The "identifiable victim effect" refers to the tendency of individuals to offer greater aid when a specific, identifiable person ("victim") is observed under hardship, as compared to a large, vaguely defined group with the same need. The effect is also observed when subjects administer punishment rather than reward. Participants in a study were more likely to mete out punishment, even at their own expense, when they were punishing specific, identifiable individuals ("perpetrators").
Contents
- Origin
- Ex post vs ex ante evaluation
- Vividness
- Certainty effect risk seeking for losses and loss aversion
- Response to the relative size of the reference group
- Aiding
- Punishment
- Criticism
- References
Vivid, flesh and blood-victims are often more powerful sources of persuasion than are abstract statistics (Collins et al. 1988). For example, Ryan White contracted HIV at age 13 and struggled with the disease until succumbing some six years later. Following his death, the US congress passed the Ryan White Care Act, which funded the largest set of services for people living with the AIDS in the country.
The effect is epitomized by the phrase (commonly attributed to Joseph Stalin), "A single death is a tragedy; a million deaths is a statistic."
Origin
The conceptualization of the identifiable victim effect as it is known today is commonly attributed to Thomas Schelling. He wrote that harm to a particular person invokes “anxiety and sentiment, guilt and awe, responsibility and religion, [but]…most of this awesomeness disappears when we deal with statistical death (Schelling 1968)”.
Ex post vs ex ante evaluation
The decision to save an identifiable victim is made ex post meaning it is done after the victim is in danger. In contrast, the decision to save a statistical victim is made ex ante meaning it is done as a pre-emptive measure to prevent the individual from being in danger (Weinstein, Shepard & Pliskin 1980). When people consider the risks of not helping a victim, they consider the probability of being responsible and blamed (Douglas 2013). This is much greater with identifiable victims than with statistical victims because one cannot accurately predict the likelihood of a tragedy occurring in the future and thus cannot be held responsible for tragedies that might occur in the future (Jenni & Loewenstein 1997).
This explanation is closest to what Thomas Schelling implied in his now-famous paper.
Vividness
Identifiable victims, as their name suggests, have features that make them identifiable. Details about their predicament, family background, educational history, etc, are shared through the media and brought to public attention. The stories are emotional with victims portrayed as innocent and helpless. Images and videos of the victim are shared, and the victim’s predicament is followed in real-time (Jenni & Loewenstein 1997). Studies have previously indicated that people respond more to concrete, graphic information than abstract, statistical information (Nisbett & Ross 1980). Therefore, identifiable victims elicit greater reactions from people than statistical victims do.
Certainty effect, risk-seeking for losses and loss aversion
The certainty effect and risk seeking for losses reinforce each other. The certainty effect is the inclination to place disproportionately greater weighting to certain outcomes than to uncertain but likely outcomes (Kahneman & Tversky 1979). The consequences to identifiable victims are viewed as certain to occur whereas the consequences to statistical victims are viewed as probabilistic (Jenni & Loewenstein 1997). Research has also shown the tendency of people to be risk-seeking for losses (Kahneman & Tversky 1986). A certain loss is viewed more negatively than an uncertain loss with the same expected value. Closely related to this is people tend to be loss averse (Kahneman & Tversky 1979). They view saving a statistical life as a gain whereas saving an identifiable victim is seen as avoiding a loss. Together, these effects result in people being more likely to aid identifiable, certain victims than statistical, uncertain victims.
Response to the relative size of the reference group
Risk that is concentrated is perceived as greater than the same risk dispersed over a wider population. Identifiable victims are their own reference group; if they do not receive aid then the entire reference group is regarded to perish (Jenni & Loewenstein 1997).To illustrate this point, consider an explosion at an offshore oil rig where 50 people work. Suppose all 50 people die in the explosion, this represents 50 of the thousands of people working on offshore oil rigs. Yet, the reference group is not the thousands of people working on offshore oil rigs but rather the 50 people working on that particular offshore oil rig. Therefore, this is perceived as 50 of 50 people certain to die so by aiding them, a significant proportion of the reference group can be saved.
People’s response to the proportion of the reference group that can be saved is such a significant contributor to the identifiable victim effect that this effect could be re-labelled as the “percentage of reference group saved effect” (Jenni & Loewenstein 1997).
Aiding
The most definitive implication of the identifiable victim effect is identifiable victims are more likely to be helped than statistical victims (Small & Loewenstein 2003).
An incident that frequently features in literature is the aid given to Jessica McClure and her family (Loewenstein, Small & Strnad 2005). On October 14, 1987, 18-month old Jessica McClure fell into a narrow well in her aunt’s home cum day-care centre in Midland, Texas (Loewenstein, Small & Strnad 2005). Within hours, ‘Baby Jessica’, as she became known, made headlines around the US. The public reacted with sympathy towards her ordeal. While teams of rescue workers, paramedics and volunteers worked to successfully rescue ‘Baby Jessica’ in 58 hours, a total of $700,000 was amassed in that time. Even after being discharged from hospital, the McClure family were flooded with cards and gifts from members of the public as well as a visit from then-Vice President George H.W. Bush and a telephone call from then-President Ronald Reagan.
Punishment
The identifiable victim effect is suggested to be a specific case of a more general ‘identifiable other effect’ (Loewenstein, Small & Strnad 2005). As such, it also has an effect on punishments. People prefer to punish identified transgressors than unidentified transgressors when given a choice between the two. People also exert more severe punishments on identified than unidentified transgressors (Small & Loewenstein 2005).
Typically in crime investigations, law enforcement forces conceal any information regarding the identities of the suspects until they have strong evidence that the suspects are credible. When identities of suspects are revealed through description of their features or release of their images, media coverage and public discussion on the issue grows. The public discourse generally becomes increasingly negative and hostile because people experience a greater emotional reaction towards a concrete, identifiable perpetrator than an abstract, unidentifiable one.
Criticism
The identifiable victim effect has been contested in academia. Critics argue that when a victim is identified information such as age and gender of the victim are revealed and people are especially sympathetic in response to that information rather than to identifiability per se (Small & Loewenstein 2003).
In 2003, Deborah Small and George Loewenstein conducted an experiment that mitigated this issue. Identifiability was strictly limited to the determination of the victim's identity (Small & Loewenstein 2003). Therefore, the victim has already been identified regardless of whether the participants know anything specific about their identity or not. The circumstances of the victim were more palpable and thus elicit greater sympathy from participants. In contrast, the identities of statistical victims were not yet determined. As such, participants found it more difficult to sympathise with indeterminate victims.