The False Polarization Effect Appears in Folk Explanations of Group Attitudes

1
The False Polarization Effect Appears in Folk
Explanations of Group Attitudes Girts Dimdins1,
Henry Montgomery2, Ivars Austers3 Stanford
University1, Stockholm University2, University of
Latvia3

• Results
• The dark circles and triangles in the graphs
  represent actual mean indexes for supporter
  (circles) and opponent (triangles) participants,
  i.e., indexes calculated from own explanations.
  The white dotted circles and triangles represent
  the indexes calculated from the simulated
  explanations given from the group perspectives
• We used Mann-Whitney U-tests for pairwise
  comparisons between the actual indexes for own
  explanations, and the indexes for simulated
  explanations from group perspectives
• Means that are marked with an asterisk differed
  significantly from the corresponding actual mean
  index (p lt .05)
• The predicted pattern of false polarization
  appeared in the means of Reason/CHR index.
  Generally, each targets in-group members showed
  the strongest false polarization (in terms of
  using more CHR explanations relative to reason
  explanations) when explaining the target behavior
  from its out-group perspective
• For the Unmarked/Marked index, there was some
  evidence of false polarization, but not all mean
  differences were significant and in the expected
  direction
• Discussion
• The study demonstrated the robust nature of the
  false polarization effect. The explanations given
  from group perspectives were generally more
  extreme and simplistic than explanations provided
  from the explainers' own perspective
• From a methodological point of view, the findings
  show that the FEB coding scheme is an efficient
  and convenient tool for studies of group
  attributions
• The fact that the FEB coding categories could be
  successfully applied in a completely different
  linguistic context (i.e., Latvian) offers strong
  support to the validity of these categories and
  points to possibilities of using the FEB model in
  cross-cultural research in the future
• For questions about this study contact Girts
  Dimdins, girts_at_psych.stanford.edu

• Introduction
• The false polarization effect (FPE) is an
  overestimation of the gap between the modal views
  of two sides in a controversy or conflict
  (Pronin, Puccio, Ross, 2002)
• FPE has been documented in a variety of
  situations where participants estimated the
  opinions of other people on rating scales
  (Keltner Robinson, 1997 Monin Norton, 2003
  Robinson, Keltner, Ward, Ross, 1995)
• In this study, we wanted to test if FPE would
  appear in the choice of words and expressions
  when individuals are asked to estimate the
  opinions of other people in a free-response
  format
• We examined how supporters and opponents of
  Latvias EU membership explained the attitudes of
  their in-group and out-group members from their
  own perspective, and from other peoples
  perspective
• Conceptual Framework and Predictions
• We used the Folk Explanations of Behavior (FEB)
  model (Malle, 1999 Malle, Knobe, OLaughlin,
  Pearce, Nelson, 2000) to examine the contents
  of explanations
• Among other causal categories, the model
  distinguishes between reasons and causal history
  of reasons (CHR)
• Reason explanations depict actors as aware of
  what caused their behavior
• CHR explanations depict actors as unaware of what
  caused their behavior
• The FEB model also takes note of the use of
  mental state markers (e.g., want, think) in
  reason explanations
• More mental state markers are used when the
  explainers want to distance themselves from
  actors (Malle, 1999)
• Awareness of causes of ones behavior or
  attitudes implies rationality, a predominantly
  positive trait (Kenworthy Miller, 2002 Locke
  Pennington, 1982). We predicted that participants
  will use more reason explanations (relative to
  CHR explanations) when explaining in-group
  attitudes (and more CHR explanations for
  out-group attitudes)
• We also predicted that participants will use more
  unmarked explanations (relative to marked
  explanations) when explaining in-group attitudes
• Both patterns should be more pronounced for
  explanations given from other group members
  perspectives (because of the false polarization
  effect)

• Method
• Sixty one supporters and 23 opponents of Latvias
  EU membership participated
• The participants explained supporter and opponent
  attitudes from own perspective and either
  in-group or out-group members perspective
• Two independent judges coded the answers using
  Malles (2000) F.EX coding scheme for folk
  explanations of behavior
• We constructed a Reason/CHR index by subtracting
  the number of CHR explanations from the number of
  Reason explanations and dividing the difference
  by the total number of explanations given. A
  Marked/Unmarked index was constructed in an
  identical manner

Examples of reason and CHR explanations Reasons
They want security for themselves They think
they are going to live like in Western
countries EU membership will increase their
chances to work in other countries CHR They do
that because of their overwhelming
patriotism Those are mostly middle-aged and old
people Unable to act independently
Examples of marked and unmarked reason
explanations Unmarked Because it will harm the
agriculture To achieve a better life quality
for themselves Because it will be safer for
them Marked They think it will be safer for
Latvia They dislike globalization They want
security for themselves