Top scores are possible, bottom scores are certain (and middle scores are not worth mentioning): A pragmatic view of verbal probabilities

In most previous studies of verbal probabilities, participants are asked to translate expressions such as possible and not certain into numeric probability values. This probabilistic translation approach can be contrasted with a novel which-outcome (WO) approach that focuses on the outcomes that people naturally associate with probability terms. The WO approach has revealed that, when given bell-shaped distributions of quantitative outcomes, people tend to associate certainty with minimum (unlikely) outcome magnitudes and possibility with (unlikely) maximal ones. The purpose of the present paper is to test the factors that foster these effects and the conditions in which they apply. Experiment 1 showed that the association of probability term and outcome was related to the association of scalar modifiers (i.e., it is certain that the battery will last at least..., it is possible that the battery will last up to...). Further, we tested whether this pattern was dependent on the frequency (e.g., increasing vs. decreasing distribution) or the nature of the outcomes presented (i.e., categorical vs. continuous). Results showed that despite being slightly affected by the shape of the distribution, participants continue to prefer to associate possible with maximum outcomes and certain with minimum outcomes. The final experiment provided a boundary condition to the effect, showing that it applies to verbal but not numerical probabilities.

[1]  Marie Juanchich,et al.  Verbal Probabilities: An Alternative Approach , 2014, Quarterly journal of experimental psychology.

[2]  Marie Juanchich,et al.  Improbable outcomes: Infrequent or extraordinary? , 2013, Cognition.

[3]  Karl Halvor Teigen,et al.  Can > Will: Predictions of What Can Happen are Extreme, but Believed to be Probable , 2013 .

[4]  Marie Juanchich,et al.  To what extent do politeness expectations shape risk perception? Even numerical probabilities are under their spell! , 2012, Acta psychologica.

[5]  C. Butler,et al.  The perceived functions of linguistic risk quantifiers and their effect on risk, negativity perception and decision making , 2012 .

[6]  S. Broomell,et al.  Effective communication of uncertainty in the IPCC reports , 2012, Climatic Change.

[7]  Adam J. L. Harris,et al.  Communicating environmental risks: Clarifying the severity effect in interpretations of verbal probability expressions. , 2011, Journal of experimental psychology. Learning, memory, and cognition.

[8]  S. Beck,et al.  Overcoming the framing effect when making decisions based on verbal probabilities: Having more time is helpful but not enough , 2011 .

[9]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[10]  David V. Budescu,et al.  Improving Communication of Uncertainty in the Reports of the Intergovernmental Panel on Climate Change , 2009, Psychological science.

[11]  B. Geurts,et al.  At least et al: The semantic of scalar modifiers , 2007 .

[12]  Kimihiko Yamagishi,et al.  Directional verbal probabilities: inconsistencies between preferential judgments and numerical meanings. , 2006, Experimental psychology.

[13]  Craig R. M. McKenzie,et al.  Information leakage from logically equivalent frames , 2006, Cognition.

[14]  Jean-François Bonnefon,et al.  Tactful or Doubtful? , 2006, Psychological science.

[15]  Mandeep K. Dhami,et al.  Interpersonal comparison of subjective probabilities: Toward translating linguistic probabilities , 2005, Memory & cognition.

[16]  Gary L. Wells,et al.  Measuring Psychological Uncertainty : Verbal Versus Numeric Methods , 2004 .

[17]  David V. Budescu,et al.  Predicting the directionality of probability words from their membership functions , 2003 .

[18]  Michael Theil,et al.  The role of translations of verbal into numerical probability expressions in risk management: a meta-analysis , 2002 .

[19]  David R. Mandel,et al.  Gain-Loss Framing and Choice: Separating Outcome Formulations from Descriptor Formulations. , 2001, Organizational behavior and human decision processes.

[20]  N. Schwarz Self-reports: How the questions shape the answers. , 1999 .

[21]  J. Shanteau,et al.  An information processing view of framing effects: The role of causal schemas in decision making , 1996, Memory & cognition.

[22]  Wibecke Brun,et al.  Yes, but it is uncertain: Direction and communicative intention of verbal probabilistic terms , 1995 .

[23]  D. Budescu,et al.  Processing Linguistic Probabilities: General Principles and Empirical Evidence , 1995 .

[24]  Rami Zwick,et al.  Comparing the calibration and coherence of numerical and verbal probability judgments , 1993 .

[25]  Valerie A. Clarke,et al.  Ratings of Orally Presented Verbal Expressions of Probability by a Heterogeneous Sample , 1992 .

[26]  M. Lynn Scarcity effects on value: A quantitative review of the commodity theory literature , 1991 .

[27]  Peter H. Ditto,et al.  From rarity to evaluative extremity: effects of prevalence information on evaluations of positive and negative characteristics. , 1989, Journal of personality and social psychology.

[28]  Karl Halvor Teigen,et al.  The language of uncertainty , 1988 .

[29]  Wibecke Brun,et al.  Verbal probabilities: Ambiguous, context-dependent, or both? , 1988 .

[30]  V F Reyna,et al.  The language of possibility and probability: Effects of negation on meaning , 1981, Memory & cognition.

[31]  Susan T. Fiske,et al.  Attention and weight in person perception: The impact of negative and extreme behavior. , 1980 .