coders should identify if any immigrant sources are quoted or cited in the story. 0 indicate that no immigrant sources is quoted, 1 indicate that an immigrant sources is represented in the news item. V33 Is any party/candidate position described as extreme? Coders should identify if a party or a political candidate is described in the news story as having extreme opinions towards the issue of immigrant. 0 indicate that there is no such reference, 1 indicate that a party or candidate is characterised as extreme.

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V33A Which party? Coders should identify the name of the party if V33 is given code 1. Parties to be coded are: Code Type Belgium Netherlands Norway Sweden UK US 1 Left

wing Groen SP SV Vänsterp.

2 Center left

Sp.a

PvdA AP Socialdemokratarna.

Labour Democrats

3 Center CD&V

CDA

KrF Folkpartiet. Lib.Dem

4 Center right

VLD VVD

H Kristdemokraterna.

Conservatives Republicans

5 Right Vlaams Belang

LPF

FrP Moderaterna

All other parties are coded as 6. V34 Is there description of disagreement within a party over the issue of immigration? Coders should identify the news item refer to a party disagreement over the issue of immigration. 0 indicate that there is no such reference, 1 indicate that such a party disagreement exist. V34A Which party? Coders should identify the name of the party if V34 is given code 1. Parties to be coded are: Code Type Belgium Netherlands Norway Sweden UK US 1 Left


2 Center left

Sp.a


Labour Democrats

3 Center CD&V

CDA


4 Center right

VLD VVD




LPF

FrP Moderaterna

All other parties are coded as 6.

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Government regulation (If V13/V14 = code 14-16 and 31-40) The next section is only to be coded for news items about immigration or integration V35 Main argument towards government regulation /free marked Coders should type 1 if the news story contains considerable negative evaluations or criticism towards government regulation or positive statements towards the free market. Code 2 should be assigned if the main argument in the news story seems favorable towards government regulation or is negative/critical towards free markets. If the news story includes both positive and negative statements towards government regulation/free marked the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral and just presents facts with no arguments or evaluation attached to these facts it should be coded as 3 (neutral). V36 Is there a reference to economic growth? If there is no reference to economic growth the article should be coded as 0.Coders should type 1 if the news story contains statements that government regulation will reduce growth or that the free market will increase economic growth. Code 2 should be assigned if the story includes statements that point a positive effect of government regulation on growth or a negative effect of free market on economic growth. If the news story includes both negative and positive statements about government regulation/ free market and economic growth the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral and just presents facts with no arguments or evaluation attached to these facts it should be coded as 3 (neutral). V37 Is there a reference to economic stability? If there is no reference to economic stability the article should be coded as 0. Coders should type 1 if the news story contains statements that government regulation will reduce stability or that the free market will increase stability. Code 2 should be assigned if the story includes statements that point a positive effect of government regulation on economic stability or a negative effect of free market on economic stability. If the news story includes both negative and positive statements about government regulation/ free market and economic stability the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral or stability are not really related to government regulation/ free market arguments it should be coded as 3. V38 Is there a reference to individual freedom? If there is no reference to individual freedom the article should be coded as 0. Coders should type 1 if the news story contains statements that government regulation will reduce individual freedom or that the free market will increase individual freedom. Code 2 should be assigned if the story includes statements that point a positive effect of government regulation on individual freedom or a negative effect of free market on individual freedom. If the news story includes both negative and positive statements about government regulation/ free market and individual freedom the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral or individual freedom is not really related to government regulation/ free market arguments it should be coded as 3. V39 Is there a reference to individual rights/opportunities? If there is no reference to individual rights/opportunities the article should be coded as 0. Coders should type 1 if the news story contains statements that government regulation will reduce individual rights or that the free market will increase individual rights. Code 2 should be assigned if the story includes statements that point a positive effect of government regulation on individual

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rights or a negative effect of free market on individual rights. If the news story includes both negative and positive statements about government regulation/ free market and individual rights the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral or individual rights are not really related to government regulation/ free market arguments it should be coded as 3. V40 Is there a reference to inequality? If there is no reference to inequality the article should be coded as 0. Coders should type 1 if the news story contains statements that government regulation will increase inequality or that the free market will have an opposite effect. Code 2 should be assigned if the story includes statements that point to a positive effect of government regulation on inequality or a negative effect of free market on inequality. If the news story includes both negative and positive statements about government regulation/ free market and inequality the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral or inequality are not really related to government regulation/ free market arguments it should be coded as 3. V41 Is there a reference to unemployment? If there is no reference to unemployment the article should be coded as 0. Coders should type 1 if the news story contains statements that government regulation will reduce unemployment or that the free market will increase unemployment. Code 2 should be assigned if the story includes statements that point to a negative effect of government regulation on unemployment or a positive effect of free market on unemployment. If the news story includes both negative and positive statements about government regulation/ free market and unemployment the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral or unemployment are not really related to government regulation/ free market arguments it should be coded as 3. V42 Is there a reference to taxes? If there is no reference to taxes the article should be coded as 0. Coders should type 1 if the news story contains statements that government regulation will not increase taxes or that the free market will increase taxes. Code 2 should be assigned if the story includes statements that indicate that government regulation will increase taxes or that free marked will reduce taxes. If the news story includes both negative and positive statements about government regulation/ free market and taxes the main argument should be identified according to the amount of time, frequency and\order of appearance of the various arguments. If the news story seems neutral or taxes are not really related to government regulation/ free market arguments it should be coded as 3. V43 Clearness of party/candidate positions. Coders should identify if the news story make a reference to whether position taken by a particular party or candidate is clear or unclear. Coders should type 0 if such reference is made. Code 1 if reference is made to a very clear party position and 2 if reference is made to a a unclear party position.

17

V43A To which political party is this comment directed? Coders should identify the name of the party if V43 is given code 1 or 2. Parties to be coded are: Code Type Belgium Netherlands Norway Sweden UK US 1 Left


2 Center left

Sp.a


Labour Democrats

3 Center CD&V

CDA


4 Center right

VLD VVD




LPF

FrP Moderaterna

All other parties are coded as 6. If V43 applies to several parties choose only party listed as main actor or main source. V44 Changing of party/ candidate positions. Coders should identify if the news story make a reference to whether or not a party/candidate position has been changed. Coders should type 0 if such reference is made. Apply code 1 if reference is made to a stable party position and 2 if reference is made to a changing or unstable party position. V44A To which political party is this comment directed? Coders should identify the name of the party if V44 is given code 1 or 2. Parties to be coded are: Code Type Belgium Netherlands Norway Sweden UK US 1 Left


2 Center left

Sp.a


Labour Democrats

3 Center CD&V

CDA


4 Center right

VLD VVD




LPF

FrP Moderaterna

All other parties are coded as 6. If V44 applies to several parties choose only party listed as main actor or main source. V45 In what direction is it said that a party\actor has changed its position: Coders should identify the direction of change if V45 is given code 2. Code 1 if Party/candidate now is described as more opposed to government regulation and code 2 if party/candidate now is described as more supportive of government regulation V46 Is any party/candidate position described as extreme? Coders should identify if a party or a political candidate is described in the news story as having extreme opinions towards the issue of government regulation/free marked. 0 indicate that there is no such reference, 1 indicate that a party or candidate is characterised as extreme.

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V46A Which party? Coders should identify the name of the party if V46 is given code 1. Parties to be coded are: Code Type Belgium Netherlands Norway Sweden UK US 1 Left


2 Center left

Sp.a


Labour Democrats

3 Center CD&V

CDA


4 Center right

VLD VVD




LPF

FrP Moderaterna

All other parties are coded as 6. V47 Is there description of disagreement within a party over the issue of government regulation? Coders should identify the news item refer to a party disagreement over the issue of government regulation. 0 indicate that there is no such reference, 1 indicate that such a party disagreement exist. V47A Which party? Coders should identify the name of the party if V47 is given code 1. Parties to be coded are: Code Type Belgium Netherlands Norway Sweden UK US 1 Left


2 Center left

Sp.a


Labour Democrats

3 Center CD&V

CDA


4 Center right

VLD VVD




LPF

FrP Moderaterna

All other parties are coded as 6.

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Education (Norway and Sweden only) (If V13/V14 = code 17)

V48. Is the main focus of the content generally negative towards some aspect of the education system? 0: No 1: Yes 2: Does not apply V49. Is there a discussion about foundational skills (reading/writing, mathematics, and natural science)? 0: No 1: Yes, should be more focus on foundational skills 2: Yes, should be less focus on foundational skills V50. Is there a discussion about academic differences between pupils in schools? 0: No 1: Yes, there are too large differences between pupils 2: Yes, there are no large differences between pupils V51. Is there a discussion about the teaching of social skills in the education system? 0: No 1: Yes, there should be more focus on social skills 2: Yes, there should be less focus on social skills V52. Is there a debate about education in relation to the national welfare system? 0: No 1: Yes, the current education system illustrates a great welfare system 2: Yes, the current education system illustrates problems with the welfare system V53. Is there a debate about gender differences in the education system? 0: No 1: Yes, the education system favours girls 2: Yes, the education system favour boys 3: Yes, the education system does not create gender differences V54. Is there a debate about differences between social classes in schools? 0: No. 1: Yes, the education system favours middle- or upper class 2: Yes, the education system favours the lower class 3: Yes, social classes are irrelevant for success in the education system V55. Is there a debate about education and ethnicity? 0: No 1: Yes, the education system favours ethnic citizens 2: Yes, the education system favours immigrants 3: Yes, ethnic background is irrelevant for success in the education system

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V56: Is there a debate related to education infrastructure (buildings, ict, restructuring, etc)? 0: No 1: Yes, there are problems or a conflict related to infrastructure 2: Yes, positive aspects related to infrastructure are debated 3: Yes, infrastructure is debated in a balanced or a neutral way V57: Actor/source criticising current education policy/system: Is there a source or an actor in the news story that criticize current educational policies? (If more than one, pick the most important by a combination of amount of time, frequency and order of appearance). - No criticism go to V60 - Yes, politician from a party in government - Yes, politician from a party in opposition - Yes, academics, other experts - Yes, from organization (e.g. teacher unions) - Yes, public official - Yes, other actors

V58: Who does main criticiser blame? Who does main criticiser blame for current problems? 1. Current government 2. Former government 3. The profession (teachers, incl the teachers education) 4. Academics (e.g. bad pedagogic theories) 5. Public official 6. Other 7. None V59: Reference to national measurement: Do the main criticiser use results on national measurements as an argument for his/her view? 0. No 1. Yes 2. Can’t tell V60: Reference to international measurement: Do the main criticiser use results on international measurement (e.g. PISA & TIMMS) as an argument for his/her view? 3. No 4. Yes 5. Can’t tell V61: Reference to other countries Does the main criticiser refer to other countries in arguing the way he/she does? 0. No 1– 99. List of countries (see appendix for country codes)

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V62: Actor/source defending current educational policy/system: Is there a source or an actor in the news story that defend current educational policies? (If more than one, pick the most important by a combination of amount of time, frequency and order of appearance). 0. No actor defending policy/system this is last variable to be coded 1. Yes, politician from a party in government 2. Yes, politician from a party in opposition 3. Yes, academics, other experts 4. Yes, from organization (e.g. teacher unions) 5. Yes, public official 6. Yes, other actors

V63: Who gets the credit? If there are identified actors that defend the education system/policies, who do they give credit to? 1. Current government 2. Former government 3. The profession (teachers, incl the teachers education) 4. Academics 5. Public official 6. Other 7. None V64: Reference to national measurement: Do the main defender use results on national measurement as an argument for his/her view? 0. No 1. Yes 2. Can’t tell V65: Reference to international measurement: Do the main defender use results on international measurement (e.g. PISA and TIMMS) as an argument for his/her view? 0. No 1. Yes 2. Can’t tell

V66: Reference to other countries Does the main criticiser refer to other countries in arguing the way he/she does? 0. No 1. 99. List of countries (see appendix for country codes)

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Code Sheet Six-Nation Study on Media Systems, News Content and Perceptions of Reality V1 Identification number Belgian news items should start with 1xxxxxx, Dutch news items with 2xxxxxx, Norwegian news items with 3xxxxxx, Swedish news items with 4xxxxxx, UK news items with 5xxxxxx and finally US news items with 6xxxxxx. The second digit should refer to the news medium (se values 1 to 5 in V4). The third digit should refer to the coder id number. V2A Country Country 1: Belgium 2: Netherlands 3: Norway 4: Sweden 5: UK 6: US V2B Population Population of each country is reported in absolute numbers. 4 600 000: Norway 6 300 000: Belgium 9 100 000: Sweden 16 600 000: Netherlands 61 100 000: UK 307 200 000: US V2C Coder identification number 1: Toril Aalberg 2: Tove Brekken (Coordinator of US & UK news content) 3: Egbert Leppink (Coordinator of Belgian and Dutch news content) 4: Audun Fladmoe (Coordinator of Norwegian and Swedish news content) 5: Berit Kvaløy 6: Nils Erik Bjørge 7: Ron van Blokland V3 Date (four numbers where the first two marks the month and the second two the day) V4A Medium 1: TV1 (PBS or main broadcaster) 2: TV2 (Commercial or second largest broadcaster) 3: Newspaper 1 (Elite/quality newspaper) 4: Newspaper 2 (Tabloid/popular newspaper) 5: Newspaper 3 (Regional newspaper)

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V4B Circulation, Newspapers Circulation figures from 2008 included in content analysis Belgium Netherlands Norway Sweden UK US Print Elite

102 280 263204

247 556 335 600 845,167 1,000,665

Print Tabloid

340 899 695635

284 414 368 200 3,073,106 2,293,310

Print Regional

127 960 116513 77 044 242 400 62290 110,999

V4C Viewer ratings, Television Average viewer statistic from 2007 Belgium Netherlands Norway Sweden UK US Broadcast Public (Except NBC in USA)

756000 1630000 706000 1023000 4850000 8400000


630000 101000 494000 491000 3750000 8300000

V5 Placement of news item (Numeric indicating page or news item number. For newspapers, if article runs over several pages refer to the starting page). V5A Newspaper unit (Indicating if page refers to main/first unit or regular additional unit/supplements). 1: Main/ first unit 2: Second unit/supplement 3: Third unit/supplement 4: Forth unit/supplement 5: Fifth unit/supplement V6 Status of news item Considers top-3 TV news as headlines, and all newspapers front page items 0: Does not apply (not headline of front news) 1: Headline/front page item 2: Other item on front page V7A Size of news item TV Continually indicate seconds on TV. V7B Size of news item TV, recoded Recorded seconds for each news item recoded into categories. 1: XS ( > 10 sec.) 2: S (11-30 sec.) 3: M (31-90 sec.) 4: L (91-150 sec.) 5: XL (> 150 sec.)

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V7C Size of news item Newspaper (size include pictures for newspapers) 1: notes (up to 10 % of a page) 2: small (between 10-30 % of a page) 3: medium (between 30 -70 % of a page) 4: large (between 70 - 150 % of a page) 5: extra large (more then 150 % of a page) V8 News section 1: General news (inc. main page and sections with no specific heading) 2: Domestic news 3: Economy and trade 4: Foreign news 5: Regional/local news 6: Culture 7: Sport 8: Entertainment 9: Lifestyle (house and home, fashion, travel) 10: Traffic and transportation 11: Crime 12: Consumer news 13: IT and computers/ Technology 14: Weather 15: Children 16: Other V9 Contextualised or decontextualised (thematic vs episodic frame) 1: Contextualised 2: Decontextualised (V10 -12 only to be coded if V8 is coded as 1 through 5) V10 Foreign news /Primary country mentioned (see appendix 1 for country codes, continuous 0 to 207 – CODE 0 FOR DOMESTIC CONTENT) V11 Secondary foreign country (see appendix 1 for country codes, continuous 0 to 207 – CODE 0 FOR DOMESTIC CONTENT) V12 Tertiary Foreign country (see appendix 1 for country codes, continuous 0 to 207 – CODE 0 FOR DOMESTIC CONTENT)

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V13 PRIMARY THEME/ISSUE OF NEWS ITEM 01-09 World politics 01: War, armed and military conflict 02: Terrorism 03: Immigration, refugees and border issues 04: Third World and development aid 05: Global Warming & climate change 06: Energy supply & Oil issues 07: Nuclear (dis-)armament & other means of mass destruction 08: EU-enlargement 09: Foreign politics/diplomacy 10: Other Wold Politics issues 11-21 Politic areas 11: Housing/Urban affairs 12: Integration 13: Environment issues 14: Poverty, Social and Welfare policies 15: Healthcare issues (including child/elderly care)/Public health 16: Labour policies 17: Education issues 18: Family matters 19: Transportation and traffic 20: Justice Affairs (incl. Gun control/Justice department affairs) 21: Other domestic politics issues 22-30. Political areas and the political game 22: Party politics 23: Political campaigns and elections 24: Personal focus on candidates/politicians/public officials 25: Democracy and structural reforms 26: Human Rights, Civil liberties, freedom of speech and Minority discrimination 27: Government (legislative and executive branch) 28: Social unrest/Civil Strife/labour unrest 29: Consumer issues 30: Other news about the political game 31-40 Business 31: General economy developments and trends 32: Trade/commerce 33: Prices/interest rates 34: Monetary/fiscal policy 35: Stock market 36: Individual company performance or sector performance 37: Public sector finance (taxes, budgets) 38: Collective bargaining 39: Agriculture/farming/rural issues/fishing 40: Other business issues 41-49 Crime/Punishment and Accidents 41: Police work, overall security and customs 42: Court cases and claims

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43: Prison issues and punishment issues 44: White collar crimes, counterfeit and corruption 45: Sex & drug related crimes 46: Violent crimes 47: Accidents 48: Emergencies and disasters 49: Other 911-stories 50-59 Culture/Arts and Religion 50: Fine Art; Books, Theatre, Music 51: Popular culture; popular music, media and film 52: Culture Industry (business issues) 53: News media reporting about (other) news media 54: Religion & Church issues 55: Personal Stories about Faith & Philosophy 56: Cultural Traditions (eg. Easter, Hanukkah) 57: - 58: The Muhammad Cartoon-Crises 59: Other Culture 60-69 Sports and Betting 60: National (and local) sports events (incl.mass/popular sport) 61: Internationals sports events (home team vs. foreigners) 62: Foreign sports events 63: Sports Stars/Celebrities 64: Sports doping and other types of cheating 65: Sports economics – including Media sports rights 66: Olympic Games and other mega-events in the past and future 67: Betting and lottery 68: - 69: Other sports 70-79 Lifestyle/Family and Health 70: Hobbies, leisure and interior 71: Tourism 72: Beauty/fashion/fitness/wellness 73: Retirement/the elderly 74: Shopping 75: Food and Drinks 76: Tobaccos and Cigarettes 77: Obesity 78: Alcohol and drug issues (e.g. abuse related) 79: Other Lifestyle /Family/Health Issues 80-89 Entertainment/Celebrities and Gossip 80: Sex/love/romance/weddings 81: Divorce/Battering/Suicide 82: Sensations & Curiosities (e.g. duck with four legs) 83: Other human interest (ordinary citizens) 84: Other human interest (celebrity) 85: Hero/Villain-stories about criminals/detectives/victims 86: Royalty

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87: Personal focus on public officials/scandal 88: Personal focus on individual celebrity/scandal 89: Other Entertainment 90-99 History, Science, Technology and other 90: Science & Research 91: Innovations & New Gadgets 92: National History 93: International History 94: Technology 95: Organic/Ecology 96: Natural disasters and response to them 97: Weather 98: Animals 99: Other Issues/No theme V14 SECONDARY THEME/ISSUE OF NEWS ITEM same categories as V13 + 0 = Does not apply (do not code more than one item per theme in V13 + V14 in sum)

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Remaining variables only to be coded if V13/V14 is coded as a) Immigration (code 03 and 12) Immigration and integration

or b) Government regulation including (Code 14 -16 and 31-40) (Welfare, labour and health

policies & Business 37) or

c) Education (17) (NB: Norway and Sweden only) ****************************************************************************** V15A – V18A Story actor – main/nr 1 1: Cabinet member 2: Party A or a representative from party A (Left wing parties – Socialists/greens etc) 3: Party B or a representative from party B (Center left parties – Labor, social democrats etc) 4: Party C or a representative from party C (Center parties – Christian Democrats/ liberals etc) 5: Party D or a representative from party D (Center right parties – Conservatives, Republican etc) 6: Party E or a representative from party E (Right wing parties – Progressive party, Vlaams Belang etc.) 7: Other party or representative from other party 8: Foreign politician/foreign parties/foreign governments 9: Government official 10: NGO’s or NGO representative 11: Academics, other experts 12: Business leaders or private companies 13: Celebrities 14: Journalists/media representatives/media 15: Ordinary citizens 16: Anonymous actors 99: Does not apply (no main, second, third or fourth story actor) V15B – V18B Gender of story actor – nr 1

1. Female 2. Male 3. Does not apply / cannot tell

V19A – V22A Sources for quotes – nr 1 1: Cabinet member 2: Party A or a representative from party A (Left wing parties – Socialists/greens etc) 3: Party B or a representative from party B (Center left parties – Labor, social democrats etc) 4: Party C or a representative from party C (Center parties – Christian Democrats/ liberals etc) 5: Party D or a representative from party D (Center right parties – Conservatives, Republican etc) 6: Party E or a representative from party E (Right wing parties – Progressive party, Vlaams Belang etc.) 7: Other party or representative from other party 8: Foreign politician/foreign parties/foreign governments 9: Government official 10: NGO’s or NGO representative 11: Academics, other experts 12: Business leaders or private companies 13: Celebrities 14: Journalists/media representatives/media 15: Ordinary citizens 16: Anonymous actors 99: Does not apply (no main, second, third or fourth source)

29

V19B – V22B Gender of source – nr 1 1. Female 2. Male 3. Does not apply/cannot tell

Next sections: Issue specific variables only Immigration (If V13/V14 = code 03 or 12) V23. Main argument towards immigration 1. General anti immigration/immigrants argument 2. Neutral or generally pro immigration/immigrants argument V24. Is there a reference to economic arguments? 0. No 1. Yes, immigrants exploit benefits 2. Yes, need immigrants as labour/human recourses V25. Is there a reference to cultural arguments? 0. No 1. Yes, immigrants is a threat to national/local culture 2. Yes, immigrants create cultural diversity V26. Is there a reference to crime? 0. No 1. Yes, immigrants increase/create crime 2. Yes, immigrants are victim of crime V27. Is there a reference to laws that regulate immigration? 0. No 1. Yes, need stricter/maintain laws to reduce immigrants or limit immigrant rights 2. Yes, need to maintain/improve laws that secures immigrants rights (prevent discrimination) V28. Are immigrants mainly framed as a problem or a resource in the news story? 1. As a problem 2. As a resource 3. Both a problem and a resource 4. Cannot say V29. Is there a geographical reference to where immigrants originate from? 0. No 1. Yes: Western Europe, North America or Oseania 2. Yes: Eastern Europe (including Russia) 3. Yes: South America, Asia or Africa V30. Is there an explicit reference to main religious background of immigrants? 0. No 1. Yes: Christian 2. Yes: Muslim 3. Yes: Other religion

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V30a. Is there an implicit reference to main religious background of immigrants? 4. No 5. Yes: Christian 6. Yes: Muslim 7. Yes: Other religion V31. Does the news story present picture(s) of immigrants that reflect skin complexion? 0. No 1. Yes; mainly of immigrants with dark skin complexion (non-white) 2. Yes; Immigrants with dark and white skin complexion is equally represented in pictures 3. Yes; mainly of immigrants with white skin complexion V32. Immigrant sources (text) 0. No 1. Yes 2. Cannot tell V33. Is any party/candidate position described as extreme? 0. No 1. Yes V33a V33. Which party? 1: Left wing party (Socialists/greens etc) 2: Center left party (Labor, social democrats etc) 3: Center party (Christian Democrats/ liberals etc) 4: Center right party (Conservatives, Republican etc) 5: Right wing party (Progressive party, Vlaams Belang etc.) 6: Other parties V34. Is there description of disagreement within a party over the issue of immigration? 0. No 1. Yes V34a V34a. Which party? 1: Left wing party (Socialists/greens etc) 2: Center left party (Labor, social democrats etc) 3: Center party (Christian Democrats/ liberals etc) 4: Center right party (Conservatives, Republican etc) 5: Right wing party (Progressive party, Vlaams Belang etc.) 6: Other parties

31

Government regulation (If V13/V14 = code 14-16 and 31-40) V35. Main argument towards government regulation /free marked 1. General anti government regulation or pro free marked 2. General pro government regulation or anti free marked 3. Neutral to government regulation/free marked V36. Is there a reference to economic growth? 0. No 1: Yes, government regulation will reduce growth/ free marked will increase growth 2: Yes, government regulation will increase growth/ free marked reduce growth 3: Yes, but not at all related to government regulation/free marked (or totally neutral) V37. Is there a reference to economic stability? 0. No 1: Yes, government regulation will reduce stability/ free marked will increase stability 2: Yes, government regulation will increase stability/ free marked will reduce stability 3: Yes, but not at all related to government regulation/free marked (or totally neutral) V38. Is there a reference to individual freedom? 0. No 1: Yes, government regulation will reduce individual freedom/ free marked increase ind. freedom 2: Yes, government regulation will increase individual freedom/ free marked reduce ind. freedom 3: Yes, but not at all related to government regulation/free marked (or totally neutral) V39. Is there a reference to individual rights/opportunities? 0. No 1: Yes, government regulation will reduce individual rights/ free marked increase ind. rights 2: Yes, government regulation will increase individual rights/ free marked reduce ind. rights 3: Yes, but not at all related to government regulation/free marked (or totally neutral) V40. Is there a reference to inequality/welfare? 0. No 2: Yes, government regulation will reduce welfare for all/ increase inequality / free marked + 1: Yes, government regulation will increase welfare for all / reduce inequality/ free marked - 3: Yes, but not at all related to government regulation/free marked (or totally neutral) V41. Is there a reference to unemployment? 0. No 1: Yes, government regulation will reduce unemployment? / free marked - 2: Yes, government regulation will increase unemployment?/ free marked + 3: Yes, but not at all related to government regulation/free marked (or totally neutral) V42. Is there a reference to taxes? 0. No 1: Yes, government regulation will not increase taxes? / free marked - 2: Yes, government regulation will increase taxes?/ free marked + 3: Yes, but not at all related to government regulation/free marked (or totally neutral)

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V43. Clearness of party/candidate positions. In the story, are there any comments that the position taken by a particular party or candidate is (un)clear? 0. No 1. Yes, position is clear V43a 2. Yes, position is unclear V43a V43a. To which political party is this comment directed? (If this applies to several parties choose only party listed as main actor or main source) 1: Left wing party (Socialists/greens etc) 2: Center left party (Labor, social democrats etc) 3: Center party (Christian Democrats/ liberals etc) 4: Center right party (Conservatives, Rebublican etc) 5: Right wing party (Progressive party, Vlaams Belang etc.) 6: Other parties

V44. Changing of party/ candidate positions. In the story, are there any comments that a particular party or politician is changing its position regarding government regulation? 0. No 1. Yes, position has not been changing 2. Yes, position has been changing V44a + V45

V44a. To which political party is this comment directed? (If this applies to several parties choose only party listed as main actor or main source) 1: Left wing party (Socialists/greens etc) 2: Center left party (Labor, social democrats etc) 3: Center party (Christian Democrats/ liberals etc) 4: Center right party (Conservatives, Rebublican etc) 5: Right wing party (Progressive party, Vlaams Belang etc.) 6: Other parties V45: In what direction is it said that a party\actor has changed its position: 1. Party/candidate are now more opposed to government regulation 2. Party/candidate are now more supportive of government regulation V46. Is any party/candidate position described as extreme? 0. No 1. Yes V46 V46a. Which party? 1: Left wing party (Socialists/greens etc) 2: Center left party (Labor, social democrats etc) 3: Center party (Christian Democrats/ liberals etc) 4: Center right party (Conservatives, Republican etc) 5: Right wing party (Progressive party, Vlaams Belang etc.) 6: Other parties V47. Is there description of disagreement within a party over the issue of government regulation? 0. No 1. Yes V47a

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V47a. Which party? 1: Left wing party (Socialists/greens etc) 2: Center left party (Labor, social democrats etc) 3: Center party (Christian Democrats/ liberals etc) 4: Center right party (Conservatives, Republican etc) 5: Right wing party (Progressive party, Vlaams Belang etc.) 6: Other parties

34

Education (Norway and Sweden only) (If V13/V14 = code 17) V48. Is the main focus of the content generally negative towards some aspect of the education system? 0: No 1: Yes 2: Does not apply V49. Is there a discussion about foundational skills (reading/writing, mathematics, and natural science)? 0: No 1: Yes, should be more focus on foundational skills 2: Yes, should be less focus on foundational skills V50. Is there a discussion about academic differences between pupils in schools? 0: No 1: Yes, there are too large differences between pupils 2: Yes, there are no large differences between pupils V51. Is there a discussion about the teaching of social skills in the education system? 0: No 1: Yes, there should be more focus on social skills 2: Yes, there should be less focus on social skills V52. Is there a debate about education in relation to the national welfare system? 0: No 1: Yes, the current education system illustrates a great welfare system 2: Yes, the current education system illustrates problems with the welfare system V53. Is there a debate about gender differences in the education system? 0: No 1: Yes, the education system favours girls 2: Yes, the education system favour boys 3: Yes, the education system does not create gender differences V54. Is there a debate about differences between social classes in schools? 0: No. 1: Yes, the education system favours middle- or upper class 2: Yes, the education system favours the lower class 3: Yes, social classes are irrelevant for success in the education system V55. Is there a debate about education and ethnicity? 0: No 1: Yes, the education system favours ethnic citizens 2: Yes, the education system favours immigrants 3: Yes, ethnic background is irrelevant for success in the education system

35

V56: Is there a debate related to education infrastructure (buildings, ict, restructuring, etc)? 0: No 1: Yes, there are problems or a conflict related to infrastructure 2: Yes, positive aspects related to infrastructure are debated 3: Yes, infrastructure is debated in a balanced or a neutral way V57: Actor/source criticising current education policy/system: Is there a source or an actor in the news story that criticize current educational policies? (If more than one, pick the most important by a combination of amount of time, frequency and order of appearance). - No criticism go to V60 - Yes, politician from a party in government - Yes, politician from a party in opposition - Yes, academics, other experts - Yes, from organization (e.g. teacher unions) - Yes, public official - Yes, other actors

V58: Who does main criticiser blame? Who does main criticiser blame for current problems? 8. Current government 9. Former government 10. The profession (teachers, incl the teachers education) 11. Academics (e.g. bad pedagogic theories) 12. Public official 13. Other 14. None V59: Reference to national measurement: Do the main criticiser use results on national measurements as an argument for his/her view? 6. No 7. Yes 8. Can’t tell V60: Reference to international measurement: Do the main criticiser use results on international measurement (e.g. PISA & TIMMS) as an argument for his/her view? 9. No 10. Yes 11. Can’t tell V61: Reference to other countries Does the main criticiser refer to other countries in arguing the way he/she does? 1. No 1– 99. List of countries (see appendix for country codes)

36

V62: Actor/source defending current educational policy/system: Is there a source or an actor in the news story that defend current educational policies? (If more than one, pick the most important by a combination of amount of time, frequency and order of appearance). 7. No actor defending policy/system this is last variable to be coded 8. Yes, politician from a party in government 9. Yes, politician from a party in opposition 10. Yes, academics, other experts 11. Yes, from organization (e.g. teacher unions) 12. Yes, public official 13. Yes, other actors

V63: Who gets the credit? If there are identified actors that defend the education system/policies, who do they give credit to? 8. Current government 9. Former government 10. The profession (teachers, incl the teachers education) 11. Academics 12. Public official 13. Other 14. None V64: Reference to national measurement: Do the main defender use results on national measurement as an argument for his/her view? 3. No 4. Yes 5. Can’t tell V65: Reference to international measurement: Do the main defender use results on international measurement (e.g. PISA and TIMMS) as an argument for his/her view? 3. No 4. Yes 5. Can’t tell

V66: Reference to other countries Does the main criticiser refer to other countries in arguing the way he/she does? 2. No 3. 99. List of countries (see appendix for country codes)

37

APPENDIX 1 WORLD COUNTRIES 0 Domestic 1 Afghanistan 2 Albania 3 Algeria 4 Andorra 5 Angola 6 Antigua & Barbuda 7 Argentina 8 Armenia 9 Australia 10 Austria 11 Azerbaijan 12 Bahamas 13 Bahrain 14 Bangladesh 15 Barbados 16 Belarus 17 Belgium 18 Belize 19 Benin 20 Bhutan 21 Bolivia 22 Bosnia & Herzegovina 23 Botswana 24 Brazil 25 Brunei Darussalam 26 Bulgaria 27 Burkina Faso 28 Burma (Myanmar) 29 Burundi 30 Cambodia 31 Cameroon 32 Canada 33 Cape Verde 34 Central African Republic 35 Chad 36 Chile 37 China 38 Colombia 39 Comoros 40 Congo 41 Democratic Republic of the Costa Rica 42 Côte d'Ivoire 43 Croatia 44 Cuba 45 Cyprus 46 Czech Republic 47 Denmark 48 Djibouti 49 Dominica

50 Dominican Republic 51 Egypt 52 El Salvador 53 Equatorial Guinea 54 Eritrea 55 Estonia 56 Ethiopia 57 Fiji 58 Finland 59 France 60 Gabon 61 Gambia 62 Georgia 63 Germany 64 Ghana 65 Greece 66 Grenada 67 Guatemala 68 Guinea 69 Guinea-Bissau 70 Guyana 71 Haiti 72 Honduras 73 Hungary 74 Iceland 75 India 76 Indonesia 77 Iran 78 Iraq 79 Ireland 80 Israel 81 Italy 82 Jamaica 83 Japan 84 Jordan 85 Kazakhstan 86 Kenya 87 Kiribati 88 Korea, North 89 Korea, South 90 Kuwait 91 Kyrgyzstan 92 Laos 93 Latvia 94 Lebanon 95 Lesotho 96 Liberia 97 Libya 98 Liechtenstein 99 Lithuania 100 Luxembourg 101 Macedonia

38

102 Madagascar 103 Malawi 104 Malaysia 105 Maldives 106 Mali 107 Malta 108 Marshall Islands 109 Mauritania 110 Mauritius 111 Mexico 112 Micronesia 113 Moldova 114 Monaco 115 Mongolia 116 Montenegro 117 Morocco 118 Mozambique 119 Namibia 120 Nauru 121 Nepal 122 The Netherlands 123 New Zealand 124 Nicaragua 125 Niger 126 Nigeria 127 Norway 128 Oman 129 Pakistan 130 Palau 131 Palestinian State* 132 Panama 133 Papua New Guinea 134 Paraguay 135 Peru 136 The Philippines 137 Poland 138 Portugal 139 Qatar 140 Romania 141 Russia 142 Rwanda 143 St. Kitts & Nevis 144 St. Lucia 145 St. Vincent & The Grenadines 146 Samoa 147 San Marino 148 São Tomé & Príncipe 149 Saudi Arabia 150 Senegal 151 Serbia 152 Seychelles 153 Sierra Leone

154 155 Singapore 156 Slovakia 157 Slovenia 158 Solomon Islands 159 Somalia 160 South Africa 161 Spain 162 Sri Lanka 163 Sudan 164 Suriname 165 Swaziland 166 Sweden 167 Switzerland 168 Syria 169 Taiwan 170 Tajikistan 171 Tanzania 172 Thailand 173 Togo 174 Tonga 175 Trinidad & Tobago 176 Tunisia 177 Turkey 178 Turkmenistan 179 Tuvalu 180 Uganda 181 Ukraine 182 United Arab Emirates 183 United Kingdom 184 United States 185 Uruguay 186 Uzbekistan 187 Vanuatu 188 Vatican City (Holy See) 189 Venezuela 190 Vietnam 191 Western Sahara* 192 Yemen 193 Zaire 194 Zambia 195 Zimbabwe 196 Arctic 197 Antarctica 198 Historical states (e.g. USSR, Yugoslavia) 199 Other 200 Everywhere/ nowhere (country not important)

39

201 Asia 202 Oceania 203 North America 204 South America 205 Africa 206 Middle East 207 Europe

40

Reliability Missing data material Coordinating data collection in six countries definitely represents a challenge and it is almost inevitable that there will be some missing data material. An overview over missing cases for each country/medium and the reason why these cases are missing are presented below. As for news broadcasts omitted or rescheduled due to sports; omitted broadcasts were not replaced and is therefore listed below as missing. Rescheduled newscasts were coded and are included in the dataset. There was no missing data material for The Netherlands or for Norway. Belgium2

Medium 1, PBS, 01.07: missing data material.

Medium 2, commercial channel, 01.25: missing data material. Medium 3, elite newspaper, 01.24 & 11.22: missing data material. Sweden Medium 4&5, 0106: January 6th is a national holiday in Sweden and thus there were no newspaper editions on this date. Medium 2, commercial channel, 01.19, 01.21 & 01.24: news broadcasts omitted due to sports. UK Medium 2, commercial channel, 01.24: news broadcasts omitted due to sports. US Medium 2, ABC, 11.22 & 11.23: news broadcasts omitted due to sports. Medium 4, USAToday: Published Monday thru Friday. We believe the overview shows that the data is as complete as can be expected for such a large study. In principle the data should have included 252 separate TV recordings over 21 dates and 321 newspaper editions over 18 dates, giving us a total of 573 recordings/editions to collect. Of this, only 4 recordings/editions (below 1 percent) are missing due to technical problems. Intercoder reliability Great effort has also been made to secure good reliability of this study. The simplest and most common method of reporting intercoder reliability is the percent agreement statistic. This statistic reflects the number of agreements per total number of coding decisions. Holsti's (1969) coefficient of reliability (C. R.) provides a formula for calculating percent agreement: the number of agreements between two different coders divided by the number of judgements. For percent agreement figures, Riffe, Lacy, and Fico (1998) state that, in communication research, "a minimum level of 80% is usually the standard" (Riffe, D., Lacy, S., & Fico, F.(1998). Analyzing media messages: Quantitative content analysis. New Jersey: Lawrence Erlbaum Associates, Inc.) We selected a random sample of news items to be coded

2 Week 2 for the regional newspaper is a proxy consisting of every other date from week 47 & week 4.

41

by two different coders. For television, we selected one broadcast from each outlet from a random week. The same was done for the different newspapers – we double coded one edition of the elite and the tabloid3

newspapers for each country. The dataset consists of several subsets and the ICR-test refers to the main part of the dataset (variables 1 thru 14). The following variables are included in the test:

V3 Date V4A Medium V5a/b Placement/unit V6 Status of news item V7B/C Size (percent of page/seconds recoded) V8 Section V9 News frame V10* Primary country mentioned V13* Primary issue The marked * variables were recoded: V10 V10_x Primary country mentioned Domestic (value 0) Foreign (Values > 1) V13 V10_x Primary issue Hard news (values 1 – 40) Soft news (Values 41 -99) The tables below show the results of the intercoder reliability test. The overall coefficient of reliability (C. R.) is 0,94 which is well above a minimum level of 80 percent agreement between coders. The tables show a high level of intercoder reliability for both television and newspapers for all six countries. We believe the high intercoder reliability is a result of intense preparations and training of coders. Details about ICR for each media type for all six countires can be found in the tables. IRC total (television & newspapers) US UK Netherlands Belgium Sweden Norway Total Number of jugdements 3731 3487 4702 6318 1879 2674 22791

Number of agreements 3446 3280 4420 5900 1759 2542 21347

C.R. 0,92 0,94 0.94 0.93 0,94 0,95 0,94 N 376 352 238 322 191 271 1750

3 Regional newspapers are not included in the ICR-test.

42

IRC Television – all countries US UK Netherlands Belgium Sweden Norway Total Number of jugdements

261 297 522 1098 279 324 2781

Number of agreements

237 279 490 1010 270 313 2599

C.R. 0,91 0,94 0,94 0,92 0,97 0,97 0,93 N 62 33 29 61 31 36 252 IRC Newspapers – all countries US UK Netherlands Belgium Sweden Norway Total Number of jugdements 3470 3190 4180 5220 1600 2350 20010

Number of agreements 3209 3001 3930 4890 1489 2229 18748

C.R. 0,92 0,94 0,94 0,94 0,93 0,95 0,94 N 347 319 209 261 160 235 1531

44

Frequency distributions V2A_COUNTRY COUNTRY Frequency Percent Valid Percent Valid 1 Belgium 10025 22,3 22,3 2 Netherlands 6034 13,4 13,4 3 Norway 6439 14,3 14,3 4 Sweden 5849 13,0 13,0 5 UK 8342 18,6 18,6 6 US 8232 18,3 18,3 Total 44921 100,0 100,0 V2B_POPULATION POPULATION OF COUNTRY IN ABSOLUTE NUMBERS Frequency Percent Valid Percent Valid 4600000 Norway 6439 14,3 14,3 6300000 Belgium 10025 22,3 22,3 9100000 Sweden 5849 13,0 13,0 16600000 Netherlands 6034 13,4 13,4 61100000 UK 8342 18,6 18,6 307200000 US 8232 18,3 18,3 Total 44921 100,0 100,0 V2C_CODER_IDNUMBER CODER IDENTIFICATION NUMBER Frequency Percent Valid Percent Valid 1 Toril Aalberg 1763 3,9 3,9 2 Tove Brekken 3117 6,9 6,9 3 Egbert Leppink 9228 20,5 20,5 4 Audun Fladmoe 2097 4,7 4,7 5 Berit Kvaloy 10734 23,9 23,9 6 Nils Erik Bjorge 12167 27,1 27,1 7 Ron van Blokland 5815 12,9 12,9 Total 44921 100,0 100,0

45

V3_DATE DATE (MM/DD) Frequency Percent Valid Percent Valid 0105 2313 5,1 5,1 0106 2327 5,2 5,2 0107 2567 5,7 5,7 0108 2570 5,7 5,7 0109 2660 5,9 5,9 0110 2367 5,3 5,3 0111 179 ,4 ,4 0119 2331 5,2 5,2 0120 2403 5,3 5,3 0121 2383 5,3 5,3 0122 2539 5,7 5,7 0123 2768 6,2 6,2 0124 2126 4,7 4,7 0125 219 ,5 ,5 1117 2411 5,4 5,4 1118 2446 5,4 5,4 1119 2581 5,7 5,7 1120 2719 6,1 6,1 1121 2594 5,8 5,8 1122 2241 5,0 5,0 1123 177 ,4 ,4 Total 44921 100,0 100,0 V4A_MEDIUM TYPE OF MEDIUM Frequency Percent Valid Percent Valid 1 Public Service (PBS) / Main

Broadcast 2405 5,4 5,4

2 Commercial / Second Largest Broadcast

1936 4,3 4,3

3 Elite / Quality Newspaper 13687 30,5 30,5 4 Tabloid / Popular Newspaper 14184 31,6 31,6 5 Regional Newspaper 12709 28,3 28,3 Total 44921 100,0 100,0

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V4B_CIRCULATION_NP NEWSPAPER_CIRCULATION FIGURES 2008 Frequency Percent Valid Percent Valid 62290 UK-Print Regional 2304 5,1 5,7 77044 Norway-Print Regional 1948 4,3 4,8 102280 Belgium-Print Elite 1994 4,4 4,9 110999 US-Print Regional 1642 3,7 4,0 116513 Netherlands-Print

Regional 1697 3,8 4,2

127960 Belgium-Print Regional 3186 7,1 7,9 242400 Sweden-Print Regional 1932 4,3 4,8 247556 Norway-Print Elite 1813 4,0 4,5 263204 Netherlands-Print Elite 1746 3,9 4,3 284414 Norway-Print Tabloid 1969 4,4 4,9 335600 Sweden-Print Elite 1867 4,2 4,6 340899 Belgium-Print Tabloid 3888 8,7 9,6 368200 Sweden-Print Tabloid 1187 2,6 2,9 695635 Netherlands-Print Tabloid 2000 4,5 4,9 845167 UK-Print Elite 2856 6,4 7,0 1000665 US-Print Elite 3411 7,6 8,4 2293310 US-Print Tabloid 2605 5,8 6,4 3073106 UK-Print Tabloid 2535 5,6 6,2 Total 40580 90,3 100,0 Missing System 4341 9,7 Total 44921 100,0 V4C_RATINGS_TV TV_AVERAGE VIEWER RATINGS 2007 Frequency Percent Valid Percent Valid 101000 Netherlands-Commercial

Broadcast 315 ,7 7,3

491000 Sweden-Commercial Broadcast

343 ,8 7,9

494000 Norway-Commercial Broadcast

283 ,6 6,5

630000 Belgium-Commercial Broadcast

420 ,9 9,7

706000 Norway-PBS 426 ,9 9,8 756000 Belgium-PBS 537 1,2 12,4 1023000 Sweden-PBS 520 1,2 12,0 1630000 Netherlands-PBS 276 ,6 6,4 3750000 UK-Commercial

Broadcast 306 ,7 7,0

4850000 UK-PBS 341 ,8 7,9 8300000 US-Commercial

Broadcast (ABC) 269 ,6 6,2

8400000 US-PBS (NBC) 305 ,7 7,0 Total 4341 9,7 100,0 Missing System 40580 90,3 Total 44921 100,0

47

V5_PLACEMENT PLACEMENT OF NEWS ITEM WITHIN MEDIUM. Pagenumber for newspapers and presentation sequence of news items for TV Frequency Percent Valid Percent Valid 1 4097 9,1 9,2 2 2616 5,8 5,9 3 2240 5,0 5,0 4 2142 4,8 4,8 5 1514 3,4 3,4 6 2055 4,6 4,6 7 1651 3,7 3,7 8 1719 3,8 3,9 9 1623 3,6 3,6 10 1301 2,9 2,9 11 1304 2,9 2,9 12 1252 2,8 2,8 13 1250 2,8 2,8 14 1141 2,5 2,6 15 1122 2,5 2,5 16 955 2,1 2,1 17 918 2,0 2,1 18 1003 2,2 2,2 19 856 1,9 1,9 20 781 1,7 1,8 21 706 1,6 1,6 22 673 1,5 1,5 23 693 1,5 1,6 24 621 1,4 1,4 25 732 1,6 1,6 26 636 1,4 1,4 27 541 1,2 1,2 28 473 1,1 1,1 29 503 1,1 1,1 30 400 ,9 ,9 31 362 ,8 ,8 32 358 ,8 ,8 33 458 1,0 1,0 34 359 ,8 ,8 35 280 ,6 ,6 36 264 ,6 ,6 37 307 ,7 ,7 38 205 ,5 ,5 39 224 ,5 ,5 40 270 ,6 ,6 41 259 ,6 ,6 42 220 ,5 ,5 43 234 ,5 ,5 44 127 ,3 ,3 45 150 ,3 ,3 46 136 ,3 ,3 47 97 ,2 ,2 48 157 ,3 ,4 49 165 ,4 ,4 50 158 ,4 ,4 51 122 ,3 ,3

48

52 144 ,3 ,3 53 92 ,2 ,2 54 140 ,3 ,3 55 125 ,3 ,3 56 133 ,3 ,3 57 80 ,2 ,2 58 65 ,1 ,1 59 40 ,1 ,1 60 64 ,1 ,1 61 85 ,2 ,2 62 112 ,2 ,3 63 121 ,3 ,3 64 77 ,2 ,2 65 45 ,1 ,1 66 62 ,1 ,1 67 44 ,1 ,1 68 38 ,1 ,1 69 53 ,1 ,1 70 46 ,1 ,1 71 25 ,1 ,1 72 45 ,1 ,1 73 37 ,1 ,1 74 59 ,1 ,1 75 28 ,1 ,1 76 37 ,1 ,1 77 30 ,1 ,1 78 37 ,1 ,1 79 15 ,0 ,0 80 23 ,1 ,1 81 13 ,0 ,0 82 30 ,1 ,1 83 19 ,0 ,0 84 37 ,1 ,1 85 20 ,0 ,0 86 26 ,1 ,1 87 9 ,0 ,0 88 19 ,0 ,0 89 12 ,0 ,0 90 11 ,0 ,0 91 16 ,0 ,0 92 13 ,0 ,0 93 4 ,0 ,0 94 9 ,0 ,0 95 5 ,0 ,0 96 5 ,0 ,0 97 5 ,0 ,0 98 2 ,0 ,0 99 1 ,0 ,0 100 3 ,0 ,0 102 1 ,0 ,0 118 1 ,0 ,0 Total 44593 99,3 100,0 Missing System 328 ,7 Total 44921 100,0

49

V5A_NEWSPAPERUNIT PLACEMENT OF NEWS ITEM IN WHICH NEWSPAPER UNIT/SUPPLEMENT Frequency Percent Valid Percent Valid 1 Main/First unit 23454 52,2 57,8 2 Second unit 11191 24,9 27,6 3 Third unit 5374 12,0 13,2 4 Fourth unit 561 1,2 1,4 Total 40580 90,3 100,0 Missing System 4341 9,7 Total 44921 100,0 V6_STATUS STATUS OF NEWS ITEM Frequency Percent Valid Percent Valid 0 Does not apply 38145 84,9 84,9 1 Headline/Frontpage Item 3787 8,4 8,4 2 Other Item on Frontpage 2989 6,7 6,7 Total 44921 100,0 100,0 V7B_SIZE_TV_RECODED TV: SIZE OF NEWS ITEM IN SECONDS, RECODED Frequency Percent Valid Percent Valid 1 XS ( <10 sec.) 820 1,8 18,9 2 S (11 - 30 sec.) 1023 2,3 23,6 3 M (31 - 90 sec.) 711 1,6 16,4 4 L (91 - 150 sec.) 1084 2,4 25,0 5 XL (>150 sec.) 703 1,6 16,2 Total 4341 9,7 100,0 Missing System 40580 90,3 Total 44921 100,0 V7C_SIZE_NP NEWSPAPERS: SIZE OF NEWS ITEM IN PERCENTAGES OF A PAGE Frequency Percent Valid Percent Valid 1 Notes ( < 10 percent) 21427 47,7 52,8 2 Small (10 - 30 percent) 10247 22,8 25,3 3 Medium (30 - 70 percent) 5878 13,1 14,5 4 Large (70 - 150 percent) 2333 5,2 5,7 5 Extra Large (>150 percent) 695 1,5 1,7 Total 40580 90,3 100,0 Missing System 4341 9,7 Total 44921 100,0

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V8_NEWSSECTION EXPLICIT PLACEMENT OF NEWS ITEM IN A SPESIFIC NEWSSECTION Frequency Percent Valid Percent Valid 1 General News 15408 34,3 34,3 2 Domestic News 2522 5,6 5,6 3 Economy and Trade 5531 12,3 12,3 4 Foreign News 2748 6,1 6,1 5 Regional/Local News 3618 8,1 8,1 6 Culture 1764 3,9 3,9 7 Sport 9592 21,4 21,4 8 Entertainment 1265 2,8 2,8 9 Lifestyle (house and home,

fashion, travel) 741 1,6 1,6

10 Traffic and Transportation 27 ,1 ,1 11 Crime 39 ,1 ,1 12 Consumer News 160 ,4 ,4 13 IT and Computers/Technology 94 ,2 ,2 14 Weather 60 ,1 ,1 15 Children 10 ,0 ,0 16 Other 1342 3,0 3,0 Total 44921 100,0 100,0 V9_NEWSFRAME CONTEXTUALISED OR DECONTEXTUALISED NEWSFRAME Frequency Percent Valid Percent Valid 1 Contextualized 7258 16,2 16,2 2 Decontextualized 37626 83,8 83,8 Total 44884 99,9 100,0 Missing System 37 ,1 Total 44921 100,0 V10_COUNTRY_1st PRIMARY COUNTRY MENTIONED Frequency Percent Valid Percent Valid 0 Domestic 22350 49,8 73,2 1 Afghanistan 116 ,3 ,4 2 Albania 3 ,0 ,0 3 Algeria 5 ,0 ,0 5 Angola 2 ,0 ,0 6 Antigua & Barbuda 1 ,0 ,0 7 Argentina 19 ,0 ,1 8 Armenia 1 ,0 ,0 9 Australia 94 ,2 ,3 10 Austria 29 ,1 ,1 11 Azerbaijan 3 ,0 ,0 12 Bahamas 3 ,0 ,0 13 Bahrain 3 ,0 ,0 14 Bangladesh 4 ,0 ,0 15 Barbados 1 ,0 ,0 16 Belarus 1 ,0 ,0 17 Belgium 247 ,5 ,8 21 Bolivia 3 ,0 ,0 22 Bosnia & Herzegovina 6 ,0 ,0 24 Brazil 32 ,1 ,1 26 Bulgaria 16 ,0 ,1

51

27 Burkina Faso 1 ,0 ,0 28 Burma (Myanmar) 18 ,0 ,1 29 Burundi 2 ,0 ,0 30 Cambodia 9 ,0 ,0 31 Cameroon 1 ,0 ,0 32 Canada 40 ,1 ,1 36 Chile 2 ,0 ,0 37 China 260 ,6 ,9 38 Colombia 22 ,0 ,1 40 Congo 148 ,3 ,5 41 Democratic Republic of Costa Rica 1 ,0 ,0 43 Croatia 2 ,0 ,0 44 Cuba 19 ,0 ,1 45 Cyprus 8 ,0 ,0 46 Czech Republic 11 ,0 ,0 47 Denmak 50 ,1 ,2 50 Dominican Republic 1 ,0 ,0 51 Egypt 34 ,1 ,1 52 El Salvador 4 ,0 ,0 55 Estonia 2 ,0 ,0 56 Ethiopia 1 ,0 ,0 58 Finland 34 ,1 ,1 59 France 284 ,6 ,9 60 Gabon 1 ,0 ,0 61 Gambia 3 ,0 ,0 62 Georgia 14 ,0 ,0 63 Germany 298 ,7 1,0 64 Ghana 14 ,0 ,0 65 Greece 33 ,1 ,1 67 Guatemala 9 ,0 ,0 68 Guinea 1 ,0 ,0 69 Guinea_Bissau 3 ,0 ,0 70 Guyana 1 ,0 ,0 71 Haiti 7 ,0 ,0 73 Hungary 8 ,0 ,0 74 Iceland 84 ,2 ,3 75 India 124 ,3 ,4 76 Indonesia 32 ,1 ,1 77 Iran 47 ,1 ,2 78 Iraq 119 ,3 ,4 79 Ireland 38 ,1 ,1 80 Israel 466 1,0 1,5 81 Italy 105 ,2 ,3 83 Japan 103 ,2 ,3 84 Jordan 3 ,0 ,0 85 Kazakhstan 2 ,0 ,0 86 Kenya 20 ,0 ,1 88 North Korea 18 ,0 ,1 89 South Korea 25 ,1 ,1 90 Kuwait 1 ,0 ,0 93 Latvia 5 ,0 ,0 94 Lebanon 16 ,0 ,1 96 Liberia 13 ,0 ,0 97 Libya 8 ,0 ,0 99 Lithuania 2 ,0 ,0

52

100 Luxembourg 7 ,0 ,0 101 Macedonia 1 ,0 ,0 102 Madagascar 5 ,0 ,0 103 Malawi 1 ,0 ,0 104 Malaysia 3 ,0 ,0 106 Mali 11 ,0 ,0 110 Mauritius 1 ,0 ,0 111 Mexico 45 ,1 ,1 114 Monaco 2 ,0 ,0 115 Mongolia 1 ,0 ,0 117 Moroco 25 ,1 ,1 118 Mozambique 1 ,0 ,0 121 Nepal 8 ,0 ,0 122 The Netherlands 261 ,6 ,9 123 New Zealand 8 ,0 ,0 124 Nicaraqua 4 ,0 ,0 125 Niger 1 ,0 ,0 126 Nigeria 7 ,0 ,0 127 Norway 38 ,1 ,1 128 Oman 5 ,0 ,0 129 Pakistan 68 ,2 ,2 131 Palestinian State 379 ,8 1,2 132 Panama 1 ,0 ,0 133 Papua New Guinea 2 ,0 ,0 135 Peru 5 ,0 ,0 136 The Philippines 5 ,0 ,0 137 Poland 28 ,1 ,1 138 Portugal 5 ,0 ,0 140 Romania 12 ,0 ,0 141 Russia 302 ,7 1,0 142 Rwanda 17 ,0 ,1 149 Saudi Arabia 26 ,1 ,1 150 Senegal 4 ,0 ,0 151 Serbia 17 ,0 ,1 155 Singapore 5 ,0 ,0 156 Slovakia 2 ,0 ,0 159 Somalia 132 ,3 ,4 160 South Africa 28 ,1 ,1 161 Spain 115 ,3 ,4 162 Sri Lanka 41 ,1 ,1 163 Sudan 9 ,0 ,0 164 Suriname 4 ,0 ,0 165 Swaziland 1 ,0 ,0 166 Sweden 59 ,1 ,2 167 Switzerland 34 ,1 ,1 168 Syria 7 ,0 ,0 169 Taiwan 4 ,0 ,0 171 Tanzania 9 ,0 ,0 172 Thailand 36 ,1 ,1 173 Togo 1 ,0 ,0 176 Tunesia 8 ,0 ,0 177 Turkey 56 ,1 ,2 180 Uganda 7 ,0 ,0 181 Ukraine 38 ,1 ,1 182 Unites Arab Emirates 11 ,0 ,0

53

183 United Kingdom 389 ,9 1,3 184 United States 1514 3,4 5,0 185 Uruguay 2 ,0 ,0 186 Uzbekistan 2 ,0 ,0 188 Vatican City 22 ,0 ,1 189 Venezuela 17 ,0 ,1 190 Vietnam 10 ,0 ,0 192 Yemen 5 ,0 ,0 193 Zaire 1 ,0 ,0 195 Zimbabwe 39 ,1 ,1 196 Arctic 1 ,0 ,0 197 Antarctica 13 ,0 ,0 198 Historical States (e.g. USSR,

Yugoslavia) 4 ,0 ,0

199 Other 39 ,1 ,1 200 Everywhere/nowhere (Country

not important) 303 ,7 1,0

201 Asia 16 ,0 ,1 203 North America 274 ,6 ,9 204 South America 9 ,0 ,0 205 Africa 29 ,1 ,1 206 Middle East 25 ,1 ,1 207 Europe 373 ,8 1,2 Total 30516 67,9 100,0 Missing System 14405 32,1 Total 44921 100,0 V11_COUNTRY_2nd 2nd COUNTRY MENTIONED Frequency Percent Valid Percent Valid 0 Domestic 364 ,8 6,8 1 Afghanistan 105 ,2 2,0 2 Albania 8 ,0 ,1 3 Algeria 9 ,0 ,2 5 Angola 2 ,0 ,0 7 Argentina 12 ,0 ,2 8 Armenia 1 ,0 ,0 9 Australia 33 ,1 ,6 10 Austria 14 ,0 ,3 12 Bahamas 1 ,0 ,0 13 Bahrain 3 ,0 ,1 17 Belgium 138 ,3 2,6 18 Belize 3 ,0 ,1 21 Bolivia 2 ,0 ,0 22 Bosnia & Herzegovina 7 ,0 ,1 24 Brazil 13 ,0 ,2 26 Bulgaria 7 ,0 ,1 28 Burma (Myanmar) 7 ,0 ,1 29 Burundi 1 ,0 ,0 30 Cambodia 2 ,0 ,0 31 Cameroon 3 ,0 ,1 32 Canada 16 ,0 ,3 33 Cape Verder 1 ,0 ,0 36 Chile 3 ,0 ,1 37 China 104 ,2 1,9

54

38 Colombia 7 ,0 ,1 40 Congo 34 ,1 ,6 41 Democratic Republic of Costa Rica 1 ,0 ,0 43 Croatia 7 ,0 ,1 44 Cuba 30 ,1 ,6 45 Cyprus 6 ,0 ,1 46 Czech Republic 13 ,0 ,2 47 Denmak 45 ,1 ,8 51 Egypt 27 ,1 ,5 54 Eritrea 2 ,0 ,0 55 Estonia 5 ,0 ,1 56 Ethiopia 8 ,0 ,1 57 Fiji 1 ,0 ,0 58 Finland 14 ,0 ,3 59 France 199 ,4 3,7 60 Gabon 1 ,0 ,0 61 Gambia 1 ,0 ,0 62 Georgia 9 ,0 ,2 63 Germany 192 ,4 3,6 64 Ghana 3 ,0 ,1 65 Greece 12 ,0 ,2 67 Guatemala 1 ,0 ,0 68 Guinea 2 ,0 ,0 70 Guyana 1 ,0 ,0 71 Haiti 2 ,0 ,0 73 Hungary 8 ,0 ,1 74 Iceland 24 ,1 ,4 75 India 51 ,1 ,9 76 Indonesia 10 ,0 ,2 77 Iran 23 ,1 ,4 78 Iraq 90 ,2 1,7 79 Ireland 30 ,1 ,6 80 Israel 468 1,0 8,7 81 Italy 51 ,1 ,9 83 Japan 45 ,1 ,8 84 Jordan 2 ,0 ,0 85 Kazakhstan 7 ,0 ,1 86 Kenya 31 ,1 ,6 88 North Korea 3 ,0 ,1 89 South Korea 14 ,0 ,3 93 Latvia 3 ,0 ,1 94 Lebanon 7 ,0 ,1 95 Lesotho 1 ,0 ,0 96 Liberia 5 ,0 ,1 97 Libya 3 ,0 ,1 100 Luxembourg 28 ,1 ,5 101 Macedonia 1 ,0 ,0 102 Madagascar 1 ,0 ,0 104 Malaysia 3 ,0 ,1 105 Maldives 1 ,0 ,0 106 Mali 6 ,0 ,1 107 Malta 1 ,0 ,0 110 Mauritius 1 ,0 ,0 111 Mexico 18 ,0 ,3 113 Moldova 2 ,0 ,0

55

114 Monaco 1 ,0 ,0 117 Moroco 40 ,1 ,7 118 Mozambique 1 ,0 ,0 121 Nepal 3 ,0 ,1 122 The Netherlands 257 ,6 4,8 123 New Zealand 7 ,0 ,1 125 Niger 3 ,0 ,1 126 Nigeria 12 ,0 ,2 127 Norway 21 ,0 ,4 128 Oman 2 ,0 ,0 129 Pakistan 56 ,1 1,0 131 Palestinian State 526 1,2 9,8 134 Paraguay 1 ,0 ,0 135 Peru 12 ,0 ,2 136 The Philippines 3 ,0 ,1 137 Poland 29 ,1 ,5 138 Portugal 9 ,0 ,2 139 Qatar 1 ,0 ,0 140 Romania 14 ,0 ,3 141 Russia 153 ,3 2,8 142 Rwanda 27 ,1 ,5 149 Saudi Arabia 44 ,1 ,8 151 Serbia 12 ,0 ,2 153 Sierra Leone 2 ,0 ,0 155 Singapore 2 ,0 ,0 156 Slovakia 4 ,0 ,1 159 Somalia 57 ,1 1,1 160 South Africa 23 ,1 ,4 161 Spain 76 ,2 1,4 163 Sudan 4 ,0 ,1 164 Suriname 3 ,0 ,1 166 Sweden 67 ,1 1,2 167 Switzerland 24 ,1 ,4 168 Syria 1 ,0 ,0 169 Taiwan 3 ,0 ,1 171 Tanzania 2 ,0 ,0 172 Thailand 23 ,1 ,4 176 Tunesia 5 ,0 ,1 177 Turkey 25 ,1 ,5 180 Uganda 9 ,0 ,2 181 Ukraine 111 ,2 2,1 182 Unites Arab Emirates 12 ,0 ,2 183 United Kingdom 144 ,3 2,7 184 United States 481 1,1 9,0 188 Vatican City 10 ,0 ,2 189 Venezuela 6 ,0 ,1 192 Yemen 3 ,0 ,1 194 Zambia 2 ,0 ,0 195 Zimbabwe 11 ,0 ,2 197 Antarctica 5 ,0 ,1 198 Historical States (e.g. USSR,

Yugoslavia) 7 ,0 ,1


not important) 23 ,1 ,4

56

201 Asia 24 ,1 ,4 203 North America 49 ,1 ,9 204 South America 9 ,0 ,2 205 Africa 37 ,1 ,7 206 Middle East 43 ,1 ,8 207 Europe 396 ,9 7,4 Total 5370 12,0 100,0 Missing System 39551 88,0 Total 44921 100,0 V12_COUNTRY_3rd 3rd COUNTRY MENTIONED Frequency Percent Valid Percent Valid 0 Domestic 82 ,2 3,8 1 Afghanistan 42 ,1 2,0 2 Albania 1 ,0 ,0 3 Algeria 7 ,0 ,3 5 Angola 1 ,0 ,0 7 Argentina 4 ,0 ,2 8 Armenia 2 ,0 ,1 9 Australia 9 ,0 ,4 10 Austria 6 ,0 ,3 11 Azerbaijan 1 ,0 ,0 16 Belarus 1 ,0 ,0 17 Belgium 40 ,1 1,9 19 Benin 2 ,0 ,1 22 Bosnia & Herzegovina 3 ,0 ,1 24 Brazil 13 ,0 ,6 26 Bulgaria 10 ,0 ,5 29 Burundi 1 ,0 ,0 32 Canada 10 ,0 ,5 33 Cape Verder 1 ,0 ,0 36 Chile 2 ,0 ,1 37 China 39 ,1 1,8 38 Colombia 2 ,0 ,1 40 Congo 5 ,0 ,2 43 Croatia 2 ,0 ,1 44 Cuba 6 ,0 ,3 45 Cyprus 2 ,0 ,1 46 Czech Republic 9 ,0 ,4 47 Denmak 18 ,0 ,8 51 Egypt 52 ,1 2,4 55 Estonia 4 ,0 ,2 56 Ethiopia 1 ,0 ,0 58 Finland 11 ,0 ,5 59 France 112 ,2 5,2 62 Georgia 3 ,0 ,1 63 Germany 76 ,2 3,5 64 Ghana 3 ,0 ,1 65 Greece 9 ,0 ,4 73 Hungary 10 ,0 ,5 74 Iceland 11 ,0 ,5 75 India 23 ,1 1,1 76 Indonesia 1 ,0 ,0 77 Iran 12 ,0 ,6

57

78 Iraq 20 ,0 ,9 79 Ireland 13 ,0 ,6 80 Israel 100 ,2 4,7 81 Italy 12 ,0 ,6 83 Japan 26 ,1 1,2 84 Jordan 4 ,0 ,2 86 Kenya 16 ,0 ,7 89 South Korea 3 ,0 ,1 90 Kuwait 2 ,0 ,1 93 Latvia 3 ,0 ,1 94 Lebanon 16 ,0 ,7 96 Liberia 1 ,0 ,0 97 Libya 9 ,0 ,4 99 Lithuania 4 ,0 ,2 100 Luxembourg 19 ,0 ,9 101 Macedonia 1 ,0 ,0 104 Malaysia 1 ,0 ,0 105 Maldives 1 ,0 ,0 110 Mauritius 1 ,0 ,0 111 Mexico 3 ,0 ,1 114 Monaco 2 ,0 ,1 117 Moroco 14 ,0 ,7 118 Mozambique 2 ,0 ,1 122 The Netherlands 81 ,2 3,8 123 New Zealand 3 ,0 ,1 126 Nigeria 3 ,0 ,1 127 Norway 15 ,0 ,7 129 Pakistan 24 ,1 1,1 131 Palestinian State 139 ,3 6,5 135 Peru 2 ,0 ,1 136 The Philippines 2 ,0 ,1 137 Poland 9 ,0 ,4 138 Portugal 7 ,0 ,3 139 Qatar 2 ,0 ,1 140 Romania 10 ,0 ,5 141 Russia 68 ,2 3,2 142 Rwanda 4 ,0 ,2 149 Saudi Arabia 32 ,1 1,5 150 Senegal 1 ,0 ,0 151 Serbia 6 ,0 ,3 153 Sierra Leone 1 ,0 ,0 156 Slovakia 7 ,0 ,3 157 Slovenia 1 ,0 ,0 159 Somalia 13 ,0 ,6 160 South Africa 7 ,0 ,3 161 Spain 40 ,1 1,9 163 Sudan 2 ,0 ,1 164 Suriname 2 ,0 ,1 166 Sweden 17 ,0 ,8 167 Switzerland 15 ,0 ,7 168 Syria 8 ,0 ,4 169 Taiwan 1 ,0 ,0 171 Tanzania 1 ,0 ,0 172 Thailand 2 ,0 ,1 176 Tunesia 4 ,0 ,2

58

177 Turkey 21 ,0 1,0 180 Uganda 5 ,0 ,2 181 Ukraine 66 ,1 3,1 182 Unites Arab Emirates 3 ,0 ,1 183 United Kingdom 103 ,2 4,8 184 United States 189 ,4 8,8 185 Uruguay 2 ,0 ,1 187 Vanuatu 1 ,0 ,0 190 Vietnam 1 ,0 ,0 192 Yemen 2 ,0 ,1 193 Zaire 1 ,0 ,0 194 Zambia 3 ,0 ,1 195 Zimbabwe 2 ,0 ,1 198 Historical States (e.g. USSR,

Yugoslavia) 4 ,0 ,2


not important) 3 ,0 ,1

201 Asia 15 ,0 ,7 203 North America 19 ,0 ,9 204 South America 8 ,0 ,4 205 Africa 23 ,1 1,1 206 Middle East 27 ,1 1,3 207 Europe 187 ,4 8,7 Total 2142 4,8 100,0 Missing System 42779 95,2 Total 44921 100,0

59

V13_PRIMARY_ISSUE_THEME PRIMARY ISSUE OR THEME OF STORY Frequency Percent Valid Percent Valid 1 War, armed and military conflict 1522 3,4 3,4 2 Terrorism 314 ,7 ,7 3 Immigration, Refugees and Border

Issues 135 ,3 ,3

4 Third World and Development Aid 84 ,2 ,2 5 Global Warming & Climate Change 63 ,1 ,1 6 Energy Supply and Oil Issues 383 ,9 ,9 7 Nuclear (dis-) armament & Other

means of mass destruction 17 ,0 ,0

8 EU-Enlargement 27 ,1 ,1 9 Foreign Politics/Diplomacy 376 ,8 ,8 10 Other World Politics Issues 160 ,4 ,4 11 Housing/Urban Affairs 315 ,7 ,7 12 Integration 29 ,1 ,1 13 Environment Issues 372 ,8 ,8 14 Poverty, Social and Welfare

Policies 140 ,3 ,3

15 Healthcare Issues (including child/elderly care)/Public Health

635 1,4 1,4

16 Labour Policies 214 ,5 ,5 17 Education Issues 478 1,1 1,1 18 Family Matters 118 ,3 ,3 19 Transportation and Traffic 737 1,6 1,6 20 Justice Affairs (incl. gun

Control/Justice Department Affairs) 323 ,7 ,7

21 Other Domestic Politics Issues 830 1,8 1,8 22 Party Politics 298 ,7 ,7 23 Political Campaigns and Elections 382 ,9 ,9 24 Personal Focus on

Candidates/Politicians/Public Officials 1338 3,0 3,0

25 Democracy and Structural Reform 62 ,1 ,1 26 Human Rights, Civil Liberties,

Freedom of Speech and Minority Discrimination

231 ,5 ,5

27 Government (Legislative and Executive Branch)

221 ,5 ,5

28 Social Unrest/Civil Strife/Labour Unrest

178 ,4 ,4

29 Consumer Issues 430 1,0 1,0 30 Other News About the Political

Game 411 ,9 ,9

31 World Economy Development and Trends

1005 2,2 2,2

32 Trade/Commerce 48 ,1 ,1 33 Prices/Interest rates 260 ,6 ,6 34 Monetary/Fiscal policy 371 ,8 ,8 35 Stock Market 467 1,0 1,0 36 Individual Companay Performance

or Sector Performance 2738 6,1 6,1

37 Public Sector Finance (taxes,budgets)

266 ,6 ,6

38 Collective Bargaining 35 ,1 ,1 39 Agricultural/Farming/Rural 119 ,3 ,3

60

Issues/Fishing 40 Other Business Issues 964 2,1 2,1 41 Police Work, overall security and

customs 717 1,6 1,6

42 Court cases and claims 1323 2,9 2,9 43 Prison Issues and Punishment

Issues 219 ,5 ,5

44 White Colar Crimes, Counterfeit, and Corruption

349 ,8 ,8

45 Sex & Drug Related Crimes 316 ,7 ,7 46 Violent Crimes 900 2,0 2,0 47 Accidents 974 2,2 2,2 48 Emergencies and Disasters 184 ,4 ,4 49 Other 911-stories 607 1,4 1,4 50 Fine Arts, Books, Theatre and

Music 939 2,1 2,1

51 Popular Culture, Popular Music, Media and Film

1373 3,1 3,1

52 Culture Industry (business issues) 306 ,7 ,7 53 News Media Reporting about

(other) News Media 330 ,7 ,7

54 Religion & Church Issues 194 ,4 ,4 55 Personal Stories about Faith and

Philosophy 11 ,0 ,0

56 Cultural Traditions (e.g. Easter, Hanukkah)

108 ,2 ,2

58 The Muhammed Cartoon-Crises 2 ,0 ,0 59 Other Culture 740 1,6 1,6 60 National (and local) sports events

(incl. Mass/Popular Sport) 2881 6,4 6,4

61 International Sports events (home team vs Foreigners)

1210 2,7 2,7

62 Foreign Sports Events 496 1,1 1,1 63 Sports Stars/Celebreties 2608 5,8 5,8 64 Sports Doping and Other types of

cheating 130 ,3 ,3

65 Sports Economics - Including Media Sports Rights

463 1,0 1,0

66 Olympic Games and other mega-events in the past and future

108 ,2 ,2

67 Betting and Lottery 54 ,1 ,1 69 Other Sports 2244 5,0 5,0 70 Hobbies, Leisure, and interior 233 ,5 ,5 71 Tourism 348 ,8 ,8 72 Beauty/fashion/fitness/wellness 206 ,5 ,5 73 Retirement/The Elderly 32 ,1 ,1 74 Shopping 99 ,2 ,2 75 Food and Drinks 265 ,6 ,6 76 Tobaccos and Cigarettes 37 ,1 ,1 77 Obesity 17 ,0 ,0 78 Alcohol and Drug Issues (e.g.

Abuse Related) 83 ,2 ,2

79 other Lifestyle/Family/Health Issues

709 1,6 1,6

80 Sex/love/Romance/Weddings 102 ,2 ,2

61

81 Divorce/Battering/Suicide 92 ,2 ,2 82 Sensations & Curiosities (e.g. duck

with four legs) 215 ,5 ,5

83 Other Human Interest Stories (Ordinary Citizens)

692 1,5 1,5

84 Other human Interest (Celebrity) 568 1,3 1,3 85 Hero/Villain-stories about

Crimianals, Detectives, Victims 27 ,1 ,1

86 Royalty 150 ,3 ,3 87 Personal Focus on Public

Officials/Scandals 88 ,2 ,2

88 Personal Focus on Individual Celebrity/Scandal

782 1,7 1,7

89 Other Entertainment 275 ,6 ,6 90 Science & Research 461 1,0 1,0 91 Innovations & News Gadgets 214 ,5 ,5 92 National History 96 ,2 ,2 93 International History 98 ,2 ,2 94 Technology 221 ,5 ,5 95 Organic/Ecology 23 ,1 ,1 96 Natural Disasters and Response to

them 137 ,3 ,3

97 Weather 400 ,9 ,9 98 Animals 377 ,8 ,8 99 Other Issues/No Theme 961 2,1 2,1 Total 44890 99,9 100,0 Missing System 31 ,1 Total 44921 100,0 V14_SECONDARY_ISSUE_THEME SECONDARY ISSUE OR THEME OF STORY Frequency Percent Valid Percent Valid 1 War, armed and military conflict 148 ,3 4,3 2 Terrorism 40 ,1 1,2 3 Immigration, Refugees and Border

Issues 44 ,1 1,3

4 Third World and Development Aid 8 ,0 ,2 5 Global Warming & Climate Change 18 ,0 ,5 6 Energy Supply and Oil Issues 31 ,1 ,9 8 EU-Enlargement 8 ,0 ,2 9 Foreign Politics/Diplomacy 89 ,2 2,6 10 Other World Politics Issues 17 ,0 ,5 11 Housing/Urban Affairs 17 ,0 ,5 12 Integration 15 ,0 ,4 13 Environment Issues 62 ,1 1,8 14 Poverty, Social and Welfare

Policies 28 ,1 ,8

15 Healthcare Issues (including child/elderly care)/Public Health

59 ,1 1,7

16 Labour Policies 38 ,1 1,1 17 Education Issues 33 ,1 1,0 18 Family Matters 16 ,0 ,5 19 Transportation and Traffic 56 ,1 1,6 20 Justice Affairs (incl. Gun

Control/Justice Department Affairs) 35 ,1 1,0

21 Other Domestic Politics Issues 87 ,2 2,5

62

22 Party Politics 31 ,1 ,9 23 Political Campaigns and Elections 16 ,0 ,5 24 Personal Focus on

Candidates/Politicians/Public Officials 124 ,3 3,6

25 Democracy and Structural Reform 6 ,0 ,2 26 Human Rights, Civil Liberties,

Freedom of Speech and Minority Discrimination

129 ,3 3,8

27 Government (Legislative and Executive Branch)

31 ,1 ,9

28 Social Unrest/Civil Strife/Labour Unrest

25 ,1 ,7

29 Consumer Issues 37 ,1 1,1 30 Other News About the Political

Game 22 ,0 ,6

31 World Economy Development and Trends

101 ,2 2,9

32 Trade/Commerce 12 ,0 ,3 33 Prices/Interest rates 22 ,0 ,6 34 Monetary/Fiscal policy 14 ,0 ,4 35 Stock Market 7 ,0 ,2 36 Individual Companay Performance

or Sector Performance 69 ,2 2,0

37 Public Sector Finance (taxes,budgets)

24 ,1 ,7

38 Collective Bargaining 2 ,0 ,1 39 Agricultural/Farming/Rural

Issues/Fishing 15 ,0 ,4

40 Other Business Issues 54 ,1 1,6 41 Police Work, overall security and

customs 36 ,1 1,0

42 Court Cases and Claims 143 ,3 4,2 43 Prison Issues and Punishment

Issues 7 ,0 ,2

44 White Colar Crimes, Counterfeit, and Corruption

65 ,1 1,9

45 Sex & Drug Related Crimes 28 ,1 ,8 46 Violent Crimes 178 ,4 5,2 47 Accidents 76 ,2 2,2 48 Emergencies and Disasters 6 ,0 ,2 49 Other 911-stories 36 ,1 1,0 50 Fine Arts, Books, Theatre and

Music 37 ,1 1,1

51 Popular Culture, Popular Music, Media and Film

87 ,2 2,5

52 Culture Industry (business issues) 5 ,0 ,1 53 News Media Reporting about

(other) News Media 41 ,1 1,2

54 Religion & Church Issues 36 ,1 1,0 55 Personal Stories about Faith and

Philosophy 1 ,0 ,0

56 Cultural Traditions (e.g. Easter, Hanukkah)

6 ,0 ,2

59 Other Culture 60 ,1 1,7 60 National (and local) sports events 8 ,0 ,2

63

(incl. Mass/Popular Sport) 61 International Sports events (home

team vs Foreigners) 12 ,0 ,3

62 Foreign Sports Events 3 ,0 ,1 63 Sports Stars/Celebreties 26 ,1 ,8 64 Sports Doping and Other types of

cheating 7 ,0 ,2

65 Sports Economics - Including Media Sports Rights

1 ,0 ,0

66 Olympic Games and other mega-events in the past and future

2 ,0 ,1

67 Betting and Lottery 6 ,0 ,2 69 Other Sports 24 ,1 ,7 70 Hobbies, Leisure, and interior 4 ,0 ,1 71 Tourism 21 ,0 ,6 72 Beauty/fashion/fitness/wellness 17 ,0 ,5 73 Retirement/The Elderly 7 ,0 ,2 74 Shopping 12 ,0 ,3 75 Food and Drinks 16 ,0 ,5 76 Tobaccos and Cigarettes 10 ,0 ,3 77 Obesity 6 ,0 ,2 78 Alcohol and Drug Issues (e.g.

Abuse Related) 20 ,0 ,6

79 Other Lifestyle/Family/Health Issues

93 ,2 2,7

80 Sex/love/Romance/Weddings 6 ,0 ,2 81 Divorce/Battering/Suicide 6 ,0 ,2 82 Sensations & Curiosities (e.g. duck

with four legs) 30 ,1 ,9

83 Other Human Interest Stories (Ordinary Citizens)

125 ,3 3,6

84 Other human Interest (Celebrity) 36 ,1 1,0 85 Hero/Villain-stories about

Crimianals, Detectives, Victims 10 ,0 ,3

86 Royalty 16 ,0 ,5 87 Personal Focus on Public

Officials/Scandals 15 ,0 ,4

88 Personal Focus on Individual Celebrity/Scandal

87 ,2 2,5

89 Other Entertainment 58 ,1 1,7 90 Science & Research 59 ,1 1,7 91 Innovations & News Gadgets 14 ,0 ,4 92 National History 11 ,0 ,3 93 International History 22 ,0 ,6 94 Technology 60 ,1 1,7 95 Organic/Ecology 2 ,0 ,1 96 Natural Disasters and Response to

them 9 ,0 ,3

97 Weather 46 ,1 1,3 98 Animals 66 ,1 1,9 99 Other Issues/No Theme 19 ,0 ,6 Total 3430 7,6 100,0 Missing System 41491 92,4 Total 44921 100,0

64

V15A_STORYACTOR_MAIN MAIN ACTOR IN NEWS STORY Frequency Percent Valid Percent Valid 1 Cabinet Minister 558 1,2 8,4 2 Representative from party A

(Left wing parties_Socialists/greens etc.)

17 ,0 ,3

3 Representative from party B (Center left parties - Labour, social democrats etc.)

52 ,1 ,8

4 Representative from party C (Center Parties -Christian Democrats/Liberals etc.)

16 ,0 ,2

5 Representative from party D (Center Right parties - Conservatives, Republican etc.)

49 ,1 ,7

6 Representative from party E (Right Wing Parties - Progressive party, Vlaams belang etc.)

9 ,0 ,1

7 Representative from other party 22 ,0 ,3 8 Foreign Politician 165 ,4 2,5 9 Government official 369 ,8 5,6 10 NGO representative 373 ,8 5,6 11 Academics, other experts 134 ,3 2,0 12 Business leaders/Private

companies 4003 8,9 60,4

13 Celebrities 6 ,0 ,1 14 Journalists/media

representatives 8 ,0 ,1

15 Ordinary Citizens 803 1,8 12,1 16 Anonymous actors 45 ,1 ,7 Total 6629 14,8 100,0 Missing 99 Does not apply/INAP 1040 2,3 System 37252 82,9 Total 38292 85,2 Total 44921 100,0 V15B_STORYACTOR_MAIN_GENDER GENDER OF MAIN STORY ACTOR Frequency Percent Valid Percent Valid 1 Female 366 ,8 19,0 2 Male 1556 3,5 81,0 Total 1922 4,3 100,0 Missing 3 Does not apply/cannot

tell 5313 11,8

System 37686 83,9 Total 42999 95,7 Total 44921 100,0

65

V16A_STORYACTOR_2nd 2nd ACTOR MENTIONED IN NEWS STORY Frequency Percent Valid Percent Valid 1 Cabinet Minister 241 ,5 9,3 2 Representative from party A


15 ,0 ,6


57 ,1 2,2


19 ,0 ,7


45 ,1 1,7


4 ,0 ,2


companies 1142 2,5 44,2


representatives 6 ,0 ,2

15 Ordinary Citizens 332 ,7 12,8 16 Anonymous actors 18 ,0 ,7 Total 2585 5,8 100,0 Missing 99 Does not apply/INAP 497 1,1 System 41839 93,1 Total 42336 94,2 Total 44921 100,0 V16B_STORYACTOR_2nd_GENDER GENDER OF 2nd STORY ACTOR Frequency Percent Valid Percent Valid 1 Female 180 ,4 19,7 2 Male 734 1,6 80,3 Total 914 2,0 100,0 Missing 3 Does not apply/cannot

tell 2161 4,8


66

V17A_STORYACTOR_3rd 3rd ACTOR MENTIONED IN NEWS STORY Frequency Percent Valid Percent Valid 1 Cabinet Minister 112 ,2 10,1 2 Representative from party A


10 ,0 ,9


40 ,1 3,6


14 ,0 1,3


46 ,1 4,1


3 ,0 ,3

7 Representative from other party 11 ,0 1,0 8 Foreign Politician 31 ,1 2,8 9 Government official 70 ,2 6,3 10 NGO representative 132 ,3 11,8 11 Academics, other experts 35 ,1 3,1 12 Business leaders/Private

companies 514 1,1 46,1

14 Journalists/media representatives

3 ,0 ,3

15 Ordinary Citizens 89 ,2 8,0 16 Anonymous actors 4 ,0 ,4 Total 1114 2,5 100,0 Missing 99 Does not apply/INAP 663 1,5 System 43144 96,0 Total 43807 97,5 Total 44921 100,0 V17B_STORYACTOR_3rd_GENDER GENDER OF 3rd ACTOR Frequency Percent Valid Percent Valid 1 Female 91 ,2 19,7 2 Male 371 ,8 80,3 Total 462 1,0 100,0 Missing 3 Does not apply/cannot

tell 1314 2,9


67

V18A_STORYACTOR_4th 4th ACTOR MENTIONED IN NEWS STORY Frequency Percent Valid Percent Valid 1 Cabinet Minister 49 ,1 8,8 2 Representative from party A


4 ,0 ,7


11 ,0 2,0


9 ,0 1,6


15 ,0 2,7


3 ,0 ,5

7 Representative from other party 10 ,0 1,8 8 Foreign Politician 19 ,0 3,4 9 Government official 24 ,1 4,3 10 NGO representative 68 ,2 12,2 11 Academics, other experts 11 ,0 2,0 12 Business leaders/Private

companies 279 ,6 49,9


2 ,0 ,4

15 Ordinary Citizens 52 ,1 9,3 16 Anonymous actors 3 ,0 ,5 Total 559 1,2 100,0 Missing 99 Does not apply/INAP 752 1,7 System 43610 97,1 Total 44362 98,8 Total 44921 100,0 V18B_STORYACTOR_4th_GENDER GENDER OF 4th ACTOR Frequency Percent Valid Percent Valid 1 Female 48 ,1 19,9 2 Male 193 ,4 80,1 Total 241 ,5 100,0 Missing 3 Does not apply/cannot

tell 1065 2,4


68

V19A_SOURES_QUOTES_1 SOURCES FOR QUOTES_1 Frequency Percent Valid Percent Valid 1 Cabinet Minister 425 ,9 8,7 2 Representative from party A


23 ,1 ,5


65 ,1 1,3


27 ,1 ,6


77 ,2 1,6


8 ,0 ,2

7 Representative from other party 26 ,1 ,5 8 Foreign Politician 139 ,3 2,8 9 Government official 495 1,1 10,1 10 NGO representative 462 1,0 9,5 11 Academics, other experts 521 1,2 10,7 12 Business leaders/Private

companies 2131 4,7 43,7


representatives 119 ,3 2,4

15 Ordinary Citizens 298 ,7 6,1 16 Anonymous actors 56 ,1 1,1 Total 4878 10,9 100,0 Missing 99 Does not apply/INAP 1748 3,9 System 38295 85,2 Total 40043 89,1 Total 44921 100,0 V19B_SOURES_QUOTES_1_GENDER GENDER OF SOURCE_1 Frequency Percent Valid Percent Valid 1 Female 690 1,5 18,2 2 Male 3094 6,9 81,8 Total 3784 8,4 100,0 Missing 3 Does not apply/cannot

tell 1918 4,3


69

V20A_SOURES_QUOTES_2 SOURES FOR QUOTES_2 Frequency Percent Valid Percent Valid 1 Cabinet Minister 157 ,3 7,3 2 Representative from party A


13 ,0 ,6


47 ,1 2,2


31 ,1 1,4


63 ,1 2,9


7 ,0 ,3


companies 708 1,6 32,8



15 Ordinary Citizens 213 ,5 9,9 16 Anonymous actors 30 ,1 1,4 Total 2159 4,8 100,0 Missing 99 Does not apply/INAP 538 1,2 System 42224 94,0 Total 42762 95,2 Total 44921 100,0 V20B_SOURCES_QUOTES_2_GENDER GENDER OF SOURCE_2 Frequency Percent Valid Percent Valid 1 Female 385 ,9 20,6 2 Male 1487 3,3 79,4 Total 1872 4,2 100,0 Missing 3 Does not apply/cannot

tell 813 1,8


70

V21A_SOURCES_QUOTES_3 SOURCES FOR QUOTES_3 Frequency Percent Valid Percent Valid 1 Cabinet Minister 63 ,1 5,8 2 Representative from party A


8 ,0 ,7


34 ,1 3,1


18 ,0 1,7


46 ,1 4,3


3 ,0 ,3





15 Ordinary Citizens 119 ,3 11,0 16 Anonymous actors 14 ,0 1,3 Total 1081 2,4 100,0 Missing 99 Does not apply/INAP 645 1,4 System 43195 96,2 Total 43840 97,6 Total 44921 100,0 V21B_SOURCES_QUOTES_3_GENDER GENDER OF SOURCE_3 Frequency Percent Valid Percent Valid 1 Female 195 ,4 20,4 2 Male 763 1,7 79,6 Total 958 2,1 100,0 Missing 3 Does not apply/cannot

tell 767 1,7


71

V22A_SOURCES_QUOTES_4 SOURCES FOR QUOTES_4 Frequency Percent Valid Percent Valid 1 Cabinet Minister 42 ,1 7,7 2 Representative from party A


6 ,0 1,1


10 ,0 1,8


11 ,0 2,0


16 ,0 2,9


2 ,0 ,4

7 Representative from other party 7 ,0 1,3 8 Foreign Politician 4 ,0 ,7 9 Government official 51 ,1 9,4 10 NGO representative 58 ,1 10,7 11 Academics, other experts 76 ,2 14,0 12 Business leaders/Private



14 ,0 2,6

15 Ordinary Citizens 66 ,1 12,2 16 Anonymous actors 8 ,0 1,5 Total 543 1,2 100,0 Missing 99 Does not apply/INAP 702 1,6 System 43676 97,2 Total 44378 98,8 Total 44921 100,0 V22B_SOURCES_QUOTES_4_GENDER GENDER OF SOURCE_4 Frequency Percent Valid Percent Valid 1 Female 89 ,2 18,6 2 Male 389 ,9 81,4 Total 478 1,1 100,0 Missing 3 Does not apply/cannot

tell 764 1,7


72

V23_MAINARGUMENT_IMMIGRATION MAIN ARGUMENT TOWARDS IMMIGRATION Frequency Percent Valid Percent Valid 1 General anti

immigration/immigrants argument 41 ,1 20,2

2 Neutral or generally pro immigration/immigrants argument

162 ,4 79,8

Total 203 ,5 100,0 Missing System 44718 99,5 Total 44921 100,0 V24_ECON_IMMIGRATION REFERENCE TO ECONOMIC ARGUMENTS REGARDING IMMIGRATION Frequency Percent Valid Percent Valid 0 No 181 ,4 88,7 1 Yes, immigrants exploit benefits 7 ,0 3,4 2 Yes, need immigrants as

labour/human resources 16 ,0 7,8

Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0 V25_CULTURE_IMMIGRATION REFERENCE TO CULTURAL ARGUMENTS REGARDING IMMIGRATION Frequency Percent Valid Percent Valid 0 No 198 ,4 97,1 1 Yes, immigrants is a threat to

national/local culture 2 ,0 1,0

2 Yes, immigrants create cultural diversity

4 ,0 2,0

Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0 V26_CRIME_IMMIGRATION REFERENCE TO CRIME ARGUMENTS REGARDING IMMIGRATION Frequency Percent Valid Percent Valid 0 No 170 ,4 83,3 1 Yes, immigrants

increase/create crime 30 ,1 14,7

2 Yes, immigrants are victim of crime

4 ,0 2,0

Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0

73

V27_LAWS_IMMIGRATION REFERENCE TO LAWS REGULATING IMMIGRATION Frequency Percent Valid Percent Valid 0 No 158 ,4 77,5 1 Yes, need stricter/maintain

laws to reduce immigrants of limit immigrant rights

28 ,1 13,7

2 Yes, need to maintain/improve laws that secures immigrants rights (prevent discrimination)

18 ,0 8,8

Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0 V28_FRAME_IMMIGRATION FRAMING OF IMMIGRANT STORY Frequency Percent Valid Percent Valid 1 As a problem 45 ,1 55,6 2 As a resource 15 ,0 18,5 3 Both a problem and a

resource 21 ,0 25,9

Total 81 ,2 100,0 Missing 4 Cannot say 123 ,3 System 44717 99,5 Total 44840 99,8 Total 44921 100,0 V29_GEOGRAPHY_IMMIGRATION REFERENCE TO ORIGINATION OF IMMIGRANTS Frequency Percent Valid Percent Valid 0 No 99 ,2 48,5 1 Yes, Western Europe, North

America, Oceania 3 ,0 1,5

2 Yes, Eastern Europe (including Russia)

25 ,1 12,3

3 Yes, South America, Asia or Africa

77 ,2 37,7

Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0 V30A_RELIGION_EXPLICIT_IMMIGRATION EXPLICIT REFERENCE TO RELIGIOUS BACKGROUND OF IMMIGRANTS Frequency Percent Valid Percent Valid 0 No 186 ,4 91,2 1 Yes, Christians 2 ,0 1,0 2 Yes, Muslims 16 ,0 7,8 Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0

74

V30B_RELIGION_IMPLICIT_IMMIGRATION IMPLICIT REFERENCE TO RELIGIOUS BACKGROUND OF IMMIGRANTS Frequency Percent Valid Percent Valid 0 No 155 ,3 76,0 1 Yes, Christians 7 ,0 3,4 2 Yes, Muslims 36 ,1 17,6 3 Yes, other religion 6 ,0 2,9 Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0 V31_SKIN_IMMIGRATION PICTURES REFLECTING IMMIGRANT SKIN COMPLEXION Frequency Percent Valid Percent Valid 0 No 135 ,3 66,2 1 Yes, mainly immigrants with

dark skin complexion (non-white) 43 ,1 21,1

2 Yes, immigrants with dark and white skin complexion equally represented in pictures

5 ,0 2,5

3 Yes, mainly immigrants with white skin complexion

21 ,0 10,3

Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0 V32_SOURCES_IMMIGRATION IMMIGRANTS QUOTED OR CITED Frequency Percent Valid Percent Valid 0 No 158 ,4 80,2 1 Yes 39 ,1 19,8 Total 197 ,4 100,0 Missing 2 Cannot tell 2 ,0 System 44722 99,6 Total 44724 99,6 Total 44921 100,0 V33A_PARTY_EXTREME_IMMIGRATION PARTY POSITION DESCRIBED AS EXTREME TOWARDS IMMIGRATION Frequency Percent Valid Percent Valid 0 No 196 ,4 96,1 1 Yes 8 ,0 3,9 Total 204 ,5 100,0 Missing System 44717 99,5 Total 44921 100,0

75

V33B_IDENTITY_EXTREME_PARTY_IMMIGRATION IDENTITY OF EXTREME PARTY Frequency Percent Valid Percent Valid 2 Center left party (Labor, Social

democrats etc.) 1 ,0 12,5

4 Center Right Party (Conservatives, Republican etc.)

2 ,0 25,0

5 Rigth wing party (Progressive party, Vlaams belang etc.)

5 ,0 62,5

Total 8 ,0 100,0 Missing System 44913 100,0 Total 44921 100,0 V34A_PARTY_DISAGREEMENT_IMMIGRATION PARTY DESCRIBED AS DISAGREEING/DIVIDED OVER IMMIGRATION Frequency Percent Valid Percent Valid 0 No 187 ,4 98,4 1 Yes 3 ,0 1,6 Total 190 ,4 100,0 Missing System 44731 99,6 Total 44921 100,0 V34b_IDENTITY_DIVIDED_PARTY_IMMIGRATION IDENTITY OF DISAGREEING/DIVIDED PARTY Frequency Percent Valid Percent Valid 2 Center left party (Labor, Social

democrats etc.) 2 ,0 66,7


1 ,0 33,3

Total 3 ,0 100,0 Missing System 44918 100,0 Total 44921 100,0 V35_MAINARGUMENT_REGULATION MAIN ARGUMENT TOWARDS GOVERNMENT REGULATION Frequency Percent Valid Percent Valid 1 General anti government

regulation/ pro free market 124 ,3 1,7

2 General pro government regulation / anti free market

771 1,7 10,5

3 Neutral towards government regulation / free market

6452 14,4 87,8

Total 7347 16,4 100,0 Missing System 37574 83,6 Total 44921 100,0

76

V36_ECON_GROWTH_REGULATION REFERENCE TO ECONOMIC GROWTH Frequency Percent Valid Percent Valid 0 No 6275 14,0 85,4 1 Yes, government regulation

will reduce growth/free market will increase growth

36 ,1 ,5

2 Yes, government regulation will increase growth/free market will reduce growth

340 ,8 4,6

3 Yes, but not related to government regulation/free market (totally neutral)

697 1,6 9,5

Total 7348 16,4 100,0 Missing System 37573 83,6 Total 44921 100,0 V37_ECON_STABILITY_REGULATION REFERENCE TO ECONOMIC STABILITY Frequency Percent Valid Percent Valid 0 No 6549 14,6 89,1 1 Yes, government regulation

will reduce stability/free market will increase stability

25 ,1 ,3

2 Yes, government regulation will increase stability/free market will reduce stability

424 ,9 5,8


349 ,8 4,8

Total 7347 16,4 100,0 Missing System 37574 83,6 Total 44921 100,0 V38_INDIV_FREEDOM_REGULATION REFERENCE TO INDIVIDUAL FREEDOM Frequency Percent Valid Percent Valid 0 No 7275 16,2 99,0 1 Yes, government regulation will

reduce individual freedom/ free market increase freedom

25 ,1 ,3

2 Yes, government regulation will increase individual freedom/ free market reduce freedom

19 ,0 ,3


28 ,1 ,4


77

V39_INDIV_RIGHTS_REGULATION REFERENCE TO INDIVIDUAL RIGHTS/OPPORTUNITIES Frequency Percent Valid Percent Valid 0 No 7146 15,9 97,3 1 Yes, government regulation will

reduce individual rights / free market will increase rights

21 ,0 ,3

2 Yes, government regulation will increase individual rights / free market will reduce rights

51 ,1 ,7


130 ,3 1,8

Total 7348 16,4 100,0 Missing System 37573 83,6 Total 44921 100,0 V40_INEQUALITY_REGULATION REFERENCE TO INEQUALITY/WELFARE Frequency Percent Valid Percent Valid 0 No 7129 15,9 97,1 1 Yes, government regulation will

increase inequality / free market +

33 ,1 ,4

2 Yes, government regulation will reduce inequality / free market -

77 ,2 1,0


103 ,2 1,4

Total 7342 16,3 100,0 Missing System 37579 83,7 Total 44921 100,0 V41_UNEMPLOY_REGULATION REFERENCE TO UNEMPLOYMENT Frequency Percent Valid Percent Valid 0 No 6401 14,2 87,1 1 Yes, government regulation

will reduce unemployment/free market -

256 ,6 3,5

2 Yes, government regulationw ill increase unemployment/free market +

51 ,1 ,7

3 Yes, but not related to government regulation or free market (totally neutral)

641 1,4 8,7


78

V42_TAXES_REGULATION REFERENCE TO TAXES Frequency Percent Valid Percent Valid 0 No 7047 15,7 95,9 1 Yes, government regulation

will not increase taxes/free market -

76 ,2 1,0

2 Yes, government regulation will increase taxes / free market +

97 ,2 1,3


131 ,3 1,8

Total 7351 16,4 100,0 Missing System 37570 83,6 Total 44921 100,0 V43A_PARTY_CLEARNESS_REGULATION PARTY POSITION DESCRIBED AS (UN)CLEAR TOWARDS REGULATION Frequency Percent Valid Percent Valid 0 No 7196 16,0 98,6 1 Yes, position is clear 85 ,2 1,2 2 Yes, position in unclear 17 ,0 ,2 Total 7298 16,2 100,0 Missing System 37623 83,8 Total 44921 100,0 V43B_IDENTITY_UNCLEAR_PARTY_REGULATION IDENTITY OF (UN)CLEAR PARTY Frequency Percent Valid Percent Valid 1 Left wing party

(Socialists/Greens etc.) 7 ,0 7,1

2 Center left party (Labor, Social democrats etc.)

31 ,1 31,3

3 Center Party (Christian democrats/liberals etc.)

33 ,1 33,3


10 ,0 10,1


3 ,0 3,0

6 Other parties 15 ,0 15,2 Total 99 ,2 100,0 Missing System 44822 99,8 Total 44921 100,0

79

V44A_PARTY_CHANGE_REGULATION REFERENCE TO PARTY CHANGING POSITION TOWARDS REGULATION Frequency Percent Valid Percent Valid 0 No 5287 11,8 99,6 1 Yes, position has not been/is

not changing 4 ,0 ,1

2 Yes, position has been/is changing

16 ,0 ,3

Total 5307 11,8 100,0 Missing System 39614 88,2 Total 44921 100,0 V44B_IDENTITY_CHANGE_PARTY_REGULATION IDENTITY OF CHANGING PARTY Frequency Percent Valid Percent Valid 1 Left wing party



5 ,0 27,8


5 ,0 27,8


3 ,0 16,7


4 ,0 22,2

Total 18 ,0 100,0 Missing System 44903 100,0 Total 44921 100,0 V45_DIRECTION_CHANGE_PARTY DIRECTION OF CHANGE PARTY/ACTOR Frequency Percent Valid Percent Valid 1 Party/candidate are now

more opposoed to government regulation

3 ,0 18,8

2 Party/Candidate are now more supportive of government regulation

13 ,0 81,3


80

V46A_PARTY_EXTREME_REGULATION PARTY POSITION DESCRIBED AS EXTREME TOWARDS REGULATION Frequency Percent Valid Percent Valid 0 No 5262 11,7 100,0 1 Yes 2 ,0 ,0 Total 5264 11,7 100,0 Missing System 39657 88,3 Total 44921 100,0 V46B_IDENTITY_EXTREME_PARTY_REGULATION IDENTITY OF EXTREME PARTY Frequency Percent Valid Percent Valid 3 Center Party (Christian

democrats/liberals etc.) 1 ,0 50,0

6 Other parties 1 ,0 50,0 Total 2 ,0 100,0 Missing System 44919 100,0 Total 44921 100,0 V47A_PARTY_DISAGREEMENT_REGULATION PARTY DESCRIBED AS DISAGREEING/DIVIDED OVER GOVERNMENT REGULATION Frequency Percent Valid Percent Valid 0 No 5160 11,5 99,9 1 Yes 5 ,0 ,1 Total 5165 11,5 100,0 Missing System 39756 88,5 Total 44921 100,0 V47B_IDENTITY_DIVIDED_PARTY_REGULATION IDENTITY OF DISAGREEING/DIVIDED PARTY Frequency Percent Valid Percent Valid 1 Left wing party



2 ,0 33,3


2 ,0 33,3


1 ,0 16,7


81

V48_MAINFOCUS_EDUCATION MAIN FOCUS TOWARDS EDUCATION SYSTEM Frequency Percent Valid Percent Valid 0 No 144 ,3 84,2 1 Yes 19 ,0 11,1 2 Does not apply/INAP 8 ,0 4,7 Total 171 ,4 100,0 Missing System 44750 99,6 Total 44921 100,0 V49_FOUNDATIONAL_EDUCATION DISCUSSION ABOUT FOUNDATIONAL SKILLS Frequency Percent Valid Percent Valid 0 No 100 ,2 97,1 1 Yes, should be more

focus on foundational skills 3 ,0 2,9

Total 103 ,2 100,0 Missing System 44818 99,8 Total 44921 100,0 V50_PUPIL_DIFFERENES_EDUCATION DISCUSSION ABOUT ACADEMIC DIFFERENCES BETWEEN PUPILS Frequency Percent Valid Percent Valid 0 No 99 ,2 96,1 1 Yes, there are too large

differences between pupils 4 ,0 3,9

Total 103 ,2 100,0 Missing System 44818 99,8 Total 44921 100,0 V51_SOCIAL_EDUCATION DISCUSSION ABOUT SOCIAL SKILLS Frequency Percent Valid Percent Valid 0 No 100 ,2 96,2 1 Yes, should be more focus on

social skills 4 ,0 3,8

Total 104 ,2 100,0 Missing System 44817 99,8 Total 44921 100,0 V52_WELFARESYSTEM_EDUCATION DISCUSSION ABOUT WELFARE SYSTEM IN RELATION TO EDUCATION Frequency Percent Valid Percent Valid 0 No 101 ,2 97,1 1 Yes, current education system

illustrates great welfare system 3 ,0 2,9


82

V53_GENDER_EDUCATION DISCUSSION ABOUT GENDER DIFFERENCES IN EDUCATION SYSTEM Frequency Percent Valid Percent Valid 0 No 103 ,2 99,0 1 Yes, education system

favours girls 1 ,0 1,0

Total 104 ,2 100,0 Missing System 44817 99,8 Total 44921 100,0 V54_SOCIALCLASSES_EDUCATION DISCUSSION ABOUT SOCIAL CLASSES IN SCHOOLS Frequency Percent Valid Percent Valid 0 No 99 ,2 95,2 1 Yes, the education system

favours middle- or upper class 5 ,0 4,8

Total 104 ,2 100,0 Missing System 44817 99,8 Total 44921 100,0 V55_ETHNICITY_EDUCATION DISCUSSION ABOUT ETHNICTY AND EDUCATION Frequency Percent Valid Percent Valid 0 No 101 ,2 97,1 1 Yes, Education System favours

ethnic citizens 1 ,0 1,0

3 Yes, ethnic background is irrelevant for success in education system

2 ,0 1,9

Total 104 ,2 100,0 Missing System 44817 99,8 Total 44921 100,0 V56_INFRASTRUCTURE_EDUCATION DISCUSSION ABOUT EDUCATION INFRASTRUCTURE Frequency Percent Valid Percent Valid 0 No 89 ,2 85,6 1 Yes, there are problems or a

conflict related to infrastructure 5 ,0 4,8

2 Yes, positive aspects related to infrastructure debated

4 ,0 3,8

3 Yes, infrastructure is debated in balanced or neutral way

6 ,0 5,8


83

V57_ACTOR_CRITICIZE_EDUCATION ACTOR OR SOURCE CRITICISING CURRENT EDUCATIONAL POLICIES Frequency Percent Valid Percent Valid 0 No, criticism 85 ,2 82,5 1 Yes, politicial from a party in

government 2 ,0 1,9

2 Yes, politician from a party in opposition

2 ,0 1,9

3 Yes, academics, other experts 3 ,0 2,9 4 Yes, from organization (e.g.

teacher unions) 4 ,0 3,9

5 Yes, public official 3 ,0 2,9 6 Yes, other actors 4 ,0 3,9 Total 103 ,2 100,0 Missing System 44818 99,8 Total 44921 100,0 V58_BLAME_EDUCATION WHO IS BLAMED BY MAIN CRITICISER Frequency Percent Valid Percent Valid 1 Current government 6 ,0 31,6 3 The profession 2 ,0 10,5 5 Public official 2 ,0 10,5 6 Other 3 ,0 15,8 7 None 6 ,0 31,6 Total 19 ,0 100,0 Missing System 44902 100,0 Total 44921 100,0 V59_NATIONAL_MEASUREMENT_EDUCATION1 RESULTS OF NATIONAL MEASUREMENTS USED AS ARGUMENT FOR CRITICISM Frequency Percent Valid Percent Valid 0 No 52 ,1 98,1 1 Yes 1 ,0 1,9 Total 53 ,1 100,0 Missing System 44868 99,9 Total 44921 100,0 V60_INTERNATIONAL_MEASUREMENT_EDUCATION1 RESULTS OF INTERNATIONAL MEASUREMENT (PISA/TIMMS) AS ARGUMENT FOR CRITICISM Frequency Percent Valid Percent Valid 0 No 81 ,2 98,8 1 Yes 1 ,0 1,2 Total 82 ,2 100,0 Missing 2 Can't tell 1 ,0 System 44838 99,8 Total 44839 99,8 Total 44921 100,0

84

V61_COUNTRY_EDUCATION1 REFERENCE TO OTHER COUNTRIES BY CRITICISER Frequency Percent Valid Percent Valid 0 No 81 ,2 97,6 183 United Kingdom 1 ,0 1,2 203 North America 1 ,0 1,2 Total 83 ,2 100,0 Missing System 44838 99,8 Total 44921 100,0 V62_ACTOR_DEFENDING_EDUCATION ACTOR OR SOURCE DEFENDING CURRENT EDUCATIONAL POLITICIES Frequency Percent Valid Percent Valid 0 No, criticism 94 ,2 93,1 1 Yes, politicial from a party in

government 2 ,0 2,0

4 Yes, from organization (e.g. teacher unions)

2 ,0 2,0

5 Yes, public official 2 ,0 2,0 6 Yes, other actors 1 ,0 1,0 Total 101 ,2 100,0 Missing System 44820 99,8 Total 44921 100,0 V63_CREDIT_EDUCATION WHO GETS THE CREDIT FROM MAIN DEFENDER Frequency Percent Valid Percent Valid 1 Current government 2 ,0 25,0 6 Other 1 ,0 12,5 7 None 5 ,0 62,5 Total 8 ,0 100,0 Missing System 44913 100,0 Total 44921 100,0 V64_NATIONAL_MEASUREMENT_EDUCATION2 RESULTS OF NATIONAL MEASUREMENTS USED AS ARGUMENT FOR DEFENCE Frequency Percent Valid Percent Valid 0 No 40 ,1 97,6 1 Yes 1 ,0 2,4 Total 41 ,1 100,0 Missing System 44880 99,9 Total 44921 100,0 V65_INTERNATIONAL_MEASUREMENT_EDUCATION2 RESULTS OF INTERNATIONAL MEASUREMENTS USED AS ARGUMENT FOR DEFENCE Frequency Percent Valid Percent Valid 0 No 41 ,1 100,0 Missing System 44880 99,9 Total 44921 100,0

85

V66_COUNTRY_EDUCATION2 REFERENCE TO OTHER COUNTRIES BY DEFENDER Frequency Percent Valid Percent Valid 0 No 41 ,1 100,0 Missing System 44880 99,9 Total 44921 100,0

86

ISBN 978-82-90217-48-3

ISS REPORT NO. 75 MEDIA SYSTEMS AND THE CHARACTER OF NEWS A CROSS-NATIONAL CONTENT ANALYSIS Project...

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Transcript of ISS REPORT NO. 75 MEDIA SYSTEMS AND THE CHARACTER OF NEWS A CROSS-NATIONAL CONTENT ANALYSIS Project...