Suchergebnisse

The modern field of study into hindsight bias was launched by Baruch Fischhoff. Fischhoff provided his research subjects with a primer on the 1810s conflict between British forces and Nepalese Gurkhas near Northern India. He suggested four possible outcomes: British victory, Gurkha victory, a peace settlement, and a military stalemate with no peace settlement. The subjects were then divided into five groups. One group was given no information about the ultimate outcome of the conflict. Subjects in each of the remaining four groups were told that one of the four outcomes had, in fact, occurred. The subjects were then asked to assess the probability of each of the outcomes at the time that the conflict began. On average, the members of each group thought that the outcome that they had been told occurred was the most likely outcome a priori, even though they had been instructed to ignore what they "knew" about the ultimate outcome. Fischhoff referred to this phenomenon as "creeping determinism": the effect that being told "an outcome's occurrence consistently increases its perceived likelihood" before the fact. Subsequent studies confirmed his earlier results. Fischhoff's studies effectively created the field of research on hindsight bias.

"Hindsight Bias in Political Decision Making" published on by Oxford University Press.

This investigation explored hindsight bias in college students' perceptions of sexual assault. Participants read a vignette about a man and woman who met at a party with the conditions varied across the vignettes: the alcohol use of the characters, the outcome of the vignette, and in the rape outcome, the victim's actions after the assault. Hindsight bias was assessed using both the posttest-only method and the pretest/posttest method and for both the outcome of the vignette and post-outcome events. Results revealed significant evidence for the existence of hindsight bias with the pretest/posttest method. Additionally, results revealed some evidence for hindsight bias contamination in perceptions of vignette characters, but in ways contrary to those predicted by the Defensive Attribution Hypothesis (Shaver, 1970).

Although hindsight bias is a very specific and narrow field of interest, there seems to be conflicting ideologies, results, and theories. Of particular interest for this paper is hindsight bias in regards to the 2016 Presidential Elections. I propose to analyze data collected on an ongoing study by Dr. Mark Pezzo in the Social Judgement Lab. The study asks participants, both before and after, the presidential election to indicate their: political party, preference of candidate, likelihood that the candidate, Donald Trump, would win, estimated percentage of vote that each candidate would receive, and demographic information for research purposes. After the preelection data, has been collected, another data collection will occur gaining information on participants' emotional response to the outcome of the election, the degree the outcome "makes sense" to the participant, and three questions that will effectively capture foreseeability. Normally hindsight bias would be predicted for all study participants, but due to the level of surprise the election outcome created, it is predicted that it may be difficult for people to make sense of it, therefore participants may show little hindsight bias, or may even show reverse hindsight bias. Hindsight bias, reverse bias, retroactive pessimism, cognitive mechanism, sensemaking, and exploratory analyses will all be investigated into detail.

Although hindsight bias is a very specific and narrow field of interest, there seems to be conflicting ideologies, results, and theories. Of particular interest for this paper is hindsight bias in regards to the 2016 Presidential Elections. I propose to analyze data collected on an ongoing study by Dr. Mark Pezzo in the Social Judgement Lab. The study asks participants, both before and after, the presidential election to indicate their: political party, preference of candidate, likelihood that the candidate, Donald Trump, would win, estimated percentage of vote that each candidate would receive, and demographic information for research purposes. After the preelection data, has been collected, another data collection will occur gaining information on participants' emotional response to the outcome of the election, the degree the outcome "makes sense" to the participant, and three questions that will effectively capture foreseeability. Normally hindsight bias would be predicted for all study participants, but due to the level of surprise the election outcome created, it is predicted that it may be difficult for people to make sense of it, therefore participants may show little hindsight bias, or may even show reverse hindsight bias. Hindsight bias, reverse bias, retroactive pessimism, cognitive mechanism, sensemaking, and exploratory analyses will all be investigated into detail.

Although hindsight bias is a very specific and narrow field of interest, there seems to be conflicting ideologies, results, and theories. Of particular interest for this paper is hindsight bias in regards to the 2016 Presidential Elections. I propose to analyze data collected on an ongoing study by Dr. Mark Pezzo in the Social Judgement Lab. The study asks participants, both before and after, the presidential election to indicate their: political party, preference of candidate, likelihood that the candidate, Donald Trump, would win, estimated percentage of vote that each candidate would receive, and demographic information for research purposes. After the preelection data, has been collected, another data collection will occur gaining information on participants' emotional response to the outcome of the election, the degree the outcome "makes sense" to the participant, and three questions that will effectively capture foreseeability. Normally hindsight bias would be predicted for all study participants, but due to the level of surprise the election outcome created, it is predicted that it may be difficult for people to make sense of it, therefore participants may show little hindsight bias, or may even show reverse hindsight bias. Hindsight bias, reverse bias, retroactive pessimism, cognitive mechanism, sensemaking, and exploratory analyses will all be investigated into detail.

Expert surveys provide a standardized way to access and synthesize specialized knowledge, thereby, enabling the analysis of a diverse range of concepts and contexts that might otherwise be difficult to approach systematically. However, while studies of public opinion have long argued that cognitive biases represent potential problems when it comes to the general population, less attention has been paid to similar issues among expert respondents. This study examines one form of cognitive bias, hindsight bias. Hindsight bias refers to the tendency to retrospectively exaggerate one's foresight of a particular event. We argue that hindsight bias is a potential problem when it comes to retrospective evaluation due to the difficulty involved in separating our assessments of the pre-crisis period from the knowledge that a crisis occurred. Using disaggregated data from the Varieties of Democracy Project, we look for evidence of hindsight bias in coders' evaluations of the periods that preceded major crises of democracy. We find that coder disagreement is significantly higher in pre-crisis scenarios than in our control group. Concerningly, despite this disagreement, coders remain similarly confident in their assessments. This represents a potential problem for those who seek to use these data to study democratic breakdowns and transitions.

This article reports on the relationship between outcome knowledge regarding an environmental event and self-reported fear of future illness. A sample of 95 subjects in three conditions showed that outcome knowledge increases post event likelihood estimations, thus indicating a hindsight bias. Subjects' perceived likelihood of increases in disease rate is shown to substantially predict subjects' level of fear of future illness for both cancer and no cancer disease. Demographic variables of gender, political ideology, and attitude toward environmental activism were shown to have mixed results in predicting fear of future illness. Positive attitude toward environmental activism modesty predicted fear of cancer but not fear of noncancer disease. Political ideology failed to significantly predict fear of future illness, although it showed a trend toward significance for predicting fear of cancer. Gender significantly predicted fear of noncancer disease but not fear of cancer, with females indicating more fear than males. The implications of the accuracy of outcome information following ambiguous and uncertain events on the genesis and exacerbation of fear of future illness is discussed.