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An Experimental Evaluation of Readers' Perceptions of Media Bias
Unformatted Document Text:  Media Bias - 12 The L.S.D. calculations yielded a critical t of 2.80; that is, in order to protect against capitalization on chance, we need to detect t’s of 2.80 between group means (rather than the critical t of 1.64 from the standard Student’s t test). We found two significant differences among the six cells: participants who were not cued and read the article about parking were significantly more likely to say their article was free of bias than those who were cued and read the article about President Bush (t = 4.64), or those who were not cued and read the housing article (t = 3.47). The cued/Bush cell was the cell which contained the fewest persons saying the article was free of bias; this and the cued-status by topic interaction indicate an interdependence between a topic and thinking about media coverage of the topic that goes beyond the scope of this study. Finally, there was a significant main effect for topic, as expected (E2). Basically, participants thought the articles about parking were freer from bias than those about President Bush or housing (the latter did not differ significantly using Fisher’s L.S.D.). Social Judgment-based expectations To test our expectation that participants would be more likely to select statements opposing their own viewpoints as biased, we constructed a dummy variable indicating our expectation of whether the participant would be for or against the topic of the story that they had to read. For the housing stories, students living on campus were assumed to be "pro" and students living off campus "con." Similarly, for the parking issue, students with cars at school were designated "pro." For the Bush article, we scored participants as "pro" if they reported more frequently voting for Republicans and "con" if Democrats. Student who said they voted for both parties about equally were described as "pro" if they self- described as conservative and "con" if liberal. The 15 participants who voted equally across parties and described themselves as moderate were omitted. As the dependent variable, we counted the number of "pro" paragraphs (either summaries or quotations) each person had designated as biased and subtracted the number of "con" paragraphs marked. The three neutral paragraphs were not included, marked or not. This created a measure where indicating that "pro" statements were biased yielded a positive score and "con" a negative score. Students who were assumed to be "pro" on an issues were more likely to mark "con" paragraphs as biased and vice versa. "Pro" participants had a mean score of -.057 and "con" participants +.066. This difference was statistically significant (t(130) = 2.12, p < .05); this result is as expected (E3).

Authors: D'Alessio, Dave.
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Media Bias - 12
The L.S.D. calculations yielded a critical t of 2.80; that is, in order to protect against capitalization on chance,
we need to detect t’s of 2.80 between group means (rather than the critical t of 1.64 from the standard Student’s t test).
We found two significant differences among the six cells: participants who were not cued and read the article about
parking were significantly more likely to say their article was free of bias than those who were cued and read the article
about President Bush (t = 4.64), or those who were not cued and read the housing article (t = 3.47). The cued/Bush cell
was the cell which contained the fewest persons saying the article was free of bias; this and the cued-status by topic
interaction indicate an interdependence between a topic and thinking about media coverage of the topic that goes
beyond the scope of this study.
Finally, there was a significant main effect for topic, as expected (E2). Basically, participants thought the
articles about parking were freer from bias than those about President Bush or housing (the latter did not differ
significantly using Fisher’s L.S.D.).
Social Judgment-based expectations
To test our expectation that participants would be more likely to select statements opposing their own
viewpoints as biased, we constructed a dummy variable indicating our expectation of whether the participant would be
for or against the topic of the story that they had to read. For the housing stories, students living on campus were
assumed to be "pro" and students living off campus "con." Similarly, for the parking issue, students with cars at school
were designated "pro."
For the Bush article, we scored participants as "pro" if they reported more frequently voting for Republicans
and "con" if Democrats. Student who said they voted for both parties about equally were described as "pro" if they self-
described as conservative and "con" if liberal. The 15 participants who voted equally across parties and described
themselves as moderate were omitted.
As the dependent variable, we counted the number of "pro" paragraphs (either summaries or quotations) each
person had designated as biased and subtracted the number of "con" paragraphs marked. The three neutral paragraphs
were not included, marked or not. This created a measure where indicating that "pro" statements were biased yielded a
positive score and "con" a negative score.
Students who were assumed to be "pro" on an issues were more likely to mark "con" paragraphs as biased and
vice versa. "Pro" participants had a mean score of -.057 and "con" participants +.066. This difference was statistically
significant (t(130) = 2.12, p < .05); this result is as expected (E3).


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