Risk it? Direct and collateral impacts of peers' verbal expressions about hazard likelihoods*

When people encounter potential hazards, their expectations and behaviours can be shaped by a variety of factors including other people's expressions of verbal likelihood (e.g., unlikely to harm). What is the impact of such expressions when a person also has numeric likelihood estimates from the same source(s)? Two studies used a new task involving an abstract virtual environment in which people learned about and reacted to novel hazards. Verbal expressions attributed to peers influenced participants’ behaviour toward hazards even when numeric estimates were also available. Namely, verbal expressions suggesting that the likelihood of harm from a hazard is low (vs. higher) yielded more risk taking with respect to said hazard. There were also inverse collateral effects, whereby participants’ behaviour and estimates regarding another hazard in the same context were affected in the opposite direction. These effects may be based on directionality and relativity cues inferred from verbal likelihood expressions.     

Motivated reasoning and verbal vs. numerical probability assessment: Evidence from an accounting context

A perplexing yet persistent empirical finding is that individuals assess probabilities in words and in numbers nearly equivalently, and theorists have called for future research to search for factors that cause differences. This study uses an accounting context in which individuals are commonly motivated to reach preferred (rather than accurate) conclusions. Within this context, I predict new differences between verbal and numerical probability assessments, as follows: first, individuals will justify an optimistic verbal assessment (e.g., somewhat possible) by retaining the option of re-defining it, in case of negative outcomes, as though the phrase really means something different, and, for that matter, means more things. This re-definition will maintain some connection to the original meaning of the phrase, but de-emphasized relative to the new meaning. Second, based on this behavior, I also predict individuals’ verbal probability assessments to be (1) more biased and yet (2) perceived as more justifiable than their numerical assessments. I find supportive evidence in an experiment designed to test the hypotheses. This study contributes to motivated reasoning and probability assessment theories (1) with new evidence of how individuals can word-smith in multiple attributes of a phrase to justify reaching a preferred conclusion, and (2) with new, reliable differences between verbal and numerical probability assessments. This study has important theoretical and practical implications relevant to organizational contexts in which people assess the likelihoods of uncertainties in words or numbers, and with motivations to reach a preferred conclusion.     

Predicting the directionality of probability words from their membership functions

Teigen and Brun have suggested that distinct from their numerical implications, most probability phrases are either positive or negative, in that they encourage one to think of reasons why the target event will or will not occur. We report two experiments testing our hypotheses that (a) the direction of a phrase can be predicted from properties of its membership function, and (b) this relation is invariant across contexts, and (c) —originally formulated by Teigen and Brun (1999)—that strong modifiers intensify phrase directionality. For each phrase, participants encoded membership functions by judging the degree to which it described the numerical probabilities 0.0, 0.1, …, 1.0, and also completed sentences including the target phrase. The types of reasons given in the sentence completion task were used to determine the phrase's directionality. The results support our hypotheses (a) and (b) regarding the relation between directionality and the membership functions, but we found only limited support for hypothesis (c) regarding the effects of modifiers on directionality. A secondary goal, to validate an efficient method of encoding membership functions, was also achieved. Copyright © 2003 John Wiley & Sons, Ltd.     

Precursor behavior and functional analysis: A brief review

Researchers have developed precursor functional analyses to provide an alternative, and presumably safer, format for functional analysis of severe problem behavior. When researchers use functional analysis contingencies for precursor behaviors, it is possible to infer functional characteristics about severe problem behaviors based on patterns of less severe precursor behaviors, permitting practitioners to complete the assessment with less risk to clients, practitioners, or others. The current paper discusses recent advances in the development and validation of precursor identification, and offers suggestions and future directions for investigating and implementing precursor functional analyses. We propose a decision‐making model, in which practitioners integrate procedures to identify precursors into the functional‐analysis process, to expedite the analysis of severe problem behaviors.     

Taurek, Numbers and Probabilities

In his paper, “Should the Numbers Count?" John Taurek imagines that we are in a position such that we can either save a group of five people, or we can save one individual, David. We cannot save David and the five. This is because they each require a life-saving drug. However, David needs all of the drug if he is to survive, while the other five need only a fifth each. Typically, people have argued as if there was a choice to be made: either numbers matter, in which case we should save the greater number, or numbers don't matter, but rather there is moral value in giving each person an equal chance of survival, and therefore we should toss a coin. My claim is that we do not have to make a choice in this way. Rather, numbers do matter, but it doesn't follow that we should always save the greater number. And likewise, there is moral value in giving each person an equal chance of survival, but it doesn't follow that we should always toss a coin. In addition, I argue that a similar approach can be applied to situations in which we can save one person or another, but the chances of success are different.     

Prior probabilities and representational momentum

In many previous experiments on representational momentum (in which memory for the final location of a moving target is displaced in the direction of target motion), participants judged whether a probe presented after a target vanished was at the same location where that target vanished or at a different location. The experiments reported here manipulated the actual or expected prior probability a same response to such a probe would be correct. In Experiment 1, a same response was correct on 10%, 30%, 50%, 70%, or 90% of the trials, but observers were not instructed regarding these probabilities. In Experiment 2, a same response was correct on 11% of the trials, but different groups of participants were instructed that a same response would be correct on 10%, 30%, 50%, 70%, or 90% of the trials. Probabilities of a same response to different probe positions, weighted mean estimates of representational momentum, hit rates and false alarm rates, and d′ and ß are reported. Representational momentum occurred in all conditions but was not influenced by actual or expected prior probability a same response would be correct. The data suggest representational momentum does not result from changes in sensitivity, and a distinction between performance bias and competence bias is introduced.