|
This paper was presented at the Association for Education in Journalism and Mass Communication in San Antonio, Texas August 2005. If you have questions about this paper, please contact the author directly. If you have questions about the archives, email rakyat [ at ] eparker.org. For an explanation of the subject line, send email to [log in to unmask] with just the four words, "get help info aejmc," in the body (drop the "").
(Jan 2006) Thank you. Elliott Parker ==================================================================== Partisan and Structural Balance in Newspaper Coverage of U.S. Senate Races in 2004 With Female Nominees
By
Frederick Fico Eric Freedman Brad Love
A paper submitted to the Theory and Methodology Division of AEJMC for consideration for presentation at the August 2005 Conference in San Antonio.
Frederick Fico is professor and Eric Freedman is assistant professor in the School of Journalism at Michigan State University, where Brad Love is a doctoral student in the Mass Media Ph.D. Program.
Abstract Nine newspapers covering U.S. Senate races in 2004 were mostly even-handed in the space and prominence given candidates. Reporter gender, newsroom diversity and newspaper size were associated with partisan imbalance giving more favorable treatment to Democrats. The partisanship of a story's lead predicted the story's structural imbalance, regardless of the party the imbalance favored. However, story partisan and structural imbalances were negligibly related, suggesting that news processing conventions rather than journalistic partisanship produced the imbalance.
Key Words: fairness; balance; election reporting; bias Media bias is seldom defined in a manner that permits it to be reliably observed in a variety of contexts. More seldom still is such bias related to journalist or news organization characteristics that enable it to be predicted. The first goal of this research, therefore, is to define two types of news bias that are distinct in their origin. The first is a structural bias in individual stories that favors one side in a conflict. Structural bias may result from news reporting conventions and limitations or the attention-commanding activities of the conflict sides. The second is a partisan bias in which aggregate news coverage systematically favors the liberal or conservative side in a political conflict. Political bias results from journalists' political orientations infiltrating coverage despite reporting conventions mandating impartiality. The second goal of this research, then, is to illuminate factors causally related to these structural and political biases. Certainly if bias exists in news reporting, journalists themselves need to know what it is and even how they might minimize it. For their part, citizens need to know the degree of caution and confidence they should have in the political information they get from media. Both the news media and the public will be better served by knowledge of such biases than by assumptions of partisanship or purity. THEORICAL FRAMEWORK Shoemaker and Reese define five levels of influences on news media content, with higher levels constraining the influence of those below.1 Influences from four such levels include non-media institutions affecting media organizations, specific media organizational characteristics, work routines within media organizations, and the characteristics of individual journalists. This study explores election coverage bias potentially influenced from these four levels. At the societal level, the operation of the political process will both command media attention and shape the coverage. At the organization level, a news organization's audience reach determines the resources potentially available to do news work. Organization goals and resources will in turn shape goal-attainment routines, the kind of personnel hired, and the rewards and punishments that reinforce desired behaviors. But the backgrounds, beliefs and expertise of such individual workers will also, to some extent, help shape the work they do. Some research has employed this hierarchical model's conceptual ordering to explore influences on political bias in news content. Most research, however, has focused solely on ways of defining and describing aspects of media content. For example, a review of content analysis studies published in Journalism & Mass Communication Quarterly since 1998 showed that barely a third of them attempted to predict any quality of media content.2 This study brings into a hierarchical model variables that previous research has empirically found to be directly and indirectly related to conflict coverage bias. Two streams of research are reviewed. One deals with studies of election coverage fairness and balance. The second deals with influences on such election coverage balance. Bias and Election Reporting Science becomes biased when atypical observations of some phenomenon produce misleading inferences about the phenomenon. In most journalistic work, however, observations are indirectly relayed by sources. Bias can therefore occur if source selection by reporters produces atypical or incomplete perspectives or information about some news topic. This problem of source selection goes directly to fairness and balance in journalism. Fairness in journalism usually refers to whether relevant sides in a conflict are included in news coverage. Balance usually refers to the evenness with which such conflict sides are treated relative to one another in that coverage. Fairness is clearly a necessary but not sufficient condition for balance in any single story. But in the aggregate of stories on some conflict, individually unfair ones reflecting opposing sides may "balance out" in the entire coverage. Fairness and balance in reporting become problematic, of course, when judgments of source availability, credibility, and truthfulness must also be made. Fairness and balance become still more problematic when news values such as impact or unusualness are part of journalistic decision making. However, many political and social issues involve conflict over values, meanings and priorities that cannot be decided by an appeal to evidence. Support or opposition to abortion, for example, may depend on the meanings and values one brings to pregnancy rather than on a decisive biological fact. In other words, most coverage of political conflict involves judgments by journalists about the legitimacy of sources and their contentions. In the political arena, journalistic judgments that result in departures from fairness and balance may have troublesome consequences for both public policy and for media credibility. Indeed, the concern for fair and balanced election reporting flows from both ethical and practical concerns that biased reporting may actually affect public policy outcomes. During the decades following World War II, such concerns were largely allayed by "minimal-effects" studies, and by traditional agenda-setting research emphasizing news media power to tell people "what to think about" rather than "what to think."3 More recently, however, "attribute" agenda setting has explored how coverage of positive or negative issue attributes can influence the public's positive or negative evaluations of issues, with real consequences on their electoral decision making.4 Also, experimental framing research has demonstrated how news coverage context can influence how news consumers respond to an issue.5 Empirical studies of news coverage political bias have focused largely on U.S. presidential elections, tracking aggregate attention to Republican and Democratic candidates in major newspapers and television networks. Findings have been ambiguous, but one pattern seems discernable (although barely so). Studies conducted during the 1960s and 1970s have (coinciding with the dominance of the traditional agenda-setting assessment of media power) generally found more even-handed coverage, while more recent work has illuminated imbalances. For example, Evarts and Stempel found no clear bias in their 1972 study of television networks, three major news magazines and six major newspapers.6 Similarly, Hofstetter found mixed results in his 1972 study of several media.7 Stovall, however, found evenhanded newspaper attention to candidates in the 1980 election, but not in the 1984 election, in which coverage favored the Republican.8 Kenny and Simpson found imbalance favoring the Republican by a Washington newspaper in the 1988 election, which they attributed to its conservative owner.9 Lowry and Shidler found television sound bites in 1992 and 1996 favoring the Democratic candidate, which they attributed to network liberal bias.10 Domke et al., however, found balanced positive and negative coverage in their 1996 study of two networks and 38 dailies.11 One problem with discerning patterns in these findings is that differences may be specific to particular elections, particular media, or particular organizations. But an additional complication is the possibility that different findings reflect different ways of conceptualizing and measuring political news bias. Studies assessing tone of coverage, for example, can be subjective and hard to replicate. Moreover, studies assessing aggregate partisan coverage of an election may miss structural bias in typical stories. Consequently, more objectively observable and replicable measures of individual stories developed in a series of studies are used in this research, thereby standardizing the measurement instruments for bias. These studies, anchoring measurement in the prominence and attention given partisan sources in individual election stories, have found imbalance toward one or the other candidates to be typical. Fico and Cote in newspaper studies of gubernatorial and presidential elections, for instance, found readers would typically encounter one-sided stories, or, if two sided, stories that gave much more space and prominence to just one of the candidates.12 Carter et al. found a similar pattern when adopting these measures to local television election coverage of a governor's race.13 However, Fico and Freedman, and Fico and Cote in newspaper studies and Fico et al. in a broadcast study found imbalance related more to incumbency than to the political party of the candidates.14 Influences on Election Reporting This research also incorporates independent variables empirically related in past studies to the partisan and structural bias dependent variables, thereby facilitating replication or modification of generalizations about factors related to bias. Moreover, this study includes additional variables that may help to predict election coverage bias. At the individual reporter level, studies have found that typical election story leads give play to only one side in a conflict. Fico and Cote in studies of newspaper coverage of gubernatorial and presidential races also found that such partisan leads predicted that candidate's domination of the rest of the story.15 Given that leads set the "agenda" for a story, this should not be surprising. Interestingly, however, imbalance in many stories was not necessarily related to imbalance in the sourcing, but rather to the ordering of sources within stories. Several studies have explored a second individual-level factor, reporter gender's relation to election stories. Fico and Freedman in a governor's race study in which a female Democrat ran against a male Republican found that male reporters gave more attention to the male Republican while female reporters gave more attention to the female Democrat.16 In a subsequent study, Freedman and Fico found that female reporters were more likely than male reporters to use non-partisan female sources in such election stories.17 Zeldes and Fico also found this gender difference in a study relating the gender of network news reporters covering the 2000 presidential race to their use of sources.18 Studies have also looked at how newsroom-level influences may shape story balance in election reporting. Fico and Cote and Fico and Freedman found that the more prominently stories were displayed, the more balanced they tended to be in their treatment of electoral opponents.19 The researchers attributed this to heightened editorial concern for balance of stories more likely to get public (and partisan) scrutiny, and to a socialization effect on reporters who model their own work on the qualities of stories given more prominent display. Few studies have directly tried to measure and relate how journalist political orientation may affect the balance of their stories. Richardson and Lancendorfer, however, found a newsroom "diversity index" related to its editorial support for affirmative action as a means to enhance diversity in higher education.20 They suggest that a large minority population in a news organization's circulation area pressures news organization management to hire more minorities, and that more minority representation in a newsroom communicates to news staff about management's own beliefs on diversity. Craft and Wanta found that the relative proportion of male and female editors at newspapers influenced the beats assigned male and female reporters, including the likelihood that women reporters would be assigned political stories.21 The implication of these studies is that both management beliefs and management demographic characteristics have direct and indirect influence on how reporters do their work. Even more, such a management commitment to newsroom diversity is plausibly related to a broader political liberalism that may influence election coverage. Fico and Freedman found that circulation, considered in that study a proxy variable for news organization resources, was related to the existence of specialty bureaus at the newspapers, and therefore indirectly related to content qualities.22 Certainly it is plausible that the more resources a news organization has, the more likely it will be able to hire more staff, including women to help achieve diversity goals. Finally, political parties and the candidates themselves will set the context in which news organizations cover elections. One well-researched context is the incumbency or challenger status of candidates.23 Lowry and Shidler, for example, explicitly tested and refuted the hypothesis that challengers would get more positive coverage than incumbents in broadcast news election coverage.24 More recently, Fico and Freedman and Fico et al. assessed the partisan and structural balance of races that were open compared to those in which a challenger sought reelection.25 Open races were characterized by more structurally balanced, even-handed individual stories. HYPOTHESES The Shoemaker-Reese hierarchical model and the studies discussed above provide guidance for hypotheses linking these variables to partisan and structural balance. Past research is replicated and extended, and measures are standardized and replicated to facilitate generalization across studies. Finally, this research approach is applied to a geographically broader set of elections and to races that are less commonly studied for their coverage balance. Structural Balance Hypotheses These hypotheses assume that newsroom conventions and resources are more likely to account for structural than political bias. H1: Stories with partisan leads are more structurally imbalanced than others.
H2: More prominent stories are less structurally imbalanced than others.
H3: Stories covering open races are less structurally imbalanced than others.
Partisan Balance Hypotheses
The following hypotheses specifically assume (for the sake of argument) that a liberal bias of journalists results in story partisan bias favoring Democratic candidates. H4: Stories by women reporters will have more partisan imbalance than others.
H5: Stories by newsrooms with higher newsroom diversity scores will have more partisan imbalance than others.
Finally, the two dependent variables in this research -- partisan and structural imbalance -- should be systematically related. Logically, stories that are imbalanced on the partisan index because of a political bias (liberal or conservative) on the part of the journalists should also be systematically imbalanced on the structural balance index. The reverse, however, would not logically hold, since random structural imbalance should equally benefit both opponents over time. Hence: RQ1: How is the partisan imbalance of stories related to their structural imbalance?
METHOD This study content analyzed the election coverage of the largest daily newspapers in nine states that held U.S. Senate elections in 2004.26 These races were selected because a woman candidate was running against a male opponent. In eight of the races, the women were Democrats. In five races, the women were incumbents. In one race a women challenged a male incumbent, and in three races women contested open seats. Races in which a woman ran against a man were selected for study because they should provide the strongest possible evidence for partisan imbalance. In other words, if a liberal bias is evident, all eight races in which a Democratic woman ran against a Republican man should have coverage giving more prominence and space to the Democrat. If structural bias is a better explanation, than attention to the races should not be patterned to favor the Democrat. The elections were studied from Labor Day to Election Day. The individual hard news story was the unit of analysis. Editorials, letters, op-ed pieces and analyses were excluded, as well as "Q & A" type stories. A story had to have at least three paragraphs on the U.S. Senate election to be included. Partisan and Structural Balance Measures These partisan and structural dependent variable measures were taken from the Fico and Freedman study of the 2002 governor's race in Michigan. Each election story was assessed on the basis of four components combined into an index for each story. These included the total number of paragraphs containing source assertions supporting each candidate, whether partisans for one or both candidates made assertions in the lead, whether partisan opponents made assertions in the second through fifth story paragraphs, and whether partisan opponents made assertions in the sixth through tenth paragraphs.27 To create the partisan balance index, each of the four components was first judged to favor the Republican, the Democrat, to be balanced or to be irrelevant (no partisan assertions were made). For example, the total paragraph measure was considered to favor the Republican if more Republican-support paragraphs appeared than Democrat-support paragraphs. The measure was considered to be balanced if an equal number of paragraphs contained assertions supporting each candidate. In a similar fashion, the lead, paragraphs two-through-five, and paragraphs six-through-ten story components were judged to favor one or the other candidate or be balanced. The partisan imbalance of a story as a whole was then determined by subtracting the number of components dominated by the Republican from the number dominated by the Democrat. The resulting story Partisan Balance score could range from +4 (all four components dominated by the Democrat) to -4 (all four components dominated by the Republican). To create the Structural Balance index, each of the four components was assessed identically as in the partisan index, but in this index the number of components dominated by the Republican in a story was subtracted from the number that favored the Democrat, and the absolute value then taken. The resulting story index score could range from 0, indicating a story structurally balanced between the two candidates (and also balanced on the partisan index) to 4, indicating that the same candidate (whether Republican or Democrat) was favored on each of the four components. Explanatory Variables Individual-level variables were story lead and reporter gender. The story's lead was assessed as a nominal-level variable based on whether it contained a partisan assertion supporting just one side (regardless of the side any such assertion supported). Reporter gender, a nominal-level variable, was determined from bylines, but newspapers were contacted to determine gender when names were ambiguous. The newsroom-level variable included was story prominence. Story prominence was an ordinal-level variable on which an inside page story scored 0, a section front page story scored 1, and a Page One story scored 2. At the organizational level, newsroom diversity and newspaper circulation were considered. A newsroom's diversity index was a ratio-level variable determined by dividing its proportionate newsroom diversity by the proportionate diversity of the news organization's surrounding community. A 0 indicated no correspondence between the two, and a score of 1 indicated that a newsroom's diversity matched the diversity of the surrounding community.28 Circulation rank was an ordinal-level variable used as a measure of news organization resources.29 Finally, type of race covered, a societal-level factor, was a nominal-level variable, with open races scored as 1 and others as 0. Measurement Validity and Reliability The balance indices weight the prominence given the assertions of partisans. This emphasis on prominence is reader-driven. Stories present information sequentially and many readers who start a story may not finish it.30 Consequently, stories that present opposing candidate assertions sequentially may not be perceived as balanced by readers who leave the story before the opponent's positions or supporters are presented. A coder reliability test was conducted on all dependent and independent variables using about 10 percent of the sample. Both percentage of agreement and Scott's Pi tests correcting for chance agreement were used. Percentage of agreement scores ranged from 95 percent to 100 percent. Scott's Pi scores ranged from .93 to 1.0. Data Analysis These data include the universe of relevant stories. Nonetheless, inferences for broader application are made, and statistical significance tests are therefore used to identify especially important findings. Study hypotheses were tested using multiple regression, in a causal model identifying influences on the two dependent variables. Independent Variable Beta weights were used to assess the relative strength and direction of influence of these variables. The Explained Variance statistic is used to assess the total influence of these independent variables on partisan and structural balance. Finally, an overarching question is whether partisan or structural bias is a better description of any bias found in the reporting. The partisan and structural balance indices used in this study will have a modest-to-strong relationship only if stories systematically favor one of the parties. That regression Beta will be positive if the Democratic Party is favored, and negative if the Republican Party is favored. A Beta at or near 0 indicates that while individual stories are imbalanced, that imbalance does not systematically favor one of the parties. RESULTS Some 175 stories were relevant for the analysis from the nine newspapers. Individual newspapers ranged from 9 to 39 stories on the studied Senate races, with a mean of 19.3 stories per newspaper. About 31 percent of stories ran on Page One, with another 43 percent running on a section front page. About 86 percent of stories were done by staff reporters, with the rest accounted for by bureau specialists or other news services. Just over 30 percent of the stories were written by women reporters. The Diversity Index for the newspapers ran from .13 to .88, with a mean of .46. On average, therefore, newspaper staffs were about half as diverse as the surrounding communities. About 47 percent of the stories covered the three open races in three states. The Partisan and Structural Balance indices indicated substantially even-handed coverage of the elections. (See Table 1) The Partisan Balance index ranged from -4 to +4, with a mean of -.29, indicating a slight bias toward Republican candidates. Nearly 46 percent of the stories ranged between -1 and +1 on the partisan index. The Structural Balance index ranged from 0 to 4, with a mean of 1.6. Only 23 percent of stories achieved imbalance scores as high as 3 or 4. Hypotheses Tests Two of the five study hypotheses were strongly supported and two were weakly supported. One was contradicted. Hypothesis One, predicting that stories with a partisan lead would be more structurally imbalanced than others, was supported. This is consistent with past research findings and with news writing conventions mandating that stories emphasize the angle established in the lead. (See Table 2) Interestingly, however, partisan leads were not systematically more likely to include Democrat assertions than Republican assertions, as indicated by the negligible .02 Beta predicting Partisan Imbalance favoring Democrats. Hypothesis Two, predicting that more prominent stories would be less structurally imbalanced than others was supported, consistent with past research. (See Table 2). But while the direction of the relationship was as predicted, its Beta was small. Moreover, stories that were more prominent were more likely to give more space and attention to Democratic assertions, although again only weakly so. Hypothesis Three, predicting that open races would be covered with less structural imbalance than other races, was contradicted. (See Table 2) In fact, stories covering open races were slightly more likely to be structurally imbalanced. Moreover, such coverage tended to give more space and attention to Republican candidates than to Democratic ones, as indicated by the negative Beta for the Partisan index. Hypothesis Four, predicting that stories by women reporters would be more imbalanced in favor of Democrats, was strongly supported. (See Table 2). Inconsistently, however, stories by women were likely to be less structurally imbalanced than others, although only weakly so. Finally, Hypothesis Five, predicting that news organizations with higher diversity scores would be more likely to give more space and attention to Democrats, was also supported, but only weakly so. (See Table 2) Such diversity was negligibly related to Structural Imbalance. Research Question A key question in this study focused on whether any news coverage imbalance was more likely due to the partisan ideology of the journalists or to factors more attributable to the news reporting process. The relationship between the Partisan and Structural Balance indices was -.05, one of the weakest relationships found in the study. In other words, although stories were frequently imbalanced structurally, that imbalance nearly as often favored Republicans as Democrats, and does not seem to reflect a systematic political bias operating though the coverage of the races studied. IMPLICATIONS Several findings emerge with implications for news coverage of the political process. Perhaps the most straightforward is that journalists already control one of the tools that influences both the balance of stories and the potential for news audiences to perceive bias. News writing conventions mandating placement of the most important or dramatic developments in story leads often result in imbalanced stories that give more attention and space to one side in an electoral contest. This emphasis does not reflect political bias on the part of journalists as much as it may the news savvy of sources who know how to capture a headline, and, of relevance to this study, the lead. Certainly journalists may take more trouble to balance leads, or even to write more neutral leads that do not yield as much control to political sources. Failure to do so may needlessly arouse perceptions of news bias attributed to political motives of journalists. A second finding, however, does not point to something so easily controlled. The gender of reporters makes a difference in the partisan balance of stories. In this study, stories written by women were more likely to give space and attention to Democrats, while stories written by men were more likely to do the same to Republicans. These are not large differences, as the much smaller effect of gender on structural balance shows. Nonetheless, it ought not to be there, and its reasons ought to be explored in newsrooms. Some other relationships may be notable, but they are smaller and less confidence must be placed in them. Newsroom diversity, taken as a measure of management political liberalism, had a small effect producing partisan imbalance favoring Democrats. However, story prominence and news organization size had somewhat stronger effects in that direction as well. Consistent with past studies, story prominence did tend to produce less structural imbalance, however. Finally, the type of race covered had mixed effects on partisan and structural balance. Open races tended to be associated with partisan imbalance giving more space and prominence to Republicans. Open races also tended to have a positive effect on structural imbalance, contrary to predictions of a negative effect. This is not consistent with previous research, and more work is needed to determine if this finding is an anomaly or whether generalizations from earlier research need to be modified. Certainly other factors must be considered. Indeed, only about 10 percent of the variation in partisan or structural imbalance could be accounted for by the factors included in the analysis. One factor, the specialty status of the reporters, shown in past research to be an influence on balance, was not a factor in this study because the overwhelming majority of stories were staff-produced. Much more needs to be learned, of course, about factors affecting news coverage of electoral conflict. An obvious next step is to determine how the partisan sources cited in these stories articulate the bias quantified in this research. For example, do partisan sources mostly extol themselves and advance their positions? Do they mostly criticize or defame their opponents? Also, how are sources other than partisans incorporated into the coverage, and how do they affect the partisan and structural balance of stories? This research also took a rigorously quantitative approach to bias measurement that limits interpretation. Standardized definitions and measures will help advance our knowledge of these influences on news bias. But so too will focused interviews with journalists, closer observation of news gathering processes, and more attention to the community and institutional contexts in which news organizations work. All these approaches should be brought to bear. The end result may be understandings that enable us to deliver news and information with less bias and better precision and context. Both the news media and the public would be better served by that result. REFERENCES 1. Pamela Shoemaker and Stephen Reese, Mediating The Message: Theories of Influence on Mass Media Content 2nd ed. (White Plains, N.Y.: Longman, 1996).
2. Only a fifth of these studies of media content explicitly dealt with how news media reported political or social conflict.
3 Jim Dearing and Everett Rogers, Agenda Setting (Thousand Oaks, CA: Sage, 1996).
4. Sei-Hill Kim, Dietram A. Scheufele, and James Shanahan, "Think About It This Way: Attribute Agenda Setting Function of the Press and the Public's Evaluation of a Local Issue," Journalism & Mass Communication Quarterly 79 (spring 2002): 7-25.
5. D. M. McLeod and B. H. Detenber, "Framing Effects of Television News Coverage of Social Protest," Journal of Communication 49 (1999): 3-23; V. Price, D. Tewksbury, and E. Powers, "Switching Trains of Thought: The Impact of News Frames on Readers' Cognitive Responses," Communication Research 34 (1997): 481-506; and C. H. de Vreese, "The Effects of Frames in Political Television News on Issue Interpretation and Frame Salience," Journalism & Mass Communication Quarterly 81 (spring 2004): 36-52.
6. Dru Evarts and Guido Stempel, "Coverage of the 1972 Campaign by TV, News Magazines and Major Newspapers," Journalism Quarterly 51 (winter 1974): 645-76.
7. C. Richard Hofstetter, Bias in the News: A Study of Network News Coverage of the 1972 Election Campaign (Columbus: Ohio State University Press, 1976).
8. James Glen Stovall, "The Third Party Challenge of 1980: News Coverage of Presidential Candidates," Journalism Quarterly 62 (summer 1985): 266-71; Games Glen Stovall, "Coverage of 1984 Presidential Campaign," Journalism Quarterly 65 (summer 1988): 443-49, 484.
9. Keith Kenny and Chris Simpson, "Was Coverage of the 1988 Presidential Race by Washington's Two Major Dailies Biased?" Journalism Quarterly 70 (summer 1993): 345-55.
10. Dennis Lowry and Jon Shidler, "The Sound Bites, the Biters and the Bitten: A Two Campaign Test of the Anti-Incumbent Bias Hypothesis in Network TV News," Journalism & Mass Communication Quarterly 75 (winter 1998): 719-29.
11. David Domke, David P. Fan, Michael Fibison, Dhavahn V. Shah, Steven S. Smith, and Mark D. Watts, "News Media, Candidates and Issues, and Public Opinion in the 1996 Presidential Campaign," Journalism & Mass Communication Quarterly 74 (winter 1997): 719-37.
12. Frederick Fico and William Cote, "Partisan and Structural Balance of News Coverage of the 1998 Governor's Race in Michigan," Mass Communication & Society 5 (spring 2002): 165-82; Frederick Fico and William Cote, "Fairness and Balance of Stories in Newspaper Coverage of the 1996 Presidential Election, Journalism & Mass Communication Quarterly 71 (spring 1999): 124-37.
13. Susan Carter, Frederick Fico, and Jocelyn McCabe, "Partisan and Structural Balance in Local Television Election Coverage," Journalism & Mass Communication Quarterly 79 (spring 2002): 41-53.
14. Frederick Fico and Eric Freedman, "Bureau, Wire Reporters Write More Balanced Stories," Newspaper Research Journal 25 (spring 2004): 44-57; Fico and Cote, "Partisan and Structural Balance of News Coverage of the 1998 Governor's Race in Michigan;" Frederick Fico, Geri Alumit Zeldes and Arvind Diddi, "Partisan and Structural Balance of Local Television Election Coverage of Incumbent and Open Gubernatorial Elections," Journalism & Mass Communication Quarterly 81 (winter 2004): 897-910.
15. Fico and Cote, "Partisan and Structural Balance in News Coverage of the 1998 Governor's Race in Michigan;" Fico and Cote, "Fairness and Balance of Stories in Newspaper Coverage of the 1996 Presidential Election."
16. Fico and Freedman, "Bureau, Wire Reporters Write More Balanced Stories."
17. Eric Freedman and Frederick Fico, "Male and Female Sources in Newspaper Coverage of Male and Female Candidates in Open Races for Governor in 2002." Forthcoming in Mass Communication & Society.
18. Geri Alumit Zeldes and Frederick Fico, "Race and Gender: An Analysis of the Sources and Reporters in the Networks' Coverage of the Year 2000 Presidential Campaign." Forthcoming in Mass Communication & Society.
19: Fico and Cote, "Partisan and Structural Balance in News Coverage of the 1998 Governor's Race in Michigan; Fico and Cote, "Fairness and Balance of Stories in Newspaper Coverage of the 1996 Presidential Election; and Fico and Freedman, "Bureau, Wire Reporters Write More Balanced Stories."
20. John D. Richardson and Karen M. Lancendorfer, "Framing Affirmative Action: The Influence of Race on Newspaper Editorial Responses to the University of Michigan Cases," Press/Politics 9 (fall 2004): 74-94.
21. Stephanie Craft and Wayne Wanta, "Women in the Newsroom: Influences of Female Editors and Reporters on the News Agenda," Journalism & Mass Communication Quarterly 81 (spring 2004): 124-138.
22. Fico and Freedman, "Bureau, Wire Reporters Write More Balanced Stories."
23. Peter Clarke and Susan Evans, Covering Campaigns (Stanford, Calif: Stanford University Press, 1983).
24. Lowry and Shidler, "The Sound Bites, the Biters and the Bitten."
25. Fico and Freedman, "Bureau, Wire Reporters Write More Balanced Stories;"
26. Fico et al., "Partisan and Structural Balance of Local Television Election
27. Coverage of Incumbent and Open Gubernatorial Elections."
26. Newspapers were: Anchorage Times, Democrat-Gazette, Los Angeles Times, Miami Herald, Atlanta Journal-Constitution, Baltimore Sun, Saint Louis Post-Dispatch, The State, and the Seattle Times.
27. Assertions were defined as sentences linked to identified sources by verbs of attribution. Such verbs included those of speaking, such as "said," "charged," "claimed," etc. Verbs denoting states of mind or feeling such as "believes," "wants," etc. were also considered to establish attribution when it was clear they were being used as synonyms for verbs of speaking.
28. Newsroom diversity was based on a survey by the ASNE. The community's diversity was assessed using U.S. Census Data. The index was developed by Dedman and Doig: B. Dedman and S.K. Doig, "Does Your Newspaper Reflect Its Community?" Paper presented at the annual meeting of the American Society of Newspaper Editors, New Orleans, LA, April, 2003. It can be accessed at http://www.asu.edu/cronkite/asne>. The diversity index of one sample newspaper was unavailable. This newspaper was given an index score equal to the mean of the others so that its other data could be used in the multivariate analysis. Tabachnick and Fidel recommend this procedure because it is conservative, lowering the correlations using the missing data variable (and therefore making it harder to support hypotheses). See, Barbara G. Tabachnick and Linda S. Fidell, Using Multivariate Statistics (New York, Harper & Row, 1983).
29. Circulation rank was used instead of raw circulation because of the great disparities among the circulations of newspapers used in the study.
30. Schramm found in a post-World War II study that between 25 and 50 percent of readers would leave a story by the sixth paragraph. Wilbur Schramm, "Measuring Another Dimension of Newspaper Readership," Journalism Quarterly 24 (1947): 293-306. Newspapers must now compete with television and the Internet, and other media. Table 1: Partisan and Structural Imbalance Index Distributions (Percent of stories with index scores.*)
Partisan Imbalance Structural Imbalance Index Index Scale Scores Most Imbalanced 4 2 4 3 7 19 2 12 31 1 11 26
Most Balanced 0 19 19
-1 15 NA -2 19 NA -3 11 NA Most Imbalanced -4 2 NA
N 175 175
*Total percents may not equal 100 due to rounding. Table 2: Influences on Partisan and Structural Imbalance in Stories (Coefficients are Betas. Betas marked with * are significant beyond the .05 level).
Influence Level And Type Partisan Imbalance Structural (Favoring Democrats) Imbalance
Societal Race Type -.12 .08
Organizational Circulation .14 -.03 Diversity Index .07 -.02
Newsroom Story Prominence .08 -.05
Individual Reporter Gender .20* -.07 Partisan Lead .02 .33*
Story Partisan Imbalance NA -.05
Equation Significance .14 .01 R-Squared .06 .12
|