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Identifiable victim effect

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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.[1] The effect is also observed when subjects administer punishment rather than reward. Research has shown that individuals can be more likely to mete out punishment, even at their own expense, when they are punishing specific, identifiable individuals ("perpetrators").[2]

Concrete images and representations are often more powerful sources of persuasion than are abstract statistics.[3] 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.[4]

The effect is epitomized by the phrase (commonly attributed to Joseph Stalin) "A single death is a tragedy; a million deaths is a statistic."[5]

Origin

The conceptualization of the identifiable victim effect as it is known today is commonly attributed to American economist 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”.[6]

Explanations

Jenni and Loewenstein (1997)[1] proposed four explanations for the identifiable victim effect: ex post versus ex ante evaluation, vividness, certainty versus uncertainty, and the proportion of the reference group at risk. These explanations are described in more detail below.

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 often made ex ante, as a pre-emptive measure to prevent the individual from being in danger.[7] When people consider the risks of not helping a victim, they consider the probability of being responsible and blamed.[8] This probability 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. This explanation is closest to what Thomas Schelling implied in his now-famous paper.

Jenni and Loewenstein (1997)[1] did not find evidence that ex post vs ex ante evaluation contributes to the identifiable victim effect, but Small and Lowenstein (2003)[9] did.

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 often portrayed as innocent and helpless. For example, Perrault et al.[10] tested an identifiable human victim message, in relation to an identifiable animal victim (i.e., a squirrel) using the context of the consequences of littering, and found the identifiable animal message - an innocent and helpless creature - elicited greater levels of distress and empathy than the identifiable human message. Images and videos of the victim are often shared, and the public is able to follow the victim's predicament in real-time. Studies have previously indicated that people respond more to concrete, graphic information than abstract, statistical information.[11] The vividness of identifiable victims creates a sense of familiarity and social closeness (opposite of social distance). Therefore, identifiable victims elicit greater reactions from people than statistical victims.

Bohnet and Frey (1999)[12] and Kogut and Ritov (2005)[13] found that vividness contributes to the identifiable victim effect. Another study by Kogut and Ritov (2005)[14] found that donations to benefit a needy child increased when the name and a picture of the child were provided. Jenni and Loewenstein (1997)[1] did not observe an effect of vividness.

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.[15] The consequences to identifiable victims are viewed as certain to occur whereas the consequences to statistical victims are viewed as probabilistic.[1] Research has also shown the tendency of people to be risk-seeking for losses.[16] A certain loss is viewed more negatively than an uncertain loss with the same expected value. Closely related to this is people's tendency to be loss averse.[15] 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.

In one of Jenni and Loewenstein's[1] two experiments, their subjects were significantly more concerned about certain than uncertain deaths.

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.[1] 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.

Jenni and Loewenstein's[1] experimental subjects showed significantly more support for risk-reducing actions when a higher proportion of the reference group was at risk. This effect was so striking that Jenni and Loewenstein suggested that the identifiable victim effect could instead be called the “percentage of reference group saved effect”.

Implications and examples

Aiding

One implication of the identifiable victim effect is identifiable victims are more likely to be helped than statistical victims.[17]

An incident that frequently features in literature is the aid given to Jessica McClure and her family.[18] On October 14, 1987, 18-month old Jessica McClure fell into a narrow well in her aunt's home day-care centre in Midland, Texas.[18] 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.[19]

The identifiable victim effect also engenders sympathy for those beyond help.

In September, 2015, three-year-old Syrian refugee Alan (or Aylan) Kurdi drowned when he and his family tried to reach Europe by boat. A photograph of Kurdi's body caused a dramatic upturn in international concern over the refugee crisis. The picture has been credited with causing a surge in donations to charities helping migrants and refugees, with one charity, the Migrant Offshore Aid Station, recording a 15-fold increase in donations within 24 hours of its publication.[20][21]

The murder of George Floyd by a police officer in May, 2020 led to worldwide protests against police brutality.[22][23] Almost 1,000 people are killed in the U.S. by police every year,[24] and a black male is 2.5 times as likely to be killed by police as a white male,[25] but these statistics do not inspire similar outrage.[26]

Punishment

The identifiable victim effect is suggested to be a specific case of a more general 'identifiable other effect'.[18] As such, it also has an effect on punishments. People prefer to punish identified transgressors rather than unidentified transgressors when given a choice between the two. People also exert more severe punishments on identified than unidentified transgressors.[2]

Individuals are also more likely to assign blame to an identified transgressor if they feel they have been wronged. There is also an increased desire for harsh punishments that persists even when self-sacrifice is required in order to punish the transgressor. This effect can possibly be explained by the increased anger felt towards an identified rather than an unidentified transgressor. This supports the theory of “vividness” as a source of the identifiable victim effect (Small & Loewenstein, 2005).[2]

Public policy

Healthcare

The identifiable victim effect may also influence healthcare, both at the individual and national level (Redelmeir & Tversky, 1990).[27] On the individual level, doctors are more likely to recommend expensive, but potentially life-saving, treatments to an individual patient rather than to a group of patients. This effect is not limited to medical professionals, as laymen demonstrate this same bias towards providing more expensive treatments for individual patients (Redelmeir & Tversky, 1990).[27] On the national level, the American people are far more likely to contribute to an expensive treatment to save the life of one person rather than spend much smaller amounts on preventative measures that could save the lives of thousands per year. A function of American individualism, this nationwide bias towards expensive treatments is still prevalent today (Toufexis & Bjerklie, 1993).[28]

Ryan White Care Act

The need to tackle the problems faced by AIDS sufferers was brought to the political forefront as a result of the legal and social plight of one particular AIDS victim, Ryan White. His circumstances and campaign for greater funding for AIDS research were widely publicised in the media which culminated in legislation being passed to provide financial support to AIDS sufferers and their families in 1990 shortly after White's death.[4]

Criminal justice

Since the identifiable victim effect can influence punishment, it has the potential to undermine the system of trial by jury (Small & Loewenstein, 2005).[2] Jurors, when deliberating, work with an identifiable perpetrator, and thus may attach negative emotions (e.g. disgust, anger) to the individual or assign increased blame when handing down a harsh sentence. Policymakers, who are unable to see the individual offender, being almost entirely emotionally removed, may actually have intended a more lenient sentence. This may produce a harsher verdict than the legal guidelines recommend or allow. On the other extreme, jurors may feel sympathy, relating with the perpetrator on a level not experienced by policymakers, leading to a milder verdict than legally appropriate or allowable (Small & Loewenstein, 2005).[2]

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. On one side, the public discourse can become increasingly negative and hostile, or, if the perpetrator is sympathetic, support for the perpetrator may grow. This is because people experience a greater emotional reaction towards a concrete, identifiable perpetrator than an abstract, unidentifiable one.[2]

Brady Bill

James S. Brady, the then-White House press secretary, was among three collateral damage victims in the attempted assassination of President Reagan in 1981. Brady was explicitly named in reports of the shooting in contrast to the other two injured, a District of Columbia police officer and a Secret Service agent. The political reaction was largely focused on the injuries of Brady which led to the enactment of the Brady Handgun Violence Prevention Act of 1993. It states that it is mandatory for firearm dealers to perform background searches on firearm purchasers.[29]

Business ethics

According to a 2016 study by Yam and Reynolds, the growing absence of the identifiable victim effect in the business world may contribute to an increase in unethical business behavior.[30] With an increasingly globalized business framework, the identifiable victim effect may become naturally mediated, freeing business leaders and employees alike to engage in unethical behavior without guilt or emotional distress. This may be possible because globalization results in less face-to-face contact, decreasing the identifiability of possible victims. Research suggests that business leaders, as well as workers, are more likely to engage in unethical behavior when the victims of their behavior are anonymous. At the executive level, one possible result of this is worker commodification and exploitation. At the worker level, employees of a company are possibly more likely to steal from the company or lie on a report if they do not believe this behavior will negatively affect a recognizable coworker. A decrease in recognizable coworkers could thus potentially lead to an increase in unethical behavior by workers (Yam & Reynolds, 2016).[30] Research also suggests that outside observers, not only perpetrators, view unethical behavior as less unethical if the victim of the unethical behavior is unidentified (Gino, Shu, & Bazerman, 2010).[31] This could possibly result in less public outcry against unethical practices in a globalized business environment, where the victims are often unseen.

Moderating factors

Attachment anxiety

High levels of attachment anxiety may increase the power of identifiable victim effect. Research indicates that individuals with high levels of attachment anxiety may donate more to identified victims and donate less to unidentified victims than the average person (Kogut & Kogut, 2013).[32] According to a study by Kogut and Kogut, attachment anxiety may reduce the expression of altruistic tendencies, commonly demonstrated by charitable giving. Researchers hypothesize that this is because anxiously-attached individuals focus their time and energy on dealing with their own vulnerabilities, leaving them no mental energy to focus on the well-being of others. However, this would only be true of the unidentified individual. When faced with an identified victim, individuals who are anxiously attached tend to donate more money than the average individual. This aligns with past research indicating that anxiously attached people experience significantly more personal distress than those securely attached when confronted with victims in need (Mikulincer et al., 2001).[33]

Although anxiously-attached people may participate in prosocial behaviors, such as donating money to a charity, their actions are suggested not to be the result of altruistic tendencies, but instead "positively correlated with egoistic, rather than altruistic motives for helping and volunteering" (Kogut, T. & Kogut E., 2013, p. 652).[32] Thus, researchers hypothesize that anxiously attached individuals are more likely to help identified victims only because they will personally benefit. This is possibly because the identified victim can fulfill the desire for personal attachment, not because the victim is in need. It is important to note that their increased helpfulness only extends to easy, effortless actions, such as donating money. It does not extend to particularly difficult or effortful actions, such as donating time (Kogut & Kogut, 2013).[32]

Guilt

Research suggests that guilt reduces the power of the identifiable victim effect (Yam & Reynolds, 2016).[30] Before engaging in a behavior, an individual conducts an assessment of the possible emotional outcomes of that behavior. An individual is drawn towards behaviors that would make them happy and repulsed by those that would make them upset. Thus, a person with a high level of guilt is drawn towards altruistic acts because they serve to alleviate the negative emotions that they are experiencing. Consequently, the presence of guilt may actually increase the occurrence of altruistic behavior, such as charitable donations, regardless of whether the victim they are helping is identified or not. Research also suggests that anticipated guilt reduces the occurrence of unethical behavior that may negatively affect an identified victim (Yam & Reynolds, 2016).[30] This may be because knowingly and negatively affecting a recognizable victim causes the individual engaging in unethical behavior to experience distress and negative emotions.

Reasoning style

Research suggests that individual differences in reasoning style moderate the identifiable victim effect (Friedrich & McGuire, 2010).[34] Two different methods of reasoning are “experiential” and “rational”. Experiential thinking (e.g. emotionally-based thinking) is automatic, contextual and fluid, and rational thinking (e.g. logically-based thinking) is deliberative, analytical, and decontextualized. Experiential thinking styles may increase the power of the identifiable victim effect, and rational thinking styles may decrease the power of the identifiable victim effect. Researchers theorize that these differences result because experiential thinkers rely on emotional responses towards an issue when making a decision. In contrast, rational thinkers analyze the situation as a whole before making a decision. Thus, a person thinking rationally would respond to all victims equally, not giving preference to those specifically named or otherwise identified, just as experiential thinkers would be drawn towards the more emotionally charged identified victim (Friedrich & McGuire, 2010).[34] However, research conducted during the COVID-19 pandemic found that identifiable victim effects on public health promoting behaviors were not only undetected, but also not mediated by behavioral tests of reasoning style.[35]

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.[17]

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.[17] Therefore, the victim had already been identified regardless of whether the participants had known anything specific about their identity or not. The circumstances of the victim were more palpable and thus elicited greater sympathy from participants. In contrast, the identities of statistical victims were not yet determined. As such, participants found it more difficult to sympathize with indeterminate victims.

Identification

In certain situations, identification of a victim can actually reduce the amount of help offered to that individual. Research suggests that if an individual is seen as responsible for their plight, people are less likely to offer help than if the victim was not identified at all (Kogut, 2011).[36] Most research dedicated to the identifiable victim effect avoids the topic of blame, using explicitly blameless individuals, such as children suffering from an illness (Kogut & Ritov, 2005).[37] However, there are real-world situations where victims may be seen as to blame for their current situation. For example, in a 2011 study by Kogut, individuals were less likely to offer help to an AIDS victim if the victim had contracted AIDS through sexual contact than if the individual was born with AIDS. In other words, individuals were less likely to offer help to victims if they were seen as at least partially responsible for their plight. A meta-study conducted in 2016 supports these findings, reporting that charitable donations were highest when the victim showed little responsibility for their victimization (Lee & Feeley, 2016).[38]

In such cases where victim blaming is possible, identification of individuals may not induce sympathy and may actually increase negative perception of the victim (Kogut, 2011).[36] This reduction in help is even more pronounced if the individual believes in the just world hypothesis, which is the tendency for people to blame the victim for what has happened to them. This pattern of blame results from a desire to believe that the world is predictable and orderly and that those who suffer must have done something to deserve their suffering.

Individual applicability

Research may indicate that the identifiable victim effect only affects identified individuals, not identified groups (Kogut & Ritov, 2005).[37] A 2005 study by Kogut and Ritov asked participants how much they would be willing to donate to either a critically ill child or a group of eight critically ill children. Although identification of the individual child increased donations, identification of the group of children as a whole did not. Researchers also found that, although both the individual and group evoked similar amounts of empathy, individual victims evoked more emotional distress than groups of victims. Continuing from this, researchers hypothesized that emotional distress, not empathy, appears to be positively correlated with desire to help, or “willingness to contribute.” This supports the idea that altruistic acts may serve as coping mechanisms to alleviate negative emotions, such as guilt (Yam & Reynolds, 2016).[30] This also supports earlier research that suggests distress and sympathy are the driving emotional factors behind the identifiable victim effect (Erlandsson, Björklund, & Bäckström, 2015).[39]

Replicability

A meta-analysis of over 40 experiments found a meta-analytic identifiable victim effect of "r = .05 ~= d = .10",[40] which is either a “null” or “small” effect, depending on which effect size labeling convention researchers adopt.[41][42] Research conducted during the COVID-19 pandemic confirmed that the effect of identifiable victims in public health messaging had either no meaningful effect or a reverse identifiable victim effect on pro-health behaviors such as hand-washing, mask-wearing, and staying at home.[35] While these data cannot conclusively rule out the possibility of identifiable victim effects, they cast doubt on their reliability and magnitude.

See also

References

  1. ^ a b c d e f g h Jenni, Karen; Loewenstein, George (1997-05-01). "Explaining the Identifiable Victim Effect" (PDF). Journal of Risk and Uncertainty. 14 (3): 235–257. doi:10.1023/A:1007740225484. ISSN 0895-5646. S2CID 8498645.
  2. ^ a b c d e f Small, Deborah A.; Loewenstein, George (2005-12-01). "The devil you know: the effects of identifiability on punishment". Journal of Behavioral Decision Making. 18 (5): 311–318. doi:10.1002/bdm.507. ISSN 1099-0771.
  3. ^ Collins, Rebecca L.; Taylor, Shelley E.; Wood, Joanne V.; Thompson, Suzanne C. (1988-01-01). "The vividness effect: Elusive or illusory?". Journal of Experimental Social Psychology. 24 (1): 1–18. doi:10.1016/0022-1031(88)90041-8.
  4. ^ a b "Ryan White and Care Act History". dhhr.wv.gov.
  5. ^ "A Single Death is a Tragedy; a Million Deaths is a Statistic – Quote Investigator".
  6. ^ Schelling, Thomas, C (1968). Chase (ed.). "The Life You Save May Be Your Own". Problems in Public Expenditure Analysis (Pp. 127–162).: 127–162.{{cite journal}}: CS1 maint: multiple names: authors list (link)
  7. ^ Weinstein, M; Shepard, D; Pliskin, J (1980). "The Economic Value of Changing Mortality Probabilities: A Decision-Theoretic Approach". The Quarterly Journal of Economics. 94 (2): 373–396. doi:10.2307/1884546. JSTOR 1884546.
  8. ^ Douglas, Professor Mary; Douglas, Professor of Anthropology Mary (2013-06-17). Risk and Blame. Routledge. ISBN 9781136490040.
  9. ^ Small, Deborah A.; Loewenstein, George (2003). "Helping a Victim or Helping the Victim: Altruism and Identifiability" (PDF). Journal of Risk and Uncertainty. 26 (1): 5–16.
  10. ^ Perrault, Evan K.; Silk, Kami J.; Sheff, Sarah; Ahn, Jisoo; Hoffman, Alice; Totzkay, Daniel (2015-10-02). "Testing the Identifiable Victim Effect With Both Animal and Human Victims in Anti-Littering Messages". Communication Research Reports. 32 (4): 294–303. doi:10.1080/08824096.2015.1089857. ISSN 0882-4096. S2CID 145537304.
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  12. ^ Bohnet, Iris; Frey, Bruno S. (1999). "Social distance and other-regarding behavior in dictator games: Comment". The American Economic Review. 89 (1): 335–339.
  13. ^ Kogut, Tehila; Ritov, Ilana (2005). "The "Identified Victim" Effect: An Identified Group, or Just a Single Individual?" (PDF). Journal of Behavioral Decision Making. 18 (3): 157–167.
  14. ^ Kogut, Tehila; Ritov, Ilana (2005). "The singularity effect of identified victims in separate and joint evaluation". Organizational Behavior and Human Decision Processes. 97 (2): 106–116.
  15. ^ a b Kahneman, Daniel; Tversky, Amos (1979-01-01). "Prospect Theory: An Analysis of Decision under Risk". Econometrica. 47 (2): 263–291. CiteSeerX 10.1.1.407.1910. doi:10.2307/1914185. JSTOR 1914185.
  16. ^ Tversky, Amos; Kahneman, Daniel (1986-01-01). "Rational Choice and the Framing of Decisions". The Journal of Business. 59 (4): S251–S278. doi:10.1086/296365. JSTOR 2352759.
  17. ^ a b c Small, Deborah A.; Loewenstein, George (2003-01-01). "Helping a Victim or Helping the Victim: Altruism and Identifiability". Journal of Risk and Uncertainty. 26 (1): 5–16. doi:10.1023/A:1022299422219. ISSN 0895-5646. S2CID 207550600.
  18. ^ a b c Loewenstein, George; Small, Deborah; Strnad, Jeff (2005-03-01). "Statistical, Identifiable and Iconic Victims and Perpetrators". Rochester, NY. SSRN 678281. {{cite journal}}: Cite journal requires |journal= (help)
  19. ^ "October 16, 1987 : Baby Jessica rescued from a well as the world watches". history.com. 2011. Retrieved 2017-02-12.
  20. ^ Henley, Jon (3 September 2015). "Britons rally to help people fleeing war and terror in Middle East". The Guardian. Retrieved 3 September 2015.
  21. ^ "Bias in the Spotlight: Identifiable Victim Effect". The Marketing Society.
  22. ^ "Protests across the globe after George Floyd's death". CNN. June 6, 2020. Archived from the original on September 17, 2020. Retrieved September 14, 2020.
  23. ^ "George Floyd death: Violence erupts on sixth day of protests". BBC News. June 1, 2020. Archived from the original on June 6, 2020. Retrieved June 13, 2020.
  24. ^ "Fatal Force". The Washington Post. Retrieved July 21, 2021.
  25. ^ Edwards, Frank; Lee, Hedwig; Esposito, Michael (August 20, 2019). "Risk of being killed by police use of force in the United States by age, race–ethnicity, and sex". Proceedings of the National Academy of Sciences of the United States of America. 116 (34).
  26. ^ "WHY PEOPLE GET UPSET ABOUT THE WRONG STORIES". Media vs Reality. February 6, 2021.
  27. ^ a b Redelmeir, D. A.; Tversky, A. (1990). "Discrepancy between medical decisions for individual patients and for groups" (PDF). New England Journal of Medicine. 322 (16): 1162–1164. doi:10.1056/nejm199004193221620. PMID 2320089. S2CID 142513619. Archived from the original (PDF) on 2017-04-28.
  28. ^ Toufexis, A.; Bjerklie, D. (1993). "The ultimate choice". Time. 142 (9): 43–4. PMID 11645235.
  29. ^ Longley, Robert (August 23, 2016). "Brady Act Gun Buyer Background Checks". thoughtco.com.
  30. ^ a b c d e Yam, K. C.; Reynolds, S. J. (2016). "The effects of victim anonymity on unethical behavior". Journal of Business Ethics. 136 (1): 13–22. doi:10.1007/s10551-014-2367-5. S2CID 144057330.
  31. ^ Gino, F.; Shu, L. L.; Bazerman, M. H. (2010). "Nameless + harmless = blameless: When seemingly irrelevant factors influence judgment of (un)ethical behavior". Organizational Behavior and Human Decision Processes. 111 (2): 93–101. doi:10.1016/j.obhdp.2009.11.001.
  32. ^ a b c Kogut, T.; Kogut, E. (2013). "Exploring the relationship between adult attachment style and the identifiable victim effect in helping behavior" (PDF). Journal of Experimental Social Psychology. 49 (4): 651–660. doi:10.1016/j.jesp.2013.02.011.
  33. ^ Mikulincer, M.; Gillath, O.; Halevy, V.; Avihou, N.; Avidan, S.; et al. (2001). "Attachment theory and reactions to others' needs: Evidence that activation of the sense of attachment security promotes empathic responses". Journal of Personality and Social Psychology. 81 (6): 1205–1224. doi:10.1037/0022-3514.81.6.1205. PMID 11761318.
  34. ^ a b Friedrich, J.; McGuire, A. (2010). "Individual differences in reasoning style as a moderator of the identifiable victim effect". Social Influence. 5 (3): 182–201. doi:10.1080/15534511003707352. S2CID 143401716.
  35. ^ a b Byrd, Nick; Białek, Michał (July 2021). "Your health vs. my liberty: Philosophical beliefs dominated reflection and identifiable victim effects when predicting public health recommendation compliance during the COVID-19 pandemic". Cognition. 212: 104649. doi:10.1016/j.cognition.2021.104649.
  36. ^ a b Kogut, T (2011). "Someone to blame: when identifying a victim decreases helping" (PDF). Journal of Experimental Social Psychology. 47 (4): 748–755. doi:10.1016/j.jesp.2011.02.011.
  37. ^ a b Kogut, T.; Ritov, I. (2005). "The "identified victim" effect: an identified group, or just a single individual?" (PDF). Journal of Behavioral Decision Making. 18 (3): 157–165. doi:10.1002/bdm.492.
  38. ^ Lee, S.; Feeley, T. H. (2016). "The identifiable victim effect: A meta-analytic review". Social Influence. 11 (3): 199–215. doi:10.1080/15534510.2016.1216891. S2CID 152232362.
  39. ^ Erlandsson, A.; Björklund, F.; Bäckström, M. (2015). "Emotional reactions, perceived impact and perceived responsibility mediate the identifiable victim effect, proportion dominance effect and in-group effect respectively". Organizational Behavior and Human Decision Processes. 127: 1–14. doi:10.1016/j.obhdp.2014.11.003.
  40. ^ Lee, Seyoung; Feeley, Thomas Hugh (2016-07-02). "The identifiable victim effect: a meta-analytic review". Social Influence. 11 (3): 199–215. doi:10.1080/15534510.2016.1216891. ISSN 1553-4510.
  41. ^ Cohen, Jacob (1977). Statistical power analysis for the behavioral sciences (Rev. ed.). New York: Academic Press. ISBN 978-0-12-179060-8. OCLC 568755085.
  42. ^ Funder, David C.; Ozer, Daniel J. (June 2019). "Evaluating Effect Size in Psychological Research: Sense and Nonsense". Advances in Methods and Practices in Psychological Science. 2 (2): 156–168. doi:10.1177/2515245919847202. ISSN 2515-2459.
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