REPORT Conspiracy Theories in the Norwegian Media TABLE OF CONTENTS TABLE OF CONTENTS 1 1. Introduction 2 2. Conspiracy: definition and context 2 3. Methodology, sampling and coding 3 4. Analysis and discussion –coverage of conspiracy theories in the media 5 4.1 Eurabia theories 6 4.2 Anti-Zionism 8 4.3 Other conspiracy theories 8 5. Comparison with the previous pre-election period 9 6. Conclusion 11 Literature 12 1 1. Introduction This report discusses the results of a piece of research on conspiracy theories in the traditional Norwegian media, as part of Counterpoint’s ‘Rival Political Narratives’ project. Since the traditional media in Norway consists of several TV stations, many nation-wide newspapers, and hundreds of local newspapers, the project requires some kind of demarcation, both in terms of time frame and scope. The time frame chosen is from 1st January 2013 to 6th September 2013. This time frame covers a period of political campaigning for the 2013 parliamentary election, held on the 8th and 9th of September. This provides a time period where political debate on various issues in the media was prominent and pressing. The scope is confined to newspapers, with the exception of one particularly relevant television interview. My choice of scope will be further elaborated in the methodology section of this report. This project was slightly expanded as a result of the findings in the 2013 data; a smaller comparative section dealing with similar data from the last parliamentary election in 2009 has also been included. As this period contains much more data using the same data-gathering methodology, the analysis here takes a different method to reveal general tendencies. This will help to illuminate the data from 2013 and will moreover add a longitudinal analysis of the most notable conspiracy theories in the Norwegian media. This report begins with a short section on definition and context, where I clarify my definition of ‘conspiracy theories’ and give some background information on the Norwegian context. The next section deals with methodology, including the process of data-gathering, coding, scope and other methodological issues. The final section presents the data and the analysis. All data gathered is coded and categorised in Annex A, an accompanying spread sheet. 2. Conspiracy: definition and context What characterises a conspiracy theory? Following Sunstein and Vermeule (2009), I will take on a pragmatic albeit functional definition of a conspiracy theory. Sunstein and Vermeule define a conspiracy theory as ‘an effort to explain some event or practice by reference to the machinations of powerful people, who attempt to conceal their role (at least until their aims are accomplished)’ (ibid: 205). A more colloquial definition of ‘conspiracy’ also includes conspiracies between equals (friends, fellow employees etc.), or even individuals who are not powerful at all (ibid). For the purpose of this project, however, I will draw upon the definition in the former quotation. Within the limits of this definition fall both true and false conspiracy theories, but in this analysis and report I will not occupy myself with either confirming or falsifying conspiracy theories. Since this project is oriented towards Norway in particular, a short contextual overview on the status of conspiracy theories in this country might prove useful. As Norway is one of the countries in the world with the highest levels of social trust (Newton 2001, Delhey and Newton 2005), one might assume that conspiracy theories are relatively rare or even absent. However, a recently published book by John Færseth on this topic demonstrates that Norway has a long tradition of conspiracy theories, which runs right through to the present day (Færseth 2013). According to Færseth, the tradition of conspiracy theories is present on both the political left and right. There are also noted conspiracy theories that are politically neutral, like chemtrails, vaccines and UFOs. For the latter category, I have not found any relevant data in the period of time in question. 2 Færseth argues that the political left has an ‘accepted type’ of conspiracy theory, often involving the USA and/or Israel. Right-wing politicians tend to lean towards Eurabia theories, as well as conspiracy theories about global warming (ibid). The author also makes the reader aware of a long range of conspiracy theories related to the Labour Party, perhaps because they have had such a central role in building, restoring and controlling post-war, modern and contemporary Norway (ibid). A great majority of his sources are from within the blogosphere, and a brief scan of his notes and literature list reveals that he makes very few references to the traditional media. However, I will show in this report that conspiracy theories are also dealt with, discussed, and both promoted and debunked in the traditional Norwegian media. Færseth’s book is useful in providing a general overview for where to start looking for conspiracy theories in the Norwegian media. 3. Methodology, sampling and coding Throughout this analysis, I have used an electronic database named ATEKST to review and detect the most prevalent and visible coverage of conspiracy theories, both implicit and explicit, in the traditional Norwegian media. This database holds all printed articles of all newspapers in Scandinavia. For both methodological and analytical reasons, it is important to distinguish between different types of text in the media. For instance, in the Scandinavian media there exists a type of article called ‘kronikk’ (‘chronicle’). The chronicle is a rather Scandinavian phenomenon, which falls somewhere in between an editorial and a feature story. Normally, the chronicle is written by a scholar, expert, politician or representative of a given organisation or group of interest, on a given topic. Sometimes the chronicles are more or less academically oriented, while at other times they are more openly subjective. Since those who write these articles do not work within the media, they are different to a normal news story or feature story. But all chronicles are approved by the editorial board of each media outlet, and normally each newspaper either chooses chronicles that discuss current events, or that are written particularly well, or that are written by well-known personalities. Clearly, the political alignment of the media outlet may also affect their choice. There are also simpler versions of the chronicle, such as the ‘leserinnlegg’ and the ‘replikk’. The former can be translated roughly as ‘reader’s contribution to the newspaper’, while the latter is a reply to a former published chronicle or general article. In my process of coding, both of these simplified versions will simply be categorised as ‘chronicles’. Sampling and gathering data from a database holding hundreds of thousands of articles needs a systematic approach. Articles containing exact words denoting a given conspiracy theory are easily searchable, but do not necessarily provide an accurate account of the current status of conspiracy theories in the Norwegian media. For instance, promoters and supporters of conspiracy theories will not primarily see their arguments as concerned with conspiracy. Therefore their choice of words and concepts may well differ dramatically from debunkers and critical authors. In this analysis, for example, the word ‘Eurabia’ was rarely used among authors actually arguing in favour of Eurabia theories. But the debunkers often evoked the concept. In general, authors who believed in conspiracy theories rarely used the word ‘conspiracy’ in their text. To ensure data from both sides of this divide, a proper methodology is crucial. Miles and Huberman (1994) suggests a three-fold technique to be used simultaneously to avoid arbitrary or random data. These are: 1. Selecting apparently typical/representative examples, 2. Selecting negative/disconfirming examples; and 3. Selecting exceptional or discrepant examples (ibid: 34). 3 In my sampling the typical and representative data (1) are the articles that are entirely explicit, using words such as ‘conspiracy’, ‘Eurabia’ and ‘Zionist conspiracy’. These articles often address someone in particular (either a group of individuals or a named individual) and are mostly sceptical towards conspiracy theories in their tone and style of argument. By examining the group and carrying out searches for the named individuals, I have found both negative/disconfirming examples (2), as well as exceptional and discrepant examples (3). Negative/disconfirming (2) examples are more specifically those articles that are non-typical. These may promote conspiracy theories in some way, or they may promote or debunk conspiracy theories other than Eurabia (i.e. media conspiracies, global warming conspiracies). Exceptional or discrepant examples fit into neither of these categories. These can be, for instance, articles making witty, ironical or sarcastic jokes about conspiracy theories (but not necessarily picking sides), or those articles that carry out an academic analysis on the subject. Moreover, by analysing articles within the second and third categories, I was able to identify new words and concepts, which in turn provided a way to add to the type-2 and type-3 data in the analysis. This methodological approach has been used for the most apparent and frequent conspiracy theories, while other less frequent ones have been confined and limited only to typical examples, due to the lack of data available in the chosen period of time (or even over any time period). Searching for data using these techniques still generates a large number of articles, where relevance varies significantly. Some articles found within the database mention relevant keywords, groups or names in a context that renders them irrelevant in this analysis – these articles have not been included nor coded. These include articles where Eurabia is mentioned as an aside, and where the actual content of the article is something entirely unrelated. In this analysis I have also excluded articles from very small and small newspapers – especially local newspapers, which Norway has very many of because of lucrative state subsidies.