Media use and the perceived justice of local science authorities

Journalism and Mass Communication Quarterly

Volumn 83, Issue 4, 2006, Pages 801-818

  Besley, John C ^a   McComas, Katherine A ^b   Waks, Leah ^c  

^a UNIVERSITY OF SOUTH CAROLINA   (United States)

^b Cornell University ^*  (United States)

^c UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MEDIA ROLE; PERCEPTION; PSYCHOLOGY;

NEW YORK COUNTY; NEW YORK [UNITED STATES]; NORTH AMERICA; UNITED STATES;

EID: 34047274819     PISSN: 10776990     EISSN: None     Source Type: Journal    
DOI: 10.1177/107769900608300405     Document Type: Article

References (94)

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43. Tyler, Rasinski, and Spodick, "Influence of Voice on Satisfaction with Leaders: Exploring the Meaning of Process-control," 72-81.
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48. Colquitt, "On the Dimensionality of Organizational Justice."
49. Thibaut and Walker, Procedural Justice,
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61. Durant, Evans, and Thomas, "Public Understanding of Science."
62. See, however: John C. Besley, Katherine A. McComas, and Craig W. Trumbo, "Exploring Media Use and Procedural Fairness Perceptions in the Context of Local Cancer Cluster Investigations" (paper presented at the annual meeting of AEJMC, San Francisco, CA, 2006).
63. Linda J. Skita and David A. Houston, "When Due Process Is of No Consequence: Moral Mandates and Presumed Guilt or Innocence," Social Justice Research 14 (September 2001): 305-26;
64. Gangl A., "Procedural Justice Theory."
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66. Frank Esser and Paul D'Angelo, "Framing the Press and the Publicity Process: A Content Analysis of Meta-coverage in Campaign 2000 Network News," American Behavioral Scientist 46 (January 2003): 617-41;
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68. For an overview, see Karen S. Johnson-Cartee, News Narratives and News Framing: Constructing Political Reality (Lanham, MD: Rowman & Littlefield Publishers, 2005).
69. Nelkin, Selling Science,
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76. Don A. Dillman, Mail and Internet Surveys: The Tailored Design Method, 2d ed. (NY: John Wiley & Sons, 2000).
77. In general, based on the significance of t-tests, respondents from the university-based community were more likely to be older, female, non-white, better educated, have a higher income, and liberal. There were no significant differences between scores on the four dependent variables. Comparing the demographic results to the U.S. Census Bureau's 2005 American Community Survey, our survey over-represented males (64% versus 48% in Tompkins County and 60% versus 50% in Ontario County), the educated (76% of our Tompkins County sample had a bachelor's degree versus a Census Bureau estimate of 53%, and 56% of our Ontario County sample had such a degree versus an Census Bureau estimate of 28%), the wealthy (median household income fell in the $50-74,999 range in both counties but is reported by the Census Bureau as $43,306 in Tompkins County and $47,242 in Ontario County). It also over-represents white respondents in Tompkins County (91% versus 83% actual).
78. Colquitt, "On the Dimensionality of Organizational Justice";
79. Jason A. Colquitt and John C. Shaw, "How Should Organizational Justice Be Measured?" in Handbook of Organizational Justice, ed. Greenberg and Colquitt, 113-52.
80. An exploratory factor analysis using oblique rotation was consistent with Colquitt's conclusions regarding the dimensionality of justice, though achieving a four-factor solution required setting the acceptable default eigenvalue to .95, rather than 1. Leaving the eigenvalue set to 1 results in a three-factor solution that seems to combine the procedural and informational justice factors. As the literature cited above notes, the ' emergence of arguments for the uniqueness of an informational justice has occurred relatively recently. We chose to follow Colquitt's lead with regard to the dimensionality issue because it remains the most comprehensive research on the topic. Moving forward, however, communication researchers clearly have an interest in assessing whether informational justice indeed constitutes a unique component of fairness. The correlation between distributional and procedural justice is the lowest of the possible correlations (r = .31, p < .00) while the relationship between procedural and informational justice is the highest (r = .48, p < .00). The correlations between procedural and interpersonal justice (r = .34, p < .00), distributive and interpersonal justice (r = .44, p < .00), distributive and informational justice (r = .45, p < .00), and interpersonal and informational justice (r = .44, p < .00) all lie within this range. A model where the dependent variable includes the combined measures for procedural and informational justice (Cronbach's α of .74) shows a pattern of relationships nearly identical to the procedural justice model presented here.
81. National Science Board, Science and Engineering Indicators.
82. In future analyses, we also expect that community attachment will interact with justice perceptions to predict outcomes of fairness perceptions such as satisfaction with authorities and willingness to cooperate with authorities (see Tom R. Tyler, Peter Degoey, and Heather J. Smith, "Understanding Why the Justice of Group Procedures Matters: A Test of the Psychological Dynamics of the Group-value Model," Journal of Personality and Social Psychology 70 (May 1996): 913-30). It is, therefore, important to include it here for possible comparisons with future projects.
83. Rasinski, "Economic Justice";
84. Rasinski and Tyler, "Fairness and Vote Choice";
85. Boeckman and Tyler, "Trust, Respect, and the Psychology of Political Engagement."
86. James Shanahan, and Michael Morgan, Television and Its Viewers: Cultivation Theory and Research (New York, NY: Cambridge University Press, 1999).
87. Not all of the attention variables included on the survey appear here. Initial analyses included an exposure measure for listening to "news or talk radio," non-news Internet exposure, as well as several entertainment television and radio attention measures, including attention to comedy sitcoms, reality television, light television drama (e.g., the Gilmore Girls), action dramas (e.g., ER), conservative talk radio (e.g., Rush Limbaugh and Dr. Laura Schlessinger), and progressive talk radio (e.g., NPR and Air America). While previous research has found a relationship between entertainment media use and views about the benefits of science (see Matthew C. Nisbet, Dietram A. Scheufele, James Shanahan, Patricia Moy, Dominique Brossard, and Bruce V. Lewenstein, "Knowledge, Reservations, or Promise? A Media Effects Model for Public Perceptions of Science and Technology," Communication Research 29 [October 2002]: 584-608), these variables were dropped in the preliminary analyses because they consistently had no relationship with the dependent variables. Doing so should also help to limit any problems with multicollinearity.
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92. John Rawls, A Theory of Justice (Cambridge, MA: Harvard University Press, 1971);
93. John Rawls, Justice as Fairness: A Restatement (Cambridge, MA: Harvard University Press, 2001).
94. Tyler et al., Social Justice in a Diverse Society.