Bias in television interviews towards politicians
Master thesis Communication Science
Student: Faranak Babai (10437983)
Supervised by: Marjolein Moorman
Graduate School of Communication
University of Amsterdam
June 2015
Abstract
Television can be biased in many different ways; in this research two ways of possible bias
are measured. The first is the bias in the representation of politicians on television. The
second is the bias of the journalists in their approach towards politicians in interviews, on
television. This study investigates the first type for the following characteristics: age, gender,
experience, and political party and the second type for the following characteristics: Left/right
winged party, coalition/oppositional party and gender. Bias is measured using six elements
being: initiative, directness, assertiveness, accountability, opposition and persistence of the
journalist, a research tool that is developed by Claymen, Elliott, Heritage and Mcdonald
(2007) and improved by Huls and Varwijk (2011). Bias is measured in the political oriented
program Pauw, a late night show about topicality with, among other guests, politicians,
journalists and lawyers. The result of the study show that indeed bias is found. The first bias
measured that males were more represented than females and among political parties, the
PvdA was more represented than all the other parties. The second bias measures, left winged
politicians, oppositional party politicians and males were approached more biased than right
winged politicians, coalition party politicians and females. In the discussion these results were
put in context with other bias studies and implications for future research are discussed.
Introduction
The political arena is inseparably bound to television. It is even unimaginable without
television. The figures of the Standard Eurobarometer (2013) show that when Europeans were
asked: ”Where do you get most of your news about national political matters from?” The
majority (82%) answered: the television. This makes it important for politicians to be able to
represent their parties on television and this gives television the power and responsibility to
represent the political arena. However, former studies have shown that the media can be
biased (Huls & Varwijk, 2011: Vos, 2014).
Definition of bias
McQuail (2010) defines bias as “any tendency in a news report to deviate from an accurate,
neutral, balanced and impartial representation of ‘reality’ of events and social world.” Bias
can manifest itself on many different levels on television (D’Alessio & Allen, 2000). Two of
these are relevant in this study, knowing: bias in representation and bias in journalists
approach towards politicians. According to D’Alessio and Allen (2000), the representation
can be found in the choices of who gets invited or interviewed, the physical amount of
attention that the politicians get. The amount of attention the politicians get should be equal or
in proportion with the political division at that time for television not to be biased. The
representation bias is also called coverage bias or bias in attention. In this research it will be
called coverage bias. The second type of bias according to D’Alessio and Allen (2000) is how
much the journalists insert their own views and opinions in their questions and reporting. This
does not mean that journalists cannot be critical but they do have to be neutral, meaning that
the journalists should be equally critical towards all the politicians. When a journalist is more
critical towards one politician than the other this can be seen as bias. This is called statement
bias or bias in the demand draft. In this research it will be called statement bias.
Relevance of researching bias
The role of television is important because apart from entertaining,
television has a public
function
and a duty towards society.
Its role is to be a watchdog in a participatory democracy
making programs that informs citizens about politics representing parties and politicians. By
doing so, the public can make informed political choices (Clayman, 1992). If bias would
indeed exist it would mean that television is not informing the public in a neutral and
objective manner. Consequently, the public is possibly steered towards certain choices, which
interrupts the democratic system (DellaVigna & Kaplan, 2006). Studies have shown that
television could influence public opinion by being more positive towards parties that get more
positive attention (Gerber, Karlan, & Bergan, 2007). Influencing the public in their attitudes,
leads to more power for parties getting approached more positively on the television and less
power to politicians and parties that get negative or no attention (Entman, 2007). It could go
even further by influencing voting behaviour when media showed to be biased (Bernhardt,
Krasa, & Polborn, 2008; DellaVigna & Kaplan, 2006). So if bias would exist, this would
mean it could interrupt the democratic system by influencing voters’ opinions and behaviour.
This study wants to contribute to a healthy democratic system, by adding knowledge about a
possible existing bias, the public can be made aware and the media or government can be
stimulated to make code of conducts or regulations to prevent the bias. Especially because, in
general and also in the Netherlands, there is not a lot of research done on this subject (Wind,
2007). This study tries to contribute to the academic field by extending the knowledge on this
subject. For example, by studying statement bias toward oppositional/coalition party
politicians and gender in television interviews which has not been studied before and by
testing a tool on validity, reliability and feasibility that has been made by Clayman et, al.
(2007) to measure bias in television interviews and extended by Huls and Varwijk (2011).
Theoretical framework
As mentioned in the introduction, this study will firstly look at coverage bias and secondly at
the statement bias on television. However, television is a broad understanding and not all
programs are suitable for this study.
A research of Veldkamp (2010) shows that the news is
appointed as the most important program for politics and politicians in which they get
attention from the public but also news shows about politics and topicality is mentioned in
this list as important for politicians to be able to send out a message to the public.
Kleinnijenhuis, Hoof, Oegema and De Ridder (2007) report news shows about politics and
topicality programs as influential for voting behaviour in the Netherlands. Because of the
impact of news shows and the opportunity that they have, as there is a journalist interviewing
politicians, news shows will be used in this research to measure Coverage and statement bias.
Coverage Bias
Starting with coverage bias, representation of politicians in the past has been measured by
looking at certain characteristics of politicians and how often those characteristics are
represented. Based on former studies (e.g. Vos, 2014) the following characteristics are taken
into consideration in this study: Experience, party size, gender and age of the politician. They
are discussed in the following paragraphs that have led to the research question:
RQ1: What are the characteristics of individual politicians on news show interviews?
Most of the researches that are done base the division of the characteristics on news values
and news routines (Vos, 2011). The news value is how much a journalists thinks the news is
relevant and important enough to be shared and discussed. The news routine is the everyday
procedural shortcuts that a journalist takes to make its decisions (Van Dalen, 2012). There are
also studies that do not agree with this, arguing that this assumes a journalist of being passive
and reacting automatically to events, which journalists do not. They have working
mechanisms, personal preferences and ideology, which their decisions are also based on
(Tresch, 2009).
Experience of the politician
The experience of the politicians has been one of the most studied characteristics in the past
(Vos, 2014). Khan (1991) studied newspapers and showed that the more experienced a
politician is, the more media attention this person will get. One year later Kuklinski and
Sigelman (1992) studied the same characteristic, but this time for television and found the
same results. A more recent study of Gershon (2012) found the same effect. However there
were also studies that found no effect of experience on media attention (Fogarty, 2008; Tresh,
2009). Looking further into it, it became clear that the studies that do find an effect were all
conducted in election time. So it seems that in a regular period of time, experience does not
play a role but it does play a role in election time. The explanation for this could be the
electoral positions. Experienced politicians are expected to have a higher position on the
electoral list because they are recognizable by the electorate which can get them more media
attention (Vos, 2014).
Size of the party
Another characteristic that will be looked at is the party the politician belongs to and if that
matters in the representation on television. Previous studies on this characteristic were not
consistent. Van Aelst, Maddens, Noppe and Fiers (2008) found that a bigger vote share in
previous elections gets the politicians more media attention. One year later the same result
was also found by Tresh (2009), but other studies like Arnold (2004) and Midtbø (2011)
found the exact opposite. The largest parties were not necessarily the ones getting the most
media attention, on the contrary, there were even researches that found the opposite (Shaffner
& Sellers, 2003). Overall, the effect that was found was contradicting. The reason that this
effect is contradicting might be because other factors like incumbency have a larger effect.
When a party is large and incumbent it does get more attention, but when it is a large
oppositional party the opposite results were found (Vos, 2014).
Gender of the politician
Concerning the characteristic gender, also mixed results were found, this seems to be
explainable. The studies that found a difference in gender were the studies of Midtbø (2011),
Van Aelst et al. (2008) and Veblen (1981). All three of the studies concluded that men were
significantly more represented than women. Another factor that these three studies had in
common was that they also measured the function of the politicians, but they did not specify
the professions, using dummy variables. For example Van Aelst et al. (2008) only coded a
dummy variable of one high office function so when the politicians had other functions they
were not taken into consideration. Other studies that had a more extensive measurement of the
function of the politician did not find differences between male and female politicians (Tresh,
2009; Gershon 2012) because they took more levels of political functions into consideration.
This means that there could be a connection between gender and profession and when the
function of the politician is taken into consideration no difference was found (Vos, 2014).
Hayes and Lawless (2013) concluded that gender is a characteristics that can influence media
attention but in time it started to have less and less influence in comparison to other
characteristics.
Age of the politician
As a last characteristic the age of the politician will be taken into account. The age of
politicians were not much researched. Midtbø (2011) and Veblen (1981) found that younger
politicians get more attention than older politicians. Cook (1986), Squire (1988) and Tsfati,
Elfassi and Waismel-Manor (2010) did not find an effect. The studies that had significant
results researched newspapers, the ones that did not find a significant result in the difference
of age researched television (Vos, 2014). There is no explanation for why there is a difference
between television and newspapers.
Statement bias
The statement part consists of the bias that the journalists have in their approach towards to
the politicians.
Interviewers have often been seen as being biased. Meaning that they do not
always bring the facts but approach them from a certain angle or leave them out, in line with
their own beliefs (Van den Besselaar, 2010). There are even journalists that do not believe in
the neutrality of a journalist, like Joris Luyendijk (2008). In his study he mentions that in
conflicts neutral terms do not exist, that a journalist needs to choose an angle to approach its
subject from. However, it is not only journalists, as also politicians are prepared for
interviews and have learned tactics to gain more control in an interview. This way it makes it
harder for journalists to get answers to their questions (Clayman & Heritage ,2002). On their
turn, journalists react to that by getting more aggressive in the way they ask their questions
(Carlier, 2007). According to these studies a bias of journalists is almost inevitable.
Unfortunately there are not many studies about the individual bias of a journalist, let alone
studies on which specific characteristics of politicians are biased on. In a lot of studies about
bias, the more impersonal influences like deadlines, space, culture and organizational policies
have been seen as main reasons for bias and therefore studied more (Stocking & Gross, 1989;
Wind, 2007). This does not mean that the influence of the journalist is less important. On the
contrary, especially when it comes to interviews where journalists have a prominent role, the
statement bias could be influential (Stocking & Gross, 1989). This part of the research chose
the characteristics left/right winged, opposition/coalition and gender to be taken into
consideration for which the following research questions are formulated.
RQ2:
Do the interviewers of the news shows have a bias toward left or right winged
politicians
?
RQ3:
Do the interviewers of the news shows have a bias toward politicians in opposition or
coalition parties
?
RQ4:
Do the interviewers of the news shows have a bias toward male or female politicians
?
The elements of bias
According to Huls and Varwijk (2011) and Clayman et al. (2007) the bias of the journalist
consists of the initiative, directness, assertiveness, opposition, responsibility and persistence
of the interviewer. The first three elements are based on the overall form a question has and
the last two elements are based on content of the question.
The element initiative is about how active or passive the journalist is towards the politician.
By having an introduction in the question and asking multiple questions at once, the journalist
limits the answering space of an interviewee.
The second element is directness. This element shows how polite and careful the interviewer
is towards the interviewee. When the interviewer explains why he or she asks the question or
by asking politely if the interviewee wants to answer, there is space given to the interviewee
to be able to refuse answering the question and to judge if the question is based on reasonable
arguments.
Assertiveness is how suggestive the question of the journalist is. When the question that the
interviewer is asking is more an answer to which the interviewee can agree or disagree with,
this is seen as suggestive because it gives very little space to the interviewee to actually
answer the question.
The fourth element is opposition, which shows if the position of the interviewer is the
opposite of the interviewee. In this case the interviewer knows the standpoint of the
interviewee and chooses to take a contraposition instead of a neutral one. The interviewer at
this point is openly critical towards the interviewee.
The fifth element is responsibility. The interviewer asks an explanation or accountability for
the actions or sayings a politician has done. It could go even further than that by not just
asking in a neutral way for an explanation but even doubt or accuse the politician.
Besides these five elements Huls and Varwijk (2011) added a sixth element, namely
persistence. The sixth element is meant for the interaction between the journalist and the
interviewee. When an interviewee avoids answering a question or does not answer it to the
satisfaction of the interviewer, the interviewer can choose to ask the question once more,
interrupt the interviewee or even appoint to the avoiding behaviour and in that way
demanding an answer.
Bias towards left or right winged politicians
Bias towards left/right winged politicians were the most researched characteristic of statement
bias. Political preference is a characteristic that is part of the personal preferences, which is
seen as one of the main sources of journalist’s bias (Reese, 2001). Journalism is no exact
science, the decisions journalists make are not based on a codified body of knowledge that
guides them (Patterson, 1996). Thus in their analyses there is space for errors of judgement
and selectivity of perception. And although it does not happen conscious, their
left/right-winged preferences do play a role in their news decisions even when they think they are being
neutral (Patterson & Donsbagh, 1996). As Huls and Varwijk (2011) also showed in their
study, journalists had a bias in their presentation towards right winged politicians. The study
even took the answers of the politicians partially in consideration and had control variables
like gender, all to make sure that those won’t be the reason for the bias that is found, which
indeed was not the case. This makes it more likely that it is the personal preference of the
journalist as the reason for the bias. Although this was in election time and almost ten years
ago, a bias of the interviewer is still expected to be found between the approach of left versus
right winged politicians, as the interviewer and the concept of the program have not been
changed and the literature shows a bias is always present.
Bias towards opposition or coalition politicians
There is no study found on the bias of the presentation of journalists towards politicians and
the characteristic opposition/coalition. However, former theory does set ground to do so.
Except for bias from personal preferences of a journalist, which is called partisan bias (like
mentioned with left/right wing), a journalist can also have structural bias. “A
structural bias is
the result of a preference of the media for some type of story or frame that leads them to pay
more attention to some politicians than to others” (Gulati, Just & Crigler, 2004)
. This bias is
not originated from ideology but from the routines of the journalist, routines of choosing a
frame or stories based on their news value. Opposition and coalition politicians have different
functions from where coalition parties think of plans and opposition parties have to debate
about these plans. There are, concerning political issues, mostly two or more sides to choose
from (oppositional/coalitional) and out of structural bias, journalists tend to choose a certain
angle to approach the politicians from (Van Dalen, 2012).
Bias towards the gender of the politicians
One of the controlling variables in the research of Huls and Varwijk (2011) was gender, and it
was the only one that showed significant results. This was not the case for all the politicians,
but looking at the element ‘persistence’ it was found that left winged female politicians were
approached with more persistence than left winged male politicians. Although this result is
minimal, it still shows a difference and it is a steppingstone to take into consideration in this
study. Little research was found about the presentation bias of the journalists towards gender.
Only Devitt (2002) researched the bias of the journalist towards the difference in gender.
Devitt (2002) discusses that journalist have a bias towards females and that they are
approached in as less professional than male politicians. He concludes that females are framed
in a maternal way. Instead being asked and judged on the content of their work they are asked
and judged on their appearance and domestic situation. Although this is different than the bias
in this study, it does show that based on gender politicians are approached differently.
Method
The research method for this thesis will be a content analysis. A content analyses fits to
answer the research questions the most because the interviews with the politicians can be
judged systematically. Media attention and bias can be measured most objective with a
content analysis, especially with an instrument like Huls and Varwijk (2011) designed.
Huls
and Varwijk (2011) used the program of Pauw and Witteman. This program does not exist
anymore but Jeroen Pauw, one of the presenters, continued with a follow up program named
Pauw. It is the same concept, namely a news show from Monday to Friday with a duration of
approximately one hour. It starts at 23:00 and discusses socially relevant topics with a variety
of guests who are involved in the topics discussed. The program attracts between 700 000 and
750 000 viewers per day (SKO, 2015) and is broadcasted on the public channel. Pauw has a
market share of approximately 18% (
SKO, 2015
). As mentioned before, Pauw is the follow
up for the program of Pauw and Witteman, which is seen as the backbone of the essentials of
public broadcasting (Huls & Varwijk, 2011) and one of the most influential programs
concerning politics (Ruigrok et al., 2012).
The first episode of Pauw was on the first of September. All episodes from the first of
September until the 17
thof December will be taken into consideration. In Appendix one the
list of guest on the show is submitted. In the months January and February the show is
replaced with another news show and the months after February will not be used because
there are provincial elections in the Netherlands on the 18
thof March 2015. This could
influence the programming, as the focus will be more on the elections, and this study focuses
on regular programming. Furthermore the previous studies in the Netherlands all focused on
election time, so it would be interesting to research a regular period of time. Furthermore, a
period of four months gives enough opportunity for this research.
As mentioned before, the research consists of two parts. The first part will be used for
descriptive analyses whereby all episodes are taken into consideration. From the
above-mentioned characteristics a question list was set up to analyze the episodes. First a distinction
is made between politicians and non-politicians, with the question: Is the interviewee a
politician? The definition of a politician will be a person that is a holder of an elected office
and is part of an official Dutch political party, this can be national or regional. This is coded
first because if the interviewee is coded as a politician the next elements have to be coded as
well:
age, gender, party of the politician and how many politicians there were in one show at
the same time.
For the statement bias a comparative analysis is used. For this part 12 episodes will be
selected where politicians are interviewed (The transcripts are submitted in appendix two)
and, different than the first part, not all parties will be taken into consideration but just four of
the biggest political parties, being VVD, PvdA, CDA and SP. The choice for the parties is not
only based on the size of the party but also their place in the political spectrum (see Figure 1).
The current political spectrum was set after the national elections in September 2012 and is
based on the positions that Kieskompas (2012) appointed to the parties. The spectrum has two
dimensions being left/ right and conservative/progressive, which divides it into four
platforms. Two of the platforms just consist of one party and will therefore not be taken into
consideration, as it would be unclear if the bias would be party specific or political favour
specific.
From each party three politicians will be selected. The selection will be based on the
importance of the person; so party leaders were chosen first in the coding process. The other
persons were chosen based on equalizing the characteristics that will be coded. For example,
when three SP politicians are interviewed, two males and one female of which one male the
party leader, the party leader and the female will be chosen.
As mentioned before, the coding of the qualitative part will be done according to the Question
analysis system of Clayman et, al. (2007) also called QAS (2002). It consists of five questions
measuring the bias of the interviewer. It was originally used for press conferences in the
United States of America, which means that it was not developed for an on-going
conversation, but just one or a couple of questions asked at once. Despite this Huls and
Varwijk (2011) showed it to be implementable in television interviews as well, adding one
extra question to make it complete. For the coding of these questions the codebook of Huls
and Varwijk (2011) will be used (the codebook used is included in the appendix three). This
has proven to be valid and reliable as it was used in the researches of Clayman et al. (2007)
and Huls and Varwijk (2011). In the research of Huls and Varwijk (2011) the following
Cohen’s Kappa’s (Cohen, 1960) were found: initiative: .91; directness: 1.00; assertiveness:
.78; opposition: .71; accountability: 1.00; persistence: .56. Persistence is not optimal as it does
not reach the .6, but in this research the definition will be made more specific to be able to get
the Kappa to at least .6.
To be able to test the inter coder reliability three of the same episodes are coded separately by
the two coders, according to the codebook. The three coded episodes are tested with a
Krippendorff’s Apha. The inter-coder reliability should preferably be Kalpha = 0,80 but a
Kalpha = 0,60 will be accepted as well if it can be explained why it is low and why it is still
acceptable. Adjustments to improve the codebook were not needed. The outcomes of the
Table 1: Khalpha outcomes of the inter-coder reliability test
Answering strategy
0,79
Politeness strategy
0,85
Conversation role
1
Initiative
0,89
Directness
1
Assertiveness
0,85
Opposition
0,87
Persistence
1
Because of the positive results the rest of the episodes were coded without any changes to the
codebook.
The first part of the research was done with frequencies and crosstabs. The second part was
tested on significance with the independent T-test as all the variables are nominal but
dichotomous.
Results
In total eighty episodes of Pauw have been taken into consideration. In these eighty episodes
501 guests attended, from which 52 (10%) were politicians. The politicians were between the
age of 29 and 76, with 39 (75%) of them being male and 13 (25%) being female. They had
political experience between 2 and 21 years. Nine parties of the parliament were represented.
With 36 of the politicians being the only politician on the show in 36 different shows, and 16
being invited with another politician on the show in 8 different shows. For the first part of the
research the following results were found and presented in the figures 2, 3, 4 5 and 6.
Figure 2: profession of the guests on the show
Figure 3: Age of the politicians
16% 13% 12% 11% 10% 7% 6% 6% 6% 5% 5% 3%
professions of the guests on the show
Other Journalist Specialist Actor Politician Lawyer Comidian Writer/Poet Singer/Musician Athlete Chairman Director 1,9% 17,3% 38,5% 30,8% 5,8% 5,8% 0 10 20 30 40 50
Age of Politican
20-29 years 30-39 years 40-49 years 50-59 years 60-69 years 70-79 yearsFigure 4: Gender of the politician
Figure 5: Experience of the politcian
Figure 6: Political parties on the show
75% 25% 0 20 40 60 80 Male Female
Gender of the politician
Male Female 30,8% 36,5% 25% 5,8% 1,9% 0 5 10 15 20 25 30 35 40 1-5 years 6-10
years 11-15years 16-20years 21-25years
Experience of the politician
1-5 years 6-10 years 11-15 years 16-20 years 21-25 years 32% 16% 16% 12% 10% 10% 4%
Political parties on the show
PvdA PVV VVD CDA SP ChristenUni 50+
Comparison with the second chamber
As mentioned before, a part of bias lies in how much the representation of the characteristic
differs from reality. In this case that is the second chamber. Comparing Pauw to the second
chamber had the following result. The age of the politician has an average of 48 on the
program of Pauw and an average of 45 in the second chamber according to Tweede kamer,
Der Staten Generaal (2015). The experience of the politician has an average of 9 years in the
program Pauw and an average of 8,3 years in the second chamber according to Tweede
kamer, Der Staten Generaal (2015). This outcome would be the ideal situation for all the
characteristics, but the results show differently. In the second chamber 38% of the politicians
is female and 62% is male. On the program of Pauw 25% of the politicians is female and 75%
is male. Also the characteristic political party was bias where almost one out of three of the
invited politicians are from the PvdA (31%.) The VVD (15%) whom has the most seats in the
second chamber and the ChristenUnie (10%) who is one of the smallest parties in the second
chamber only had a difference of 5% in representation, showing an obvious bias in the
representation of political parties.
Statement bias
For statement bias part of the study an independent T-test was executed for the three
independent variables being Left or Right Winged, Opposition or Coalition and Gender and
the six dependent variables being Initiative, Directness, Assertiveness, Opposition,
Accountability and Persistence. The following results were found.
Left or right winged
There was no significant difference found between left and right winged politicians for the
elements initiative, assertiveness, opposition and persistence.
There was a significant t(113,78)=-2,18, p=0,031,CI[-0,10 ; -0,01] difference found for
directness. An independent T-test showed a difference between left winged politicians
(M=0,06, SD=0,24) and right winged politicians (M=0,01, SD=0,08). A difference is also
found between left winged politicians (M=0,15, SD=0,36) and right winged politicians
(M=0,04, SD=0,19) for the element accountability. The difference is significant
t(135,52)=-2,89, p=0,004,CI[-0,19 ; -0,04]. This means that for directness, as well as accountability the
journalist was more biased towards the left winged politician than the right winged politician.
Opposition or coalition parties
There were no significant differences found between politicians from oppositional/coalition
parties for the elements opposition and persistence. With an independent T-test there was a
difference found between politicians in an oppositional party (M=0,33, SD=0,47) and
politicians in a coalition party (M=0,18, SD=0,39) for the element initiative. The difference is
significant t(124,11)=2,48, p=0,015, CI[0,29 ; 0,26].
There was also a difference found between politicians in an oppositional party (M=0,07,
SD=0,26) and politicians in a coalition party (M=0,01, SD=0,08) for the element directness.
The difference is significant t(92,18)=2,27, p=0,025, CI[0,01 ; 0,12].
Another difference was found between politicians in an oppositional party (M=0,42,
SD=0,49) and politicians in a coalition party (M=0,28, SD=0,45) for the element
assertiveness. The difference is significant t(154,19)=2,24, p=0,026, CI[0,02 ; 0,27].
There was a difference found between politicians in an appositional party (M=0,14, SD=0,35)
and politicians in a coalition party (M=0,05, SD=0,22) for the element accountability. The
difference is significant t(119,04)=2,16, p=0,033, CI[0,01 ; 0,17].
This means that in all four of the elements the journalist has more bias towards politicians in
the oppositional parties than politicians in the coalition parties.
Gender
There is no significant difference found between male and female politicians for the elements
initiative, directness, assertiveness, and persistence.
There is a difference found between male politicians (M=0,29, SD=0,45) and female
politicians (M=0,16, SD=0,37) for the element opposition. The difference is significant
t(259,59)=2,51, p=0,013, CI[0,03 ; 0,277].
There is a difference found between male politicians (M=0,12, SD=0,33) and female
politicians (M=0,03 SD=0,16) for the element accountability. The difference is significant
t(229,46)=3,05, p=0,003, CI[0,03 ; 0,15]. This means that in both of the elements the
journalist has more bias towards male politicians than female politicians.
Conclusion and discussion
The aim of this study was to contribute to the knowledge about coverage bias on television
and statement bias on television by performing a content analysis. The results of this content
analysis were analysed and exposed certain patterns that will be discussed now.
Coverage bias
Bias was defined as “any tendency in a news report to deviate from an accurate, neutral,
balanced and impartial representation of ‘reality’ of events and social world.” (McQuail,
2010). For the coverage bias this means the characteristics age, gender, experience, and
political party of the politicians in the program Pauw are representational to the politicians in
the second chamber. For the characteristics age and experience it is indeed representational
and thus not bias. For the characteristic gender it is not as one out of three politicians is
female whereas on the show only one out of four is female, which makes the program Pauw
not representational and even bias towards the characteristic gender looking at the definition
of McQuail (2010). The representation of gender is discussed in many studies with diverse
outcomes such as the research of Vos (2014). The outcomes of this research are not in line
with the findings of Vos (2014) as she concluded that only when the profession is not
measured precisely bias in gender would be found. In this study the profession was clear and
did not need measuring as it concerns the politicians in the second chamber. However, a bias
was still found. Hayes and Lawless (2013) considered gender as a subject of the past but this
study shows that this is not the case in the program Pauw.
Another bias was found in the characteristic political party. The bias found in this study could
possibly be explained by the theory of news values and news routines (Van Dalen, 2012). His
theory was that the choice for a politician gets limited based on the subject that is going to be
discussed in the program and thus influence the choice. However this does not limit the
choice to just one politician. Even though it is partially the news routines and the news values
that influence the choices, there is still space left for a journalist to influence which politician
gets on the show based on personal preferences. This is the part where the personal
working
mechanisms, preferences and ideology can play a role in the choice of the politician, which
could be the case in the program Pauw as a bias is found.
A difference between the program Pauw and the second chamber on gender or political
parties maybe does not seem as much but it can be of influence because a fair representation
of political parties is needed for the public to base their political choices on (DellaVigna &
Kaplan, 2006). When a party gets none or limited attention on television it does not gets the
chance to position itself in the political field for the voters. It would be the same for gender as
it would mean that inequality keeps on existing as the female politicians get less chances to
position themselves (Devitt, 2002).
This research had a limitation of just measuring the bias in one program.
Because this study
had the limitation of researching only one program it is advisable that further research is done
comparing programs to see if there is bias in the representation of the politicians. Programs
like De wereld draait door, Knevel en de Brink but also commercial television programs like
Business Class could be interesting for content analyses as these discuss and invite many
politicians. If a bias would be found, thereby replicating the current research results, it could
mean that bias does play a notable role in the representation of politicians on television, which
would be in conflict with the neutrality of the journalists.
Statement bias
For statement bias part of the research, bias in the presentation of the journalists is studied
and
for all the three variables (Left/right winged, opposition/coalition and gender) significant
results were found. There was more bias towards left winged politicians, politicians in
oppositional parties and male politicians. Although it might not seem like it, the outcomes of
the study are supported by accusations that Pauw got from many critics on being biased
towards right winged politicians and women as concluded in the study of
Ruigrok et al.
(2012). The research of Huls and Varwijk (2011) can support this, because on the
characteristic left/right winged they indeed found Pauw being more biased towards right
winged politicians and females. In an attempt to be more neutral it is possible that Pauw
purposely tried to be biased towards left winged politicians and male politicians as he was
accused of being biased towards right winged politicians and females. This could be a
reaction on what Gulati et al. (2004) called a structural bias, where the bias does not
originates from ideology. Pauw probably chooses it out of a professional angle to be more
neutral. Especially because it is in contrast in his bias with the study of Huls and Varwijk
(2011), where his bias probably originated more out of ideology or personal believes as Van
den Besselaar (2010) argues journalists do. In both ways the outcomes of this study reinforces
the theory that journalists are biased in their interviewing and cannot be objective (Luyendijk,
2008). However, it does have to be taken into consideration that politicians also try to take
control in an interview by learning tactics and preparing for the interview. This way they
make it harder for the journalist to get answers to the questions they do not like (Clayman &
Heritage, 2002). The reaction of the journalist is that they get more aggressive in their
interviews (Carlier, 2007). For example,
oppositional parties could be more aggressive in the
interviews attacking the decisions coalition parties made, as it is their job to do the same thing
in the second chamber as well, which could make the reaction of the journalist less neutral. It
could also be that the attitude of the male politicians was more aggressive than the female
ones and therefore the approach of the journalist adjusted to that. This would also be the
recommendation for further studies, as it was a limitation in this study that there was only
looked at the journalist and not other aspects that could influence the bias. Pauw or
comparable programs should be studied in a much broader sense. Studying the answers of the
politicians, their reaction and attitude should be taken into account in interviews, as this could
be part of the reason for the excising bias. Furthermore, other aspects that could influence the
bias should be taken into consideration as well. For example by looking at the others guests
that interfere in the conversation but also the reaction of the audience. Not only the verbal
ones, but also negative or positive facial expressions or sounds. Only by looking deeper into it
and taking all the possible influences into consideration it can be concluded that a bias of a
journalist exists and how it can be explained. Studying this is important as the news
interviews are getting more important in the media landscape and in political communication
(Clayman & Heritage, 2002). The researches Clayman and Heritage (2002) even suggest it as
social academic study material only because it has such a prominent role in modern public
domain. Journalists have a democratic function and television interviews worldwide are
getting one of the most used formats for political communication (Carlier, 2007).
Finally, another limitation of this study was that the twelve politicians were chosen based on
certain characteristics like political party or gender instead of just randomization. This way
the parties as well as gender were kept equal. Looking at the outcome of the outcomes of the
coverage bias of this research, there was a bias found for parties and gender. Randomization
for statement bias would have probably given other outcomes in the variety of characteristics
looking at the outcomes of the coverage bias. For example PvdA (31%) politicians would
have got much more chances to be in the chosen 12 than the SP (9%). Nonetheless the
significant outcomes of this research can be seen as an important steppingstone for further
research about bias in the media. It is of importance that studies keep searching for reasons
and existence of bias to be able to strive for a healthy democracy.
“A reliable and multiform journalist is of utmost importance for the democratic society, that
cannot function without informed citizens and a free exchange of ideas. In that open society
the journalist gets the right to gather news freely, with the responsibility to do this truthfully,
independent, fair and openly.
References
Arnold, R. D. (2004). Congress, the press and political accountability. Princeton, NJ:
Princeton University Press.
Bernhardt, D., Krasa, S., & Polborn, M. (2008). Political polarization and the electoral effects
of media bias. Journal of Public Economics, 92(5), 1092-1104.
Besselaar van den, P. (2010). Journalisten negeren feiten als het uitkomt. Retrieved from
http://www.villamedia.nl/opinie/bericht/journalisten-negeren- feiten-als-het-uitkomt/
Carlier, N. (2007). Politieke praatjes; Een analyse naar vraag en antwoord in televisie-
interviews met Nederlandse fractievoorzitters. Masterscriptie, Erasmus Universiteit,
Rotterdam.
Clayman, S. E., & Heritage, J. (2002). The news interview; Journalists and public figures on
the air. Cambridge: Cambridge University Press.
Cook, T. (1986). House members as newsmakers: The effects of televising Congress.
Legislative Studies Quarterly, 11(2), 203–226.
Entman, R. M. (2007). Framing bias: Media in the distribution of power. Journal of
communication, 57(1), 163-173.
Eurobarometer (2013), Media use in the European Uninion, Brussels, 80.
D'Alessio, D., & Allen, M. (2000). Media bias in presidential elections: a meta‐ analysis.
Journal of communication, 50(4), 133-156.
DellaVigna, S., & Kaplan, E. (2006). The Fox News effect: Media bias and voting (No.
w12169). National Bureau of Economic Research.
Devitt, J. (2002). Framing gender on the campaign trail: Female gubernatorial candidates and
the press. Journalism & Mass Communication Quarterly, 79(2), 445-463.
Fogarty, B. J. (2008). The strategy of the story: Media monitoring legislative activity.
Legislative Studies Quarterly, 33(3), 445–469.
Gerber, A., Karlan, D., & Bergan, D. (2007). Does the Media Matter? A Field Experiment.
Gershon, S. A. (2012). Press secretaries, journalists, and editors: Shaping local congressional
newscoverage. Political Communication, 29(2), 160–183.
Clayman, S.E., Elliott, M.N., Heritage, J. and McDonald, L.L. (2007) ‘When Does the
Watchdog Bark? Conditions of Aggressive Questioning in Presidential News Conferences’,
American Sociological Review 72: 23–41.
Gulati, G. J., Just, M. R., & Crigler, A. N. (2004). News coverage of political campaigns.
Handbook of political communication research, 237-256.
Hayes, D., & Lawless, J. L. (2013, [January]). A non-gendered lens: The absence of
stereotyping in contemporary congressional elections. Paper presented at the annual meeting
of the Southern Political Science Association, Orlando, FL.
Huls, E., & Varwijk, J. (2011). Political bias in TV interviews. Discourse & society, 22(1),
48-65.
Kahn, K. F. (1992). Does being male help? An investigation of the effects of candidate gender
and campaign coverage on evaluations of US Senate candidates. The Journal of Politics,
54(02), 497-517.
Kieskompas.(2012).TweedeKamerverkiezingen 2012. Retrieved from
http://www.tweedekamer2010from:.kieskompas.nl/page/1/default#top
Kleinnijenhuis, J., Van Hoof, A. M., Oegema, D., & De Ridder, J. A. (2007). A Test of
Rivaling Approaches to Explain News Effects: News on Issue Positions of Parties, Real‐
World Developments, Support and Criticism, and Success and Failure. Journal of
Kuklinski, J., & Sigelman, L. (1992). When objectivity is not objective: Network television
news coverage of U.S. senators and the “paradox of objectivity.” Journal of Politics, 54(3),
810–833.
Luyendijk, J. (2008). Een waanzinnige respons. Retrieved from
http://www.jorisluyendijk.nl/
McQuail, D. (2010). McQuail's mass communication theory. Sage publications.
Midtbø, T. (2011). Explaining media attention for Norwegian MPs: A new modelling
approach. Scandinavian Political Studies, 34(3), 226–249.
Nederlands genootschap van hoofdredacteuren (z.d.). Code voor de journalistiek. Retrieved
from:http://www.genootschapvanhoofdredacteuren.nl/het_genootschap/code-voor-de
journalistiek.html
Patterson, T. E., & Donsbagh, W. (1996). News decisions: Journalists as partisan actors.
Patterson, T. E. (1996). Bad news, bad governance. The Annals of the American Academy of
Political and Social Science, 546, 97-108.
Reese, S. D. (2001). Understanding the global journalist: A hierarchy-of-influences approach.
Journalism Studies, 2(2), 173-187.
Ruigrok, N., Schaper, J., Welbers, K., Jacobi, C., van der Beek, P., & Wagemakers, S. (2012).
Impact van Pauw & Witteman.
Schaffner, B. F., & Sellers, P. J. (2003). The structural determinants of local congressional
news coverage. Political Communication, 20(1), 41–57.
Stocking, S. H., & Gross, P. H. (1989). How do journalists think? A proposal for the study of
cognitive bias in newsmaking. ERIC Clearinghouse on Reading and Communication Skills,
2805 E. 10th St., Smith Research Center, Suite 150, Bloomington, IN 47405.
Squire, P. (1988). Who gets national news coverage in the U.S. Senate? American Politics
Quarterly, 16(2), 139–156.
Tsfati, Y., Elfassi, D. M., & Waismel-Manor, I. (2010). Exploring the association between
Israeli legislators’ physical attractiveness and their television news coverage. International
Journal of Press/Politics, 15(2), 175–192.
Tweede kamer, der staten general. Alle kamerleden. (2015). Retrieved from:
http://www.tweedekamer.nl/kamerleden/alle_kamerleden
Van Aelst, P., Maddens, B., Noppe, J., & Fiers, S. (2008). Politicians in the news: Media or
party logic? Media attention and electoral success in the Belgian election campaign of 2003.
European Journal of Communication, 23(2), 193–210.
Van Dalen, A. (2012). Structural Bias in Cross-National Perspective How Political Systems
and Journalism Cultures Influence Government Dominance in the News. The International
Journal of Press/Politics, 17(1), 32-55.
Veblen, E. P. (1981). Liberalism and national newspaper coverage of members of Congress.
Polity, 14(1), 153–159.
Veldkamp. (2010). Mediagebruikersrapport 2010. Retrieved from
https://www.nationaalcrisiscentrum.nl/sites/risicoencrisis.sandbox.tdclighthouse.com/files/ass
ets/documents/mediagebruikersrapport_2010.pdf
Vos, D. (2014). Which politicians pass the news gates and why? Explaining inconsistencies in
research on news coverage of individual politicians. International Journal of Communication,
Wind, M. (2007) ‘Publieke Omroep: Het Blijft Kleven, dat Linkse Imago’ [The National
Channel: It Does Not Get Rid of Its Left-Wing Image], Trouw, 24 November. Retrieved
from: www. trouw.nl/krantenarchief/
Appendix 1: List of guests on Pauw
Ma 1 sept: j
1. Jozias van Aartsen (VVD, Burgemeester den Haag, 1947, 1970) 2. Jeanine Hennis-Plasschaert (VVD, minister van defensie, 1973, 2000) 3 Alain Clark,
4. Martijn Koning 5. Ilja Leonard Pfeijffer Di 2 sept:
6. Dimitri Verhulst, 7. Martijn fischer, 8. Diederick Koopal,
9.Wim van de Camp (CDA, en
10. Myrthe Hilkenslid europees parlement, 1953, 1986) Wo: 3 sept:
11.The Kik, 12.Femke Halsema
13. Sybrand van Haersma Buma (CDA, fractie voorzitter tweede kamer, 1965, 2002) en 14. Henk Spaan
Do 4 sept: 15.Victor Reinier, 16. Sanne Wallis de Vries,
17. Emile Roemer (SP, fractievoorzitter,1962, 2010) 18. Hagar Peeters en
19. Gert-Jan Segers (christen uni, tweede kamerlid, 1969, 2012) Vr 5 sept:
20. Sanne Hans,
21. Fatima Moreira de Melo, 22. Jacques Brinkman, 23. Michiel Pestman, 24. Abdou Bouzerda en I
25. brahim Wijbenga (CDA, raadslid Eindhoven, 1977, 2013) Ma: 8 sept:
26. Paul de Leeuw, 27. Erik van Muiswinkel, 28. Cor Bakker, 29. Eric Vloeimans, 30. Jeroen Akkermans en 31. Peter Middendorp Di 9 sept: 32. Herman Brusselmans, 33. Emilio Guzman, 34. Razia Santoe, 35. Nick Mulvey, 36. Veeru Mewa en 37. Olaf Koens Wo 10 sept:
38. Arie Slob christen uni, fractie voorzitter, 1961, 2002) 39. Ferry Mingelen,
41. Karline Kleijer en 42. Floor van der Meulen Do 11 sept: 43. Giovanca, G 44. Gerdi Verbeet, 45. Frits Wester en 46. Boyan Slat Vr 12 sept: 47. Diederik Stapel, 48. Anton Dautzenberg, 49. Roel Coutinho, 50. Bart Waalewijn,
51. Fleur Agema,(PVV, tweede kamerlid, 1976, 2006) J 52. Jurre van Kesteren en
53. Typhoon Ma 15 sept: 54. Arjan Erkel, 55. Midas Dekkers, 56. Abdelkarim El-Fassi, 57.Nasrdin Dchar, 58. Bram Moszkowicz en
59. Patrick van der Broeck (CDA, gedepudeerde province Limburg, 1966, 1995) Di 16 sept:
60. Jaaike Brandsma, 61. Edwin Vermetten, 62. Kees Jansma en
63. Edith Schippers (VVD, Minister van gezondheid, 1964, 2003) Wo 17 sept:
64. Jan Roos, 65. Michael Schaap, 66. Myrthe Hilkens,
67. Wouke van Scherrenburg,
68. Ahmed Marcouch (PvdA, parlementslid, 1969, 2010) en 69. Paul van Musscher
Do 18 sept: 70. Ferry Mingelen,
71. Alexander Pechtold (D66, fractievoorzitter,1965,2006) 72. Damiaan Denys,
73. Franka Hummels, 74.Jos van der Velpen, 75. Sander Janssen en J 76. Jan-Hein Kuijpers Vr 19 sept:
77. stefan de Vries, 78. Yuri van Gelder, 79.Bart Chabot en
80. Anouchka van Miltenburg Ma 22 sept:
82. Ozcan Akyol,
83. Samira Bouchibti(PvdA, kamerlid, 1970, 2006), 84. Farid Azarkan, 85. Jaap Jongbloed en 86. Mieke Stemerdink Di 23 sept: 87. Johan Goossens, 88. Stine Jensen, 89. Bénédicte Ficq, 90. Jan-Hein Kuijpers, 91. Tom Kleijn,
92. Harry van Bommel (SP, kamerlid, 2,1998) en 93. Han ten Broeke (VVD, kamerlid, 1969, 2006) Wo 24 sept:
94. Peter Plasman,
95. Gijs van de Westelaken, 96. Theodor Holman, 97. Hans Hillen, 98. Peter van Uhm, 99. Steven Ruijter 100. Tom kleijn Do 25 sept:
101. Jeroen Dijsselbloem (PvdA, minister van financien, 1966,2002) 102. Ellen ten Damme,
103. Natalie Righton, 104. Ozcan Akyol, J 105. Jan Vlug en 106. William Spaaij Vr 26 sept: 107. Lucia Rijker, 108. Marieke Niestadt, 109. Abdul Ahmadzai, 110. Wil Eikelboom, 111. Mart Smeets, 112. Diana Prazak en 113. Dimitri Bontinck Ma 29 sept:
114. Paul van Vliet, 115. Hans Jaap Melissen, 116. René Mioch, 117. Laura Smit, 118. Ralph de Wit, 119. Roy Eggink en
120. Joël Voordewind (christenuni, tweede kamerlid, 1965, 2006) Di 30 sept:
121. Hans van der Togt, 122. Bert van der Veer, 123. Klaas Wilting, 124. Nico Meijering en
Wo 1 okt:
126. Peter van Uhm, 127. Gerard Spong, 128. Michael Boogerd, 129. Marinne Zwagerman, 130. Olcay Gulsen en 131. Danny Mekic Do 2 okt: 132. Ferry Mingelen, 133. George van Houts, 134. Merel van Houts, 135. Niels van Elk,
136. Henk Nijboer (PvdA, kamerlid, 1983, 2012) en 137. Jeroen Smit
Vr 3 okt: 138. Jeroen Woe, 139. Niels van der Laan,
140. ahmed Aboutaleb (PvdA, Burgemeester, 1961 2007), 141. Riet Brinkman,
142. Linda Penders, 143. Kees Jansma en 144. Marco van Duijn Ma 6 okt:
145. Rob Oude Breuil, 146. Natalie Righton,
147. Jos van Rey (VVD, Lid provincial staten, 1945, 2011) en 148. Robert Doornbos
Di 7 okt:
149. Ferry Mingelen, 150. Beatrice de Graaf, 151. Hans Dorrestijn, 152. Zazi, Sadet Karabulut en 153. Theo ten Haaf
Wo 8 okt: 154. Frans timmermans Do 9 okt: 155. Karline Kleijer, 156. Farid Azarkan, 157. Aart Zeeman, 158. Peter Buwalda, 159. Ad Visser, 160. Martin Buitenhuis en 161. Edwin de Roy van Zuydewijn Vr 10 okt: 162. Olaf Koens, 163. Axel Rüger, 164. Marike Stellinga, 165. Jesse Klaver, 166. Naeeda Aurangzeb en
Ma 13 okt:
168. Sander Dekker, 169. Quinsy Gario, 170. Sunny Bergman, 171. Joram van Klaveren, 172. Ton Senf en 173. Ahmed Khottoul Di 14 okt: 174. Jan Mulder, 175. Monic Hendrickx, 176. Johnny de Mol, 177. Jan Slagter, 178. Frits Barend en 179. Bob van der Goen Wo 15 okt:
180. Martijn Koning, 181. Filip Raes,
182. Martine en Louise Fokkens, 183. Metje Blaak,
184. Caja van Tolie, 185. Linda Futa van Goch, 186. Henk Bleker en 187. Dion Graus Do 16 okt:
189. Bert van der Veer, 190. Marike Stellinga, 191. Marc Giling, 192. Douwe Linders, 193. Freek de Jonge en 194. Patrick Peezenkamp Vr 17 okt: 195. Bianca Krijgsman, 196. Dolf Jansen, 197. Henk Krol en J 198. Jan Nagel Ma 20 okt: 199. Tom Kleijn, 200. Jeroen Oerlemans, 201. Herman van Veen, 202. Eric van Gorp Di 21 okt: 203. Frits Barend, 204. Margot Ros, 205. Maike Meijer, 206. Wanda de Kanter, 207. Pauline Dekker, 208. Jaap de Groot en 209. Henk van der Meijden
Wo 22 okt: 210. Yehudi Moszkowicz, 211. Theo Hiddema, 212. Frieda Mulisch, 213. Enzo Knol, 214. Peter R. De Vries en 215. Anna Korterink Do 23 okt: 2.16. Ewald Engelen, 217. Nout Wellink en 218. Marco Kroon Vr 24 okt: 219. Henk Spaan, 220. Dolf Jansen,
221. Matthijs van Nieuwkerk, 222. Filip Joos en
223. Teun van Dijck Ma 27 okt:
224. Diederik Samsom, 225. Hozny El Asadi, 226. Nico van Hasselt, 227. Jo Roos,
228. Tine van Beijeren-Engelsman, 229. Pim Christiaans en 230. Johannes Rypma Di 28 okt: 231. Katja Herbers, 232. Jörgen Raymann, 233. Nienke Miezenbeek, 234. Heidy Rebel, 235. Willem Bosch, 236. Giel de Winter en 237. Thomas van der Vlugt Wo 29 okt:
238. Tom Kleijn, 239. Peter Buwalda, 240. Sophie Hilbrand, 241. Piet Hein van der Hoek, 242. Daniëlla Blanken, 243. Annemarie Heite Do 30 okt: 244. Ferry Mingelen, 245. Lucia Rijker, 246. Jeroen Smit, 247. Remy Bonjasky, 248. Porgy Franssen, 249. Ella Vogelaar, 250. Yoeri Albrecht. Vr 31 okt:
252. Ad Visser, 253. Tim Knol, 254. Mario van Parijs en 255. Isa Hoes
Ma 3 nov:
256. Bert Wagendorp, 257. Katinka Polderman, 258. Leontien van Moorsel, 259. Huub Stapel,
260. Arko van Bakel en 261. Saskia Belleman Di 4 nov:
262. Theo Reitsma, 263. Ria Visser, 264. Conny van Bentum, 265. Ben Oude Nijhuis, 266. Martin van Rijn, 267. Nico Meijering, 268. Jan-Hein Kuijpers en 269. Sander Janssen Wo 5 nov:
270. FU Van Rijn, met 271. Renske Leijten, 272. Jan Slagter en
273. Wouke van Scherrenburg. –
274. Adriaan van Dis: Ode aan zijn moeder. –
275. Heleen Dupuis: Reageert op alle commotie. -Miljonairsdebat: 276. Erik de Vlieger vs
277. Harry de Winter Do 6 nov;
278. Maarten van Rossem, 279. Menno Bentveld, 280. Fred Jansen, 281. Hein Dudink en 282. Peter Aerts Vr 7 nov: 283. Beatrice de Graaf, 284. Ellen ten Damme, 285. Willem Bosch, 286. Ronald Plasterk,
289. Mara Hoek, Leonie Vleesenbeek, Don Vleesenbeek en Cecile Brouwer Ma 10 nov: 290. Cécile Brouwer, 291. Pieter-Jaap Aalbersberg, 292. Jacobine Geel, 293. Paul de Kuijer, 294. Arie de Bruijn en 295. Peter Arts Di 11 nov:
297. Patrick Peezenkamp, 298. Nelleke van der Krogt, 300. Herman Pleij, 301.Tanja Jess, 302. Hans Docter, 303. Henk Westbroek, 304. Henk Temming en 305. Filemon Wesselink Wo 12 nov: 306. Frits Barend, 307. Peter R. De Vries, 308. Sanae Ben Abdelouahab, 309. Fatiha el Khattabi, 310. Souad Mokhtari, 311. Meta Boom, 312. Renske Lonhard en 313. Cheryl Boekholt Do 13 nov: 314. myrthe Hilkens, 315. Ferry Mingelen, 316. Johan Derksen, 317. Stephanie-Joy Eerhart, 318. Rudy Bennett, 319. Theo van Es, 320. Piet Eerhart, 321. Erik van Engelen en 322. Peter Hagens Vr 14 nov: 323. Gerard Spong, 324. Dolf Jansen, 325. Frank Evenblij, 326. Tunahan Kuzu en 327. Selçuk Öztürk Ma 17 nov: 328. Fleur Agema, 329. Tom Middendorp, 330. Otwin van Dijk en 331. Ali Bouali Di 18 nov: 332. Ferry Mingelen, 333. Esther Verhoef, 334. Saskia Noort, 335. Gerrit Zalm en 336. Robin de Levita Wo 19 nov: 337. Jeroen Smit, 338. Willem Bosch, 339. Derk Sauer, 340. Liesbeth Zegveld, 341. Rocky Tuhuteru,
343. Jan Smit, 344. John de Wolf, 345. Evgeniy Levchenko, 346. Jan van Halst Do 20 nov: 347. Tom Kleijn, 348. Giovanca, 349. Gerard Spong, 350. Ad Visser, 351. Willem Bosch en 352. Lodewijk Asscher Vr 21 nov: 353. Gert-Jan Segers, 354. Gerard Spong, 355. Willem Bosch, 356. Martijn Froon, 357. Ingrid Wender en 358. Minou Bosua Ma 24 nov: 359. Marike Stellinga, 360. Remy Bonjasky, 361. Peter Aerts, 362. Ernesto Hoost, 363. Rico Verhoeven, 364. Peter LeMaire, 365. Elly Winkel, 366. Sander de Kramer en 367. Elle van Rijn Di 25 nov: 368. Kim Faber, 369. Hubert Jansen, 370. Serge Weening, 371. Sharon Gesthuizen, 372. Evita Pagie, 373. Sietse Fritsma en 374. Dorine Manson Wo 26 nov:
375. Janny van der Heijden, 376. Jack Wouterse, 377. Hajé Weisfelt, 378. Lex Uiting, 379. Carola Schouten, 380. Don Ceder,
381. Annemarie van Gaal, 382. Simone de Jong en 383. Wilbert de Donk Do 27 nov: 384. Liesbeth List, 385. Annemarie Oster, 386. Coosje Smid,
388. Charly Luske, 389. Jordy Buijs, 390. Trudy Coenen, 391. Selli Altunterim, 392. Ozcan Akyol en 393. Sadet Karabulut Vr 28 nov:
394. Jan Jaap van der Wal, 395. Kees Broere, 396. Gijs Staverman, 397. Inez Weski, 398. Dione de Graaff, 399. Otto Wichers, 400. Martijn Fischer, 401. Axel Ruger, 402. Kees van Oort en 403. Vincent Willem van Gogh Ma 1 dec:
404. Kiki Schippers, 405. Lize van Olden, 406. Victoria Osborn, 407. Andre Seebregts, 408. Tinka Veldhuis, 409. Saskia Belleman, 410. Sanne Wallis de Vries, 411. Peter Plasman, 412. Claudia Schoemacher, 413. Marith Rebel-Volp, 414. Justice en Chelina Di 2 dec: 415. Fred Teeven, 416. Evita Pagie, 417. Ilja Gort, 418. Hans Dorrestijn, 419. Saskia Nadort en 420. Roby Nadort Wo 3 dec: 421. Peter Plasman, 422. André Manuel, 423. Atilay Uslu, 424. Jan Keunen, 425. Frits Broks, 426. Theo Weterings, 427. Joeri Pels, 428. Monique Pels en 429. Oscar Hammerstein Do 4 dec: 430. Myrthe Hilkens, 431. Tom Kleijn, 432. Gerard Spong, 433. Erica Terpstra,
435. Lita Rabeling, 436. Daphne Roes, 437. Frits Huffnagel en 438. Paul Jansen Vr 5 dec: 439. Dolf Jansen, 440. Richard Groenendijk, 441. Hennie van der Most en 442. Femke van Rossum Ma 8 dec:
443. Damiaan Denys, 444. Jeroen Krabbé, 445. Heidy Vernee,
446. Myrthe van der Meer en Pippa Di 9 dec:
447. Martine Sandifort, 448. Remko Vrijdag, 449. Jens Olde Kalter, 450. Wouter Laumans en 451. Jacqueline Hagemann Wo 10 dec: 452. Ferry Mingelen, 453. Bart Chabot, 454. Frits Huffnagel, 455. Ruben Nicolai,
456. Laurentien van Oranje en 457. Ruben Oppenheimer Do: 11 dec: 458. Claudia de Breij, 459. Cornald Maas, 460. Felix Rottenberg, 461. Willibrord Frequin en 462. Rob Muntz Vr 12 dec: 463. Bram Moszkowicz, 464. Ad Visser, 465. Jan van Hooff, 466. Maxim Hartman, 467. Jim Jansen, en 468. Merijn Vunderink Ma 15 dec:
469. Sander Janssen, 470. Jens Olde Kalter, 471. Youp van ’t Hek, 472. Adri Lammers, 473. Kevin van Geet, 474. Natascha Freiwald, 475. Leonie Verstering en 476. Marno Wolters
Di 16 dec:
477. Fatima Moreira de Melo, 478. Ferry Mingelen, 479. Bart Chabot, 480. Natalie Righton, 481. Naeeda Aurangzeb, 482. Frits Barend en 483. Rob Oudkerk Wo 17 dec: 484. Ferry Mingelen,
485. Wouke van Scherrenburg, 486. Eric Corton, 487. Gerard Ekdom, 488. Coen Swijnenberg, 489. Domien Verschuuren, 490. Ed Nijpels, 491. Jan Vos en 492. Derwin Schorren Do 18 dec: 493. Myrthe Hilkens, 494. Ferry Mingelen, 495. Ed Nijpels, 496. Kees van Kooten, 497. Wim de Bie, 498. Tijl Beckand en 499. Mike Boddé Vr 19 dec: 500. Mike Boddé, 501. Joram van Klaveren, 502. Tunahan Kuzu, 503. Selcuk Ozturk, 504. Wim Kieft, 505. Patrick Lodiers en 506. Guusje ter Horst
