Introduction
“I wanted only to live in accord with the promptings which came from my true self. Why was that so very difficult?”
― Hermann Hesse, Demian: Die Geschichte von Emil Sinclairs Jugend
Over the past week, I’ve taken the time to review a topic related to at least consumer economics, law, and politics: Framing. I decided to explore this topic because understanding the psychology of decision-making is important for navigating the world in an effective and prudent manner; framing is just one aspect of how our decisions can be unconsciously affected.
The more I read on the topic, the more I was simultaneously disturbed by the level of irrationality with which decisions are typically made and intrigued by how decisions can be tacitly shaped through slight shifts in presentation. Later texts on how Framing has been studied in the field of cognitive neuroscience seemed more preliminary but still remarkable.
In this paper, I’ll briefly review the concept of Framing. I’ll cover papers written by Kahneman and Tversky, Rachlinski, and several others. The domains of research include Economics, Law, Neuroscience, and research in Cognitive Science. I will try to synthesize some of the information presented in these articles to create a model of decision-making with regard to how decisions are made under the influence of Framing.
I will conclude the paper by discussing some of the possible effects of Framing, especially with regard to politics. I hope you find the potential consequences of Framing on politics as disturbing and intriguing as I.
What is Framing?
Framing or, more accurately, Prospect Theory, can best be understood as a means to reconcile the normative claims made about choices with how they are actually occurring. I.e., Framing is a descriptive model that supplies a researcher or observer of human behavior with certain conditional precepts but does not ultimately define those precepts; the behavior defines the model and the model, i.e., prospect theory, allows you to make predictions – predictions that are more accurate than the initial normative model.
The normative models, specifically utility theory, depended on four “assumptions” of behavior (Tversky and Kahneman, 1989). These presumptions are Cancellation, Transitivity, Dominance, and Invariance. The assumption of Cancelation is the “elimination of any state of the world that yields the same outcome regardless of one’s choice” (ibid). If the assumption of Cancelation were to have held, “it should [have] depend[ed] only on states in which they yield[ed] different outcomes.” The second assumption, Transitivity is “satisfied if it is possible to assign to each option a value that does not depend on the other available options.” Transitivity would have held if decisions were made individually or separately. Thirdly, the concept of Dominance holds that “if one option is better than another in one state and at least as good in all other states, the dominant option should be chosen.” I.e., the best and worst options should be respected if the decision is truly a rational one. And lastly, Invariance suggests that “different representations of the same choice problem should yield the same preference… the preference between options should be independent of their description.” If Invariance were to have held, it would have meant that “variations of form that do not affect the actual outcomes should not [have] affect[ed] the choice” (ibid). By the time Tversky and Kahneman had written this paper, the presupposition of Cancellation already had cause to be invalidated (Allais, 1979 and Ellsberg, 1961).
The most notable, and perhaps most widely known, concept in Framing is the fact that invariance fails to hold. The popular problem used to demonstrate the invalidity of invariance is the survival frame vs. the mortality frame, with the mortality frame typically being the favored presentational mode. Importantly, “the framing effect” elicited by this frame “was not smaller for experienced physicians or for statistically sophisticated business students than for a group of clinic patients [italics added]” (Tversky and Kahneman, 1989 and McNeil et al., 1982). In other words, experts are not immune to this effect, suggesting that its root causes are not necessarily culturally conditioned, but are more a product of innate physiological processes interacting with cultural conditions.
The second major example is the gains vs. losses frame (Tversky and Kahneman, 1985). The choice was composed of two decisions, each with two choices between them. The first decision was described as follows: “A. a sure gain of $240 [or] B. 25% chance to gain $1000 and 75% chance to gain nothing.” 84% of participants chose the first option for this first decision. The second allowed participants in the study to incur “C. a sure loss of $750 [or] D. 75% chance to lose $1000 and 25% chance to lose nothing.” 87% of participants chose the second choice. Decision one evoked a risk-averse response, while decision two evoked a risk-seeking response. Gains are typically decided under a risk-averse mindset, while losses are typically decided under a risk-seeking mindset. Interestingly, the combined choices by the participants in the study expressed a “dominated preference.” I.e., the participants would have been better off choosing options B & C over options A & D. The authors note that “[w]hen the options are presented in [the] aggregated form, the dominant option is invariably chosen.” However, when the options are presented separately, they choose the options that are likely to net them a greater cost. What this demonstrates is that, under the right conditions, invariance doesn’t hold and are thus is subject to framing or – specifically – presentation effects.
Tversky and Kahneman provide an explanation for the phenomenon:
“Because the evaluation of outcomes and probabilities is generally non-linear, and because people do not spontaneously construct canonical representations of decisions, invariance commonly fails. Normative models of choice, which assume invariance, therefore cannot provide an adequate descriptive account of choice behavior.” (Tversky and Kahneman, 1989).
Prospect Theory, which includes Framing, consists of Framing itself and Evaluation. Framing is “a preliminary analysis of the decision problem, which frames the effective acts, contingences, and outcomes.” Framing is controlled by how a choice problem is “presented… by norms, habits, and expectancies of the decision maker” (italics added). Evaluation is the time wherein the choice is assigned a value with respect to the other choices, and chosen based on that value (Tversky and Kahneman, 1989).
Tversky and Kahneman propose a value function that, as a model, helps to explain how framing effects can be considered with respect to loss aversion and risk-seeking behavior. Their function is “defined on gains and losses… concave for gains and convex for losses, and… steeper for losses than for gains.” The authors show that their S-shaped function helps to explain the behavior of participants in several studies. They identify that “shifts in reference can be induced by different decompositions of outcomes into risky and riskless components.” This reference point “can also be shifted by a mere labeling of outcomes.” I.e., the language itself, not the concrete qualities of the problems, alters the evaluation of the choices.
Importantly, if a discussion was framed with respect to losses, those participating in the dialogue were less likely “to reach agreement and more often failed to discover the Pareto-optimal solution” (Bazerman, 1983). Also, whenever one party sees their compromises as a loss and the compromise of the other party as a gain, the two parties may be risk-averse or loss-averse; as such, they are more likely to stick with the certain decision than the decision of chance. This effect can partly be ameliorated by trading in ‘bargaining chips’ of equal value. Doing so tends to dissolve the loss-aversion effect (Kahneman and Tversky, 1984).
Wage increases, specifically nominal wage increases, also may be affected by framing. In periods of inflation, a merely nominal wage increase may be regarded as a net gain despite the fact that it is actually a reflection of lost real wages. This effect is the result of the fact that the wage is going up nominally, and thus is perceived as a real increase in wages. Effectively, if inflation were not occurring, and wages were decreased in proportion to the decrease in real wages during periods of inflation, the employee would be unwilling to accept the loss. However, during periods of inflation, and when the wages increase only because there’s a larger money supply, the employee is deceived into believing they’re making more money when they’re losing money. The mere use of concrete values to express an increase in value without respect to the proportionate loss of real wages generates the illusion. The employees see the gain in nominal wages as “fair” despite the fact that they’re losing money (Kahneman, Knetsch, & Thaler, 1986).
Interestingly, incentives may not change the effect of framing and, in some instances, may make framing effects, specifically risk-averse or risk-seeking behavior, more severe (Grether, 1980; Tversky and Kahneman, 1983; Grether and Plott, 1979; Slovic and Lichtenstein, 1983).
In short, what we can conclude is that framing effects are legitimate phenomena – something like framing is occurring, and normative theories of behavior do not account for what is actually happening. Thus, framing is a better descriptive model and enables more robust predictions of behavior. Again, framing is defined by the presentation of the problems posed, and the norms, habits, and expectations of the people trying to solve the problem or making a choice, at least. This means that different cultures likely elicit different framing effects e.g., the culturally contingent outcomes of the Muller-Lyer Illusion. This group-contingent modifier on framing effects will later be shown to also be affected by age. Fascinatingly, the law is also affected by the framing effect, and Prospect Theory can be used to make predictions about the choices people make when deciding whether to take a case to court.
Framing Effects and the Law
In his 1996 paper, Gains, Losses, and the Psychology of Litigation, Rachlinksi discusses the effect prospect theory has on the likelihood of a case heading to court based on whether the case is framed as a gain for the plaintiff or a potential loss for the defendant, for example. He partly attributes risk-seeking litigation with a desire to receive vindication, i.e., “Parties may litigate doggedly in pursuit of perfectly rational concerns, such as defending their good name or vindicating an injustice” (Rachlinski, 1996); to put it clearly, preserve or gain something. For the defendant, the concerns governing litigious behavior likely vary a bit more. Rachlinski argues that defendants typically make choices that appear to be risk-seeking.
Just as Kahneman and Tversky propose, Rachlinski argues that, with respect to gains, plaintiffs and defendants may be more likely to opt for a risk-averse strategy. The inverse is true for losses: plaintiffs and defendants who decide to litigate under a loss frame may choose to be more risk-seeking. This matches the S-Function proposed by the former authors, i.e., gains reflect a concave curve and losses a convex curve, and losses have a steeper slope than gains.
Rachlinski started by examining if he could predict whether a case would reflect a risk-averse or risk-seeking strategy based on proposed settlements provided to mock clients and their attorneys. The settlements were invariant, but were framed as either “winning” or “losing.” What he found was that plaintiffs “consistently [chose] between a sure gain by settling and the prospect of winning more at trial.” I.e., the plaintiffs are more willing to accept what they can get than risk losing what they will get for what the might get; the certain reward is more ‘valuable’ than the potential reward. He argues that “plaintiffs [are] more likely [to] consist of individuals with more limited wealth than the defendants, which are more likely to be corporate entities” (ibid). Thus, whether one may settle is likely contingent on more factors than just the frame. Yet, the frame – given his example’s invariance – likely has a significant effect on plaintiffs and defendants alike.
Rachlinski also reviewed a study by Babcock et al. demonstrating how the framing hypothesis is supportable. Rachlinski identified that plaintiffs in the Babcock study were consistently risk-averse; they “were willing to accept between ten percent and twenty percent less than the expected value of litigated outcomes.” Another study, although its results were a little ambiguous, still supported the framing effect (Van Koppen, 1990) – “data from subjects who were evaluating the plaintiff’s perspective supported the framing hypothesis in all conditions, data from the subjects evaluating the defendant’s perspective who were paid or who developed their own probability estimates supported a more traditional, expected utility model.” In one last study (Coursey and Stanley, 1988), the authors found results that supported the expected utility model, although it tacitly supported the framing model. In this study, participants were subjected to two conditions; the first condition required litigants to “forfeit a portion of their payment” if they failed to settle; in the second condition, “only the ultimate loser of the gamble had to pay for initiating the gamble.” This led Coursey and Stanley to the conclusion that the second gamble because it was riskier, incentivized the participants to take a risk-averse strategy and to settle for what they were certain about. All of the studies, although they can be construed to support the utility model, do support the S-function. As either plaintiff or defendant, viewing their returns as gains rather than as potential losses caused them to take more risk-averse actions generally.
Rachlinski sought to demonstrate framing effects on litigation choices, and so devised his own studies. The results of his study supported the framing effect. In his first study, plaintiff subjects were more likely than defendants to accept the offers provided to them. This is telling, given that, by the nature of his study, participants were required to view the settlement’s winnings or losses from the perspective of either the defendant or plaintiff. I.e., “the comparison of the settlement rates between the plaintiff and defendant subjects within a probability level required comparing the settlement rate for the plaintiff subjects at that probability with the rate for defendant subjects at the other level.” The plaintiffs tended to be risk-averse, suggesting they saw their litigation strategy as a potential gain rather than a loss and were more willing to accept what they could get rather than what they might win if they decided not to settle. Rachlinski keenly noted: “Plaintiffs prefer sure, riskless settlement cases more than defendants,” even if the stakes went up.
Rachlinski performed another study, as well, this time assessing whether a group of first-year law students would “wait [to] avoid” a riskier effect or take the riskier strategy and withhold documentation that could have them sanctioned. The riskier option allowed the defendant to avoid costs for their employer but incurred numerous downsides, including reputational loss. The students who evaluated the case as a loss took the risker option and chose to “settle before disclosing the documents.” This was an important finding as it clearly showed that the defendant’s frame was more likely to cause them to take a risky option, including an unethical one. Waiting and settling later still incurred a loss, but it didn’t incur as many losses as the riskier strategy; thus, taking the potential losses into consideration, which include “[the wrath of] parents, judicial sanctions for fraudulent settlement negotiations, and a potential loss of reputation,” allowed the waiting strategy to be seen as a potential gain. In other words, looking at potential losses and perceiving them as gains makes it more likely that one will take a risk-avoidant strategy, whereas looking at potential losses and only potential losses make it more likely one will engage in risky behavior, including behavior that is exceptionally unethical and unlawful.
In total, these simulation studies, including the reviewed studies, support prospect and frame theory. I.e., “these data support the idea that behavioral decision theory generally – and prospect theory more specifically – provide a more comprehensive and accurate portrait of a litigant’s behavior than expected utility theory.”
However, these were only simulated studies, so what do cases in the real world suggest: does framing theory hold? Rachlinski does one more study wherein he analyzes 722 “cases of civil litigation decided by juries in the California counties of San Francisco, San Mateo, and Santa Clara between 1981 and 1988.” The cases were classified as ‘Defendant Error” i.e., “if the defendant would have been better off by accepting the plaintiff’s offer than electing to go to trial”; ‘Plaintiff Error’ i.e., “if the plaintiff would have been better off by accepting the defendant’s offer”; or finally, ‘No Error’ i.e., ‘if the jury gave an award that fell between the two final offers.” Rachlinski found that, while plaintiffs made more errors, the errors defendants made were significantly costlier. “Statistical analysis revealed that the difference in mean costs of Defendant versus Plaintiff Errors was highly significant [t (517) = 5.82, p<.001].” On average, the cost to plaintiffs due to Plaintiff Error was $15,532 per case, whereas the defendant’s cost on average due to Defendant Error was $81,638 per case. I.e., “Defendant Errors remain significantly more costly than the Plaintiff errors” when determined “by multiplying the man size of each error times the probability of its occurrence [t (517) = 4.87, p<.001)].
Corporate Litigation was a little different. However, once again, “errors proved far more costly to the defendants.” The difference caused by Plaintiff Error vs. Defendant Error was statistically significant “t (66) = 2.00, p < .05.” Plaintiff Errors cost plaintiffs on average $43,863 per case, while Defendant Errors cost corporate defendants on average $594,145 per case.
By continuing to litigate rather than settling (the riskier option), the defendants, on average, won more cases. However, when they did not, it was far costlier for them to make an error than the plaintiff. The data from these Californian cases suggest that plaintiffs lose substantial sums of money settling, i.e., taking the more risk-averse approach, on average. I.e., even if there’s a cost associated with continuing to litigate, that cost, on average, will be less than the costs incurred by the defense if they are in error. Rachlinski notes that this cost cannot always be attributed to the wealth of the plaintiffs alone, as corporate plaintiffs “make low settlement offers and defendants reject them in favor of even lower offers.” He also notes that “failed settlement talks made more than half of the plaintiffs worse off at trial than they could have been in a settlement, [however] the quarter who benefited from litigation won such enormous awards that, on average, the failures to settle improved the plaintiffs’ outcomes.” I.e., while the defendants take the riskier approach on average, maybe they shouldn’t, and while the plaintiffs take the risk-averse approach on average, and lose more often doing so, the benefit from winning is so high that maybe they should litigate.
Overall, Rachlinski’s study of Prospect Theory or Framing and law clearly demonstrates that framing a case with respect to either gains or losses can have a significant effect on the course of action an attorney or client will be willing to take. In other words, seemingly unconsciously, how a case is framed can alter the manner in which a choice is made, even resulting in completely unscrupulous and unethical choices.
The Behavioral Neuroscience of Choice
While not the same as framing, context is a significant variable when assessing consumer choice; framing can be seen as a category of context theory, as well. Consumer choices, which include political choices (a candidate is a kind of product or good chosen by consumers), “engage multiple cognitive functions that govern attention driven encoding of information, retrieval of task relevant information from memory, prediction of uncertain values, and post-choice satisfaction updating” (Bartels and Johnson, 2015).
Consumer choices, even those affected by framing, can be viewed as products of experience and learning. For example, in one study, different wait times dictated whether it was more “beneficial to sustain or curtail” a persistent set of behaviors (McGuire and Kable, 2012). Over time, people who chose to curtail their patient behavior, or found it more beneficial to curtail their patient behavior, were habituated, i.e., learned, to become more impatient. In other words, long-term decisions can be affected by the payoff of the benefit received from waiting, while preference for short-term outcomes can be affected by the reward received from obtaining immediate gratification.
With regards to framing, one study found that ‘bad choices’ were caused by representations of the “decision environment that were incongruous with its true dynamics” (Gureckis and Love, 2009). I.e., unless the agent is capable of learning about their environment, or has enough time to learn about their environment, they will continue to make bad or costly mistakes. This idea was also identified by Tversky and Kahneman (Kahneman and Tversky, 2013). Their example is as follows:
“Image a person who is involved in a business venture, has already lost 2,000 and is now facing a choice between a sure gain of 1,000 and an even chance to win 2,000 or nothing. If he has not yet adapted to his losses, he is likely to code the problem as a choice between (-2,000, .50) and (-1,000) rather than a choice between (2,000, .50) and (1,000). As we have seen, the former representation induces more adventurous choices than the latter.” (italics added)
I.e., unless he has updated his representation of the environment, an individual will not only make poorer choices, but those poorer choices can effectively be seen as riskier choices or risk-seeking behavior. Thus, for a consumer to make an appropriate choice, his model or representational model of the world around him has to effectively correspond to the world around him.
The neuro-physiological bases for these decisions seem relatively clear, although it is likely that there’s more room for investigation. In their 2015 paper, Hsu and Yoon identified that “behavioral preferences were found to be correlated with activity in [the] ventromedial prefrontal cortex” (McClure et al., 2004; Deppe et al., 2005; and Spitzer et al., 2002). The researchers identified that children “appear to develop… sophisticated knowledge of environmental stimuli such as brand logos, and are able to recognize them as early as 3 years old” (McAlister and Cornwell, 2010). They also identified that consumption domains, such as music preference, relate to when, for example, a song was popular, “with the strongest relationships for pieces that were hits when the respondent was in late adolescence or early adulthood” (Holdbrook and Schindler, 1989). Hsu and Yoon theorize that this early brand affiliation may be the result of the fact that reward-related regions of the brain, e.g., frontal-striatal pathways, “undergo particularly marked developmental changes during adolescence,” while disturbance of these developmental pathways causes “profound effects on experimentation and consumption of alcohol and other drugs” (Doremus-Fitzwater, Varlinskaya, and Spear, 2010). Hsu and Yoon also identify that similar effects can be observed from model organisms, underscoring the “important interaction of parental care and neural systems in shaping organisms’ behavioral responses to reward and punishment” (Fone and Porkess, 2008 and Liu et al., 2000).
Importantly, the vmPFC (ventromedial prefrontal cortex) has been correlated to a reduced understanding of fair vs. unfair offerings (Gu et al., 2015), risk-taking behavior with respect to costly normative decisions (Baumgartner et al., 2011), and deficits in social conduct, decision-making, and emotional processing in patients with lesions to this area of the brain (Tranel, Bechara, and Denburg, 2002). This putatively suggests the role of the vmPFC in normative behavior and, specifically, the acquisition of norms through conditioning. I.e., in combination with the striatum, which includes areas such as the nucleus accumbens, the vmPFC learns appropriate vs. inappropriate behavior. I.e., the ability to build a coherent representational model of the world around one’s self is contingent upon a functioning and efficient frontal-striatal pathway. This is supported by contemporary research showing higher frontal-striatal pathway activations were associated with gambling disorders (Brevers et al., 2015) and that pathological gambling disorders are related to frontal-striatal pathway dysfunction (van Holst et al., 2010).
Another key aspect of decision-making is the ability to pay attention to the choices in front of you. Hsu and Yoon suggest the striatum, dorsal ACC, and insula (Kim, Shin, and Han, 2014) respond to “variations in consideration size” i.e., “the space [between] the entire universe of available option[s] and the final choice… [consisting] of the set of alternatives considered immediately prior to [the] choice” (Shocker et al., 1991 and Hauser and Wernerfelt, 1990). I.e., evaluation is achieved through the weighing of choices confined to a specific set of choices with respect to the self and that choice. The ability to manipulate choices in one’s working memory appears to play a significant role in this process (Rustichini, 2021).
Another paper, focusing on how consumer choices are influenced by Bault and Rusconi (2020), also highlights the importance of attention. They review how attention changes based on what is being evaluated during a choice (Krajbich and Rangel, 2011). Bault and Rusconi highlight that “during binary choices between snacks, the striatum and the ventromedial prefrontal cortex… encode the value of the attended item, relatively to the value of the unattended item” (Hare et al., 2011 and Lim et al., 2011). This finding is based on an attentional drift diffusion model, which “states that the values of the attributes of the currently attended item are retrieved and integrated” (Krajbich et al., 2010). “When the difference between the values of the two items reaches a given threshold, the decision process terminates” (ibid). Bault and Rusconi note that this theory has several implications. 1. “the chosen item is the last one to be fixated before the threshold is reached and the decision is made”; 2. “the first fixated item gets an advantage in the value computation process and thus is more like to be chosen”; and 3. “the longer an item is being looked at the more likely it is that it will be chosen” (italics added). In other words, you can predict what a consumer will purchase or manipulate what they’ll purchase by drawing their attention towards a specific good (Krajbich et al., 2012).
In fact, it is clear that researchers can manipulate how attractive a face appears (Shimojo et al., 2003), judgments about moral situations (Pärnamets et al., 2015), and decisions to acquire food or art items (Armel et al., 2008 and Lim et al., 2011). Researchers have also identified that “visually salient items would grab more attention” (Itti and Koch, 2001) and that “features such as intensity, color, and orientation results in participants making a choice that contradicts their initial preferences” (Navalpakkam et al., 2010 and Towal et al., 2013). Interestingly, with respect to working memory, when the cognitive load is higher, these effects become even stronger; i.e., more manipulatable people are distracted people.
Clearly, marketers have not failed to take note of these kinds of facts. However, this could have a deleterious effect on vulnerable populations, including children and older adults. Bault and Rusconi highlight how adolescents engage more in risky behavior (Stienberg, 2017) and that the “uneven neurodevelopmental trajectories of the brain system implicated in processing rewards on one side, and those involved in cognitive control on the other can explain” a proclivity to be more subjected to peer-influence than older individuals (Casey et al., 2008). In adolescents, the “hyper-reactivity of the reward system, especially in the striatum, is associated with emotional hypersensitivity to rewarding stimuli, faces, and socioemotional stimuli” Galvan et al., 2006; Casey et al., 2008; and Hare et al., 2008). This makes the manipulation of children through context effects, and framing, highly efficient, such that when children acquire loyalty to a brand early in their life, this loyalty often persists into adulthood (Haryanto et al., 2016). Media manipulation of children, specifically commercial advertisements, are also “highly effective” (Atkin, 1978 and Gorn and Goldberg, 1982).
One inference that can be made from this evidence is that political party and affiliation can be provided to children and maintained into adulthood. Political party and affiliation can be seen as a kind of product to be advertised to consumers, including children. Combined with childhood peer pressure, marketing may be used to ensure a demographic or population adopts a political party early and conforms to that party for a long time, especially if leaving the party causes the child to be isolated or ostracized by their peers. This can cause significant conflict between children and their parents, and can thoroughly alter the course of a society (Goldberg and Gorn, 1978; Gorn and Goldberg, 1982; and Story and French, 2004). The disturbing part is that it’s not clear that any of these phenomena are happening consciously.
Older individuals are also susceptible to these kinds of marketing effects. Older individuals make poorer decisions in uncertain or changing environments (Bault and Rusconi, 2019). Older adults “borrow at higher interest rates and pay more fees to financial institutions than their younger counterparts” (Agarwal et al., 2007) and are “less consistent in health-related decisions” (Löckenhoff and Cartensen, 2007). They are also more vulnerable “to deceptive advertising than their younger counterparts” (Denbrug et al., 2007). Older individuals are also less capable of “discriminat[ing] between potentially misleading and more truthful… claims” (Gaeth and Heath, 1987), give higher credit to repeated claims, and even if they are told the claim is false, they will still recall it as true (Skurnik et al., 2005). In older individuals, this is caused by “structural changes in frontostriatal pathways… linked to disadvantageous decision[s]” (Samanez-Larkin and Knutson, 2015 and Vijver et al., 2016). Politically, this means that older individuals are highly susceptible to media manipulation and can be easily swayed by false claims and recalcitrantly hold to those claims.
With respect to the S-function provided to us by Kahneman and Tversky, this suggests that older individuals, because they are unable to update their representational model of the world to avoid making poorer choices or riskier or costlier choices, can be qualified as risk-seeking. Children, especially if their model is prohibited from being updated by peer pressure, may also consistently make poorer choices, resulting in poor representations of the world, bad choices, and thus reflect risker behavior. I.e., media, especially political media, can frame the thinking of older individuals and children in such a way as to consistently result in risker and poorer choices by them.
These kinds of poor choices are also shown to compound. I.e., “financial scarcity causes a reduction in cognitive control” Mani et al., 2013, or attentional disruptions. “[C]hanges in attention allocation: salient information relative to short-term decisions receive more attention than information concerning the future, which can cause bad economic decisions such as overborrowing” (Shah et al., 2012). In other words, this creates a cycle. People who are stressed seek relief and are more likely to have a loss frame, meaning they’re more likely to make risker decisions to relieve that stress because they’re seeing their world in light of their losses. If a politician comes along, and markets to them appropriately, the stressed population is more likely to make a riskier decision, because they’re more manipulatable. This results in a poorer choice, which increases the stress of the consumer population who bought into the politician’s promises. In turn, this makes the population even more manipulatable. I.e., stress makes one manipulatable, and can cause someone to make a decision that can increase stress, making them even more manipulatable, i.e., susceptible to coercive marketing. It’s a feed-forward phenomenon, a positive feedback of stress and consumer behavior.
One final paper I’d like to discuss with respect to framing is a model created by Hornsby and Love (2020). This model is called the Coherency Driven Choice model or CDC. This model “learns preferences over choice attributes and uses past choices as the basis for updating them” (ibid). The CDC model “self-supervises using its past choices, thereby making them and similar options more likely to be sampled” (ibid). The CDC model shows that “error-driven, self-supervision helps the agent to maximize coherence between its preferences and choices over time” (ibid). Thus, the CDC “can achieve a sense of order in environments where there are innumerable possible options and dimensions by which to score them” (ibid). The authors state that “the error-driven nature by which CDC learns means that it will update its preferences in order to maximize the perceived contrast between accepted and rejected options” (ibid); i.e., it will seek the ideal of its previously accepted options and avoid the ideal of its previously rejected options, maximizing this choice preference over numerous choice iterations.
Hornsby and Love (2020) showed that their model was operable in theory, and thus was capable of the self-reinforcing behavior that would be consistent with the authors’ conception of coherency. Their model “suggests that a person will have an over-exaggerated preference towards the unique branding of their preferred [good], helping to retrospectively justify their apparent preference” ibid. These exaggerated preferences “helped the model to maximize the perceived contrast between the accepted and rejected choices,” idealizing the differences. In other words, once one is part of a tribe or a group, it’s hard to dissuade them from being a part of that tribe or group, even a political group. In fact, if this model holds, it’s not clear whether or not the opposite party could ever be conceived of as a desirable good. In theory, the model isn’t capable of accounting for all environmental variables driving choice, but it does show that choice preferences should tend to move in particular directions over time based on previous choices. For example, a preferred and idealized product may be out of stock. In this case, although the preferred product may not be chose-able, it’s highly likely a similar product will be chosen in the future. I.e., even if an individual switched political parties or tribes, they would still have their preference model in place and would tend to move in the direction of their previous choices, altering the party they adopt as their own through their choices or identifying themselves as alien to their adopted political party or tribe.
In their second experiment testing this model, Hornsby and Love demonstrated this latter fact. The aim of the authors’ second experiment was “to explore the extent to which people retrospectively update their existing preferences following a free choice.” They hypothesized that “people would show higher levels of agreement for the right-wing view… if their chosen candidate revealed support for that view, compared to the left-wing view.” In other words, people would rationalize their political beliefs so that they aligned with their chosen political candidate.
They also hypothesized that the tendency for the study’s participants to rationalize their political beliefs so that they would align with their chosen political candidate “would vary depending on individual differences.” They specifically argued that “different individuals would be more or less prone to updating their preferences retrospectively, due to differences in their longstanding political beliefs” (ibid). Particularly, they argued that “Republican-identifying participants would be more likely to update their beliefs to be coherent with their initial vote.” They argued that voters are more likely to engage in this behavior due to the nature of power and the necessity to capitulate to power and, secondly, the evidence showing that conservatives “value coherency comparatively more when making political decisions” (ibid, Mendez, 2017; Haidt and Graham, 2007; and Jost, Laser, Kruglanski, and Sulloway, 2003).
The results showed that “participants’ stated degree of belief was significantly influenced by the randomly-assigned belief revealed by their chosen candidate (non-parametric two-way analysis of variance (ANOVA) (F, (1, 952) = 28.89, p < 0.001, CL = 0.563)” The authors and researchers also found that “those that voted for a candidate that later revealed a right-wing opinion… agreed an average of 43.59% more with the right-wing view compared to if the candidate later revealed a left-wing view… [suggesting] that choosing a political candidate based on initially trivial characteristics made participants more likely to agree with the candidate’s later-revealed controversial opinion, irrespective of whether the person self-identified as a Democrat or Republican.” Interestingly, if the subject identified as a Republican, “if their candidate later revealed a more right-wing opinion they were 65.66% more in agreement with the right-wing view (Median = 82.00, IQR = 59.75) compared to when the candidate revealed a more left-wing view (Median = 49.50, IQR = 70.25) (U = 10,131.5, p < 0.001, CL = 0.629). Republicans, in particular, were more likely to adopt the view of their chosen candidate. The authors note that “[Republicans] median support for pro-life abortion policies was 60% higher when their chosen candidate later expressed support for pro-life policies… compared to pro-choice policies” (ibid). I.e., Republics were more likely to adjust their beliefs to be consistent with the last choice they made, even if it were made on farcical grounds, for example, did their chosen candidate like dogs or cats. The authors explain this phenomenon by stating that “differences in people’s belief systems may give rise to different propensities to adjust preferences following a choice.”
These findings suggest that if a choice is made under a loss-frame mindset, and the choice is a poor one, it will cause stress, that stress will compound the loss-frame mindset, and the individual will be liable to engaging in post-hoc rationalizations (conscious or unconscious) that make their choice appear more coherent. The authors of this study argue that people do this to preserve internal consistency when there’s no other rational strategy that’s feasible. The authors state that when “preferences are not transitive, people can become liable to manipulation (or ‘dutch booking’)” (Davidson, McKinsey, and Suppes, 1955). “For example,” the authors argue, “if out of three beers, a person prefers beer A over B, beer B over C but would rather have C than A, their preferences are cyclical. This person could be tricked into paying for a series of costly trades in which the drinker ended with his original beer.” I.e., he’s more likely to be tricked. However, I think this argument is a rationalization itself for the reality, which can be described, that people do get stuck in these choice loops. Specifically, they’re likely to get stuck in these kinds of loops when they’re engaging in risk-seeking behavior. It’s not that risk-seeking is bad per se; it’s that, if the model isn’t updated when losses begin to have deleterious effects (e.g., in a person with a gambling disorder), the individual engaging in the risky behavior will simply rationalize their choice. Their inability to unify the three into a coherent singularity is the result of faulty evaluative processes. The desire for coherence can effectively be seen as a shift from the convex segment of the S-function to the concave segment of the S-function, i.e., a move from the risk-seeking strategy to the risk-averse strategy. If they’re unable to see that the attributes that they’re seeking are all the same (or simply similar enough), they’ll never stick to what they can be certain of, and will always move towards what, to them, appears as the next best thing.
The authors also argue that there are ‘spillover effects.’ Specifically, the authors argue that the choices that “we make have consequences for related future choices” I.e., “people may be prone to agree with a controversial opinion held by a political candidate, by virtue of the fact that they voted for them.” If they did not do this, they would be liable to the same cycle just discussed; i.e., they will never stick to what they can be certain of, they will move towards what appears as the next best thing, and thus will engage in riskier behaviors, and thus will become more prone to physiological stress. This is why we must be very careful about our choices; once we make one, it will be harder to avoid that choice in the future; we will become more apt to rationalize that choice, while the more choices we make, the more we idealize the attribute(s) associated with the initial choice, becoming “fussier” along the way. Thus, our political choices face a two-fold problem: once we make a political choice, we’re more likely to stick with the candidate we’ve chosen and be swayed by the opinions of our chosen candidate, even if they weren’t our own; however, if we don’t stick with what we have, we’ll become fussier along the way, continue to make riskier choices, and thus suffer as a result, especially as our desideratum becomes exponentially more idealized.
Thus, if someone switches tribes or political parties, their candidate may pander to them. As a result, those who chose the candidate but did not do so for the pandered opinions may adopt those opinions simply because their chosen political candidate stated them. Thus, the political opinions of a party may shift as the constituency changes, i.e., the essence of the tribe’s culture will shift as the constitution of the tribe changes. In theory, if these new members alienate enough of the former members, the former members (the fussier members) will likely differentiate themselves from the new members because they do not match the ideal form they’ve constituted from their preference model. In some regard, this creates a new consumer base for a new political candidate to tap into the alienated constituency for political power. I.e., capture is possible, and Conservatives seem more prone to capture, but if they have their idealized model (i.e., understand who they are and what they represent), they will move away from the changing model and reconstitute themselves and their previous model. This is riskier, but if it’s framed as a gain rather than a loss, the risk can be mitigated.
Conclusions and Discussion
“As in water face answereth to face, so the heart of man to man.
Hell and destruction are never full; so the eyes of man are never satisfied.
As the fining pot for silver, and the furnace for gold; so is a man to his praise.”
– Proverbs 27: 19 – 21
First of all, a definition for Framing alludes to how a problem or choice is presented relative to the norms, habits, and expectations of the decision-maker, which can be manipulated by producers. Framing, I think, has been shown to be a better predictor of human behavior than other normative models that try to explain why people choose what they do. Importantly, because Framing is affected by the underlying physiology of an individual and the culture they’re from, Framing Effects are culturally contingent.
We also can claim that the Law, even how it’s structured (Rachlinski wrote quite a bit about how Prospect Theory can explain the failure of Loser-Pays Litigation Legislation in Florida), is affected by framing. But as was covered in this paper, what we can ultimately take away from the review of how Framing affects litigation and law is that merely altering how we perceive a problem (for example, whether we should wait and incur a small financial loss – which can be viewed as a gain – or take a risk and act, and potentially incur an even larger loss, even if that loss costs us our reputation and is unethical), changes the choice of action we take. Sometimes, it’s even better to recognize that our desire for security, i.e., our proclivity to be risk-averse, may be costlier – specifically as a defendant when litigating. This means we must be very careful when making choices; we need as much information about a choice, and choices like it, and the effects of those choices before we make a decision.
The framing effect and context effects, in general, have not been overlooked by businesses or political parties either. Political party and affiliation are a kind of product and are advertised to a consumer base, including children. As noted, children and older adults are particularly susceptible to marketing and, thus, political advertisement. Children, in particular, are also subjected to peer pressure, and brand adoption is very likely to occur at a young age. These two points imply that children tend to adopt the brands their peers adopt to avoid feelings of isolation or alienation. Political parties can use this to their advantage, get children to become loyal to a political party early on, and use their peers to enforce conformity to the political party’s will. Any rebellion from the norm by a child could result in ostracization, a very painful outcome for a young child, which incentivizes compliance. As noted, this can cause significant conflict between parents and their children, and worst of all, it’s not clear whether the behavior is conscious.
With respect to older individuals, they are more susceptible to media marketing and manipulation. They simply need to be fed false information consistently enough to adopt it as factual, and when this occurs, because they’re less able to respond to changing circumstances and environments, they will be less likely to change their opinions, even if they’re told the information is false. They are also more likely to make risky financial decisions, which suggests that they are in a loss frame of mind; i.e., they are not perceiving the world as something to maintain but as something that is slipping away from them, which makes a lot of sense. However, when it comes to political decisions, this means that they are more likely to make choices that could burden others for short-term gains or potential gains that they think are worth the cost, given their mindset. Ultimately, this can have very negative effects on the course of a society.
Both the mindset of the child and the adult can be explained by the S-Function provided to us by Kahneman and Tversky. As noted for older adults, they likely are perceiving things as slipping away from them, and as such, are more prone to risk-seeking behaviors. I.e., they’re more willing to take the risk and incur a loss. This isn’t necessarily a bad thing, but it does mean that, if, on average, their choices are more costly than beneficial, i.e., ‘bad’ choices, then they will tend to make ‘bad’ choices later in life, and those ‘bad’ choices, especially if they have substantial political power, could affect their society significantly. For children, as was noted in the body of the paper, they are still developing, and, as such, are less capable of updating their mental schema of the world, particularly in regards to whether they’ve incurred losses or gains; as such, they’re more susceptible to the loss-frame mindset and will be more likely to make riskier decisions. This is especially true for political behavior. Children do not want to lose touch with their peer group; they want to be like their peers; thus, because they may be afraid of being ostracized by their peers, they may be willing to make choices their peers or a political organization pressures them into (even if they’re costly) because they are not seeing what they can gain by leaving their peer group or their political tribe.
Importantly, poor choices, which are the result of being incapable of properly updating one’s representation of the world to see a problem or choice as a gain rather than a loss (especially when the choice stems from a risky decision), create a positive feedback loop. Stressed people, or people who are overwhelmed, make riskier decisions, which may cost them more. This incursion of costs could stress one out further, resulting in even riskier decisions, especially if the representational model of the world has not been updated to perceive choices vis-à-vis what can be gained. Politicians are highly likely to take advantage of these kinds of situations. A politician may market himself to his constituency, he may be a risky decision for them, but because they’re in a situation that makes it more likely for them to make a risker decision than to stick with what they know, he has better chances of winning. This could very well be a ‘bad’ choice for them. This ‘bad’ decision could exacerbate their stress, causing them to take even riskier courses of action, activating a positive feedback loop of ‘bad’ decisions, and possibly even social collapse.
Also of note, the choices we make are extremely important, especially with regard to how we update our mental representation of the world and our preferences for items in the world around us. Simply deciding on whether we support a political candidate based on whether he likes cats makes us more likely to support his political opinions in the future or to rationalize his political opinions as our own. However, if we didn’t do this, we might be more susceptible to political manipulation; i.e., we could constantly be in a loss frame of mind and more prone to making riskier decisions that won’t pay off, resulting in, as far as I see it, a kind of purity spiral. In other words, to reiterate what was stated in the body of the paper: once we make a political choice, we’re more likely to stick with the candidate we’ve chosen and be swayed by the opinions of our chosen candidate to remain coherent, even if those opinions are not our own; however, if we don’t stick with what we’ve chosen, we open ourselves up to accusations of incoherency or incoherent effects, as a result – because we may have an idealized choice in mind – the more we choose between candidates to fit that idealized preference, the fussier we’ll get along the way, continuously making risker choices, suffering as a result. Bear in mind, these are general effects. In some instances, it may be better to take the more idealized, less conformist, and risker approach.
Lastly, from the research covered in this paper on framing effects and context effects in regard to political candidates, a changing political constituency will have an effect on a party’s culture. Representative politicians secure their power through votes. As a result, they are likely to pander to voters to increase the pool of constituents that will vote for them. This means that if someone has voted for that political candidate in the past, they’re more likely to adopt the candidate’s new views. To be clear, this means that the essence of a culture – its norms, standards, and values – can change as a result of a significant change in the constitution of that culture or the makeup of that culture. Fascinatingly, in theory, this also means that the members who seek to preserve their culture, or who are alienated by the change, may seek to self-organize and establish their own party, tribe, or group. I.e. they have an idealized model or preference, but the new culture does not comport to that idealized model or preference. And because they’ve made so many choices with regard to those norms, values, or standards in mind, they’re more likely to seek embodiments of those norms, standards, or values, and thus will make a risky choice and abandon the culture that, for all intents and purposes, abandoned them. And as long as these kinds of people are able to avoid seeing this risky decision as a loss but can view it as a gain, or can perceive their situation as a gain, they should – in theory – make fewer ‘bad’ decisions – i.e., they can become like those plaintiffs who would have been better off litigating rather than remaining risk-averse.
The goal of this paper was to get a better understanding of how we make decisions so that I could move through the world more efficiently and prudently. I think one of the main takeaways I have from this research is just how unconscious we are, how irrational we are, about the decisions we make. For some people, the consequences of framing effects can be life-changing and extremely detrimental. Completely unbeknownst to them, they can be suggestively enticed into buying a particular product or adopting a worldview. What’s more unsettling, they can regard the choices they are nudged into making as their own and will defend them passionately, despite the fact that they’re alien to them.
For me, this elicits some unnerving existential questions. For example, how much of what we are is us? I guess what I mean by that is this: in a world where the environment has a significant effect on the choices you make, and the choices you make are not wholly your own – i.e., they can be stochastically influenced by numerous variables, including anthropogenic variables – then what are we? In other words, where does one person begin and another end (at least psychologically); which ideas are actually yours; the things you’ve defined yourself by, have you defined yourself by them or has someone nudged you into defining yourself by them? Are you their product; are you an extension of them rather than yourself?
This doesn’t imply that one should vie for absolute autonomy or that they should idealize the concept of self or individuality – I think doing so belies the very aim as gibberish. However, what I do think this suggests is that we should not be so willing to adopt an individualist framework, particularly because it is an act of self-deception. If someone intentionally designs a choice to influence you into making a particular decision, and that decision defines who you are, they have intentionally defined who you are – then where is the you? If you are part of a group, and that group has standards that preserve them as a people in a particular environment, and you have defined yourself by those standards or values, that group has defined you – you are an embodiment of that group, you are not really an individual. These kinds of phenomena would occur naturally in almost all societies; thus, it is incoherent for a society to advocate for individuality. In effect, a society that promotes individuality nudges a member of that society into becoming an individual but, in doing so, provides them with values that promote individualism which they use to define themselves and thus are defined as a member of that society or group – i.e., they are not an individual. This is, as I see it, a version of the ‘dutch booking’ trick. I.e., an incoherent and cyclic phenomenon. It is also not surprising that there are models of behavior out there that suggest a society of individuals is easier to take advantage of than a group, i.e., a red-striped zebra effect. In other words, it’s easier to trick an individualistic society (an oxymoron) into cyclically trading for the same beer over and over again. To put it bluntly, the notion of the individual is an incoherent one, as it’s not clear where one person actually begins and another ends, nor is it clear which choices are yours and which are not; a society that idealizes individualism is incoherent from the top-down or has an undercurrent of incoherency billowing upward.
This doesn’t mean that particular members of a group do not exist, each defined by personal experience (they do), only that the idea of an individual, whose beliefs, choices, property even, for example, are entirely his own, is preposterous. No one emerges from a vacuum; thus, no actual individual exists – at least some part of us has been influenced by someone else, and that part of us is not, in some regard, our own.
Mankind then, in its purely consumptive and individualistic form, is like a mindless, undulating mass, unconsciously directed by signals around it. To harness these signals via framing is only to seemingly control such a grotesque monstrosity. Dependent on the globular horde, you become bound to its maintenance, and thus must subject yourself to its desires, binding and enslaving yourself to its perpetually open maw for the preservation of your own skin; ultimately reflecting yourself in its abominable image; it provides you life, if you sell it your soul; if you let it creep under your skin and dominate you. A consumeristic society will thus reflect this soulless, mindless, unconsciously consuming amoeba. What then is to be gained by the preservation of such an abomination? Nothing, for that is what it represents: void.
Bibliography
Agarwal, S., Driscoll, J.C., Gabaix, X. and Laibson, D., 2007. The age of reason: Financial decisions over the lifecycle.
Allais, M., 1979. The foundations of a positive theory of choice involving risk and a criticism of the postulates and axioms of the American School (1952). In Expected utility hypotheses and the Allais paradox (pp. 27-145). Springer, Dordrecht.
Armel, K.C., Beaumel, A. and Rangel, A., 2008. Biasing simple choices by manipulating relative visual attention. Judgment and Decision making, 3(5), pp.396-403.
Atkin, C.K., 1978. Observation of parent-child interaction in supermarket decision-making. Journal of marketing, 42(4), pp.41-45.
Babcock, L., Farber, H.S., Fobian, C. and Shafir, E., 1995. Forming beliefs about adjudicated outcomes: Perceptions of risk and reservation values. International Review of Law and Economics, 15(3), pp.289-303.
Bartels, D.M. and Johnson, E.J., 2015. Connecting cognition and consumer choice. Cognition, 135, pp.47-51.
Bault, N. and Rusconi, E., 2020. The art of influencing consumer choices: a reflection on recent advances in decision neuroscience. Frontiers in Psychology, 10, p.3009.
Baumgartner, T., Knoch, D., Hotz, P., Eisenegger, C. and Fehr, E., 2011. Dorsolateral and ventromedial prefrontal cortex orchestrate normative choice. Nature neuroscience, 14(11), pp.1468-1474.
Bazerman, M.H., 1983. Negotiator judgment: A critical look at the rationality assumption. American Behavioral Scientist, 27(2), pp.211-228.
Brevers, D., Noël, X., He, Q., Melrose, J.A. and Bechara, A., 2016. Increased ventral‐striatal activity during monetary decision making is a marker of problem poker gambling severity. Addiction biology, 21(3), pp.688-699.
Casey, B.J., Getz, S. and Galvan, A., 2008. The adolescent brain. Developmental review, 28(1), pp.62-77.
Coursey, D.L. and Stanley, L.R., 1988. Pretrial bargaining behavior within the shadow of the law: Theory and experimental evidence. International Review of Law and Economics, 8(2), pp.161-179.\
Davidson, D., McKinsey, J.C.C. and Suppes, P., 1955. Outlines of a formal theory of value, I. Philosophy of science, 22(2), pp.140-160.
Denburg, N.L., Cole, C.A., Hernandez, M., Yamada, T.H., Tranel, D., Bechara, A. and Wallace, R.B., 2007. The orbitofrontal cortex, real‐world decision making, and normal aging. Annals of the New York Academy of Sciences, 1121(1), pp.480-498.
Deppe, M., Schwindt, W., Kugel, H., Plassmann, H. and Kenning, P., 2005. Nonlinear responses within the medial prefrontal cortex reveal when specific implicit information influences economic decision making. Journal of neuroimaging, 15(2), pp.171-182.
Doremus-Fitzwater, T.L., Varlinskaya, E.I. and Spear, L.P., 2010. Motivational systems in adolescence: possible implications for age differences in substance abuse and other risk-taking behaviors. Brain and cognition, 72(1), pp.114-123.
Ellsberg, D., 1961. Risk, ambiguity, and the Savage axioms. The quarterly journal of economics, pp.643-669.
Erk, S., Spitzer, M., Wunderlich, A.P., Galley, L. and Walter, H., 2002. Cultural objects modulate reward circuitry. Neuroreport, 13(18), pp.2499-2503.
Farnsworth, W., Guzior, D.F. and Malani, A., 2010. Ambiguity about ambiguity: An empirical inquiry into legal interpretation. Journal of Legal Analysis, 2(1), pp.257-300.
Fone, K.C. and Porkess, M.V., 2008. Behavioural and neurochemical effects of post-weaning social isolation in rodents—relevance to developmental neuropsychiatric disorders. Neuroscience & Biobehavioral Reviews, 32(6), pp.1087-1102.
Gaeth, G.J. and Heath, T.B., 1987. The cognitive processing of misleading advertising in young and old adults: Assessment and training. Journal of Consumer Research, 14(1), pp.43-54.
Galvan, A., Hare, T.A., Parra, C.E., Penn, J., Voss, H., Glover, G. and Casey, B.J., 2006. Earlier development of the accumbens relative to orbitofrontal cortex might underlie risk-taking behavior in adolescents. Journal of Neuroscience, 26(25), pp.6885-6892.
Goldberg, M.E. and Gorn, G.J., 1978. Some unintended consequences of TV advertising to children. Journal of Consumer Research, 5(1), pp.22-29.
Gorn, G.J. and Goldberg, M.E., 1982. Behavioral evidence of the effects of televised food messages on children. Journal of consumer research, 9(2), pp.200-205.
Grether, D.M. and Plott, C.R., 1979. Economic theory of choice and the preference reversal phenomenon. The American Economic Review, 69(4), pp.623-638.
Grether, D.M., 1980. Bayes rule as a descriptive model: The representativeness heuristic. The Quarterly journal of economics, 95(3), pp.537-557.
Gu, X., Wang, X., Hula, A., Wang, S., Xu, S., Lohrenz, T.M., Knight, R.T., Gao, Z., Dayan, P. and Montague, P.R., 2015. Necessary, yet dissociable contributions of the insular and ventromedial prefrontal cortices to norm adaptation: computational and lesion evidence in humans. Journal of Neuroscience, 35(2), pp.467-473.
Gureckis, T.M. and Love, B.C., 2009. Short-term gains, long-term pains: How cues about state aid learning in dynamic environments. Cognition, 113(3), pp.293-313.
Haidt, J. and Graham, J., 2007. When morality opposes justice: Conservatives have moral intuitions that liberals may not recognize. Social Justice Research, 20(1), pp.98-116.
Hare, T.A., O'doherty, J., Camerer, C.F., Schultz, W. and Rangel, A., 2008. Dissociating the role of the orbitofrontal cortex and the striatum in the computation of goal values and prediction errors. Journal of neuroscience, 28(22), pp.5623-5630.
Hare, T.A., Schultz, W., Camerer, C.F., O'Doherty, J.P. and Rangel, A., 2011. Transformation of stimulus value signals into motor commands during simple choice. Proceedings of the National Academy of Sciences, 108(44), pp.18120-18125.
Haryanto, J.O., Moutinho, L. and Coelho, A., 2016. Is brand loyalty really present in the children's market? A comparative study from Indonesia, Portugal, and Brazil. Journal of Business Research, 69(10), pp.4020-4032.
Hauser, J.R. and Wernerfelt, B., 1990. An evaluation cost model of consideration sets. Journal of consumer research, 16(4), pp.393-408.
Hornsby, A.N. and Love, B.C., 2020. How decisions and the desire for coherency shape subjective preferences over time. Cognition, 200, p.104244.
Hsu, M. and Yoon, C., 2015. The neuroscience of consumer choice. Current opinion in behavioral sciences, 5, pp.116-121.
Itti, L. and Koch, C., 2001. Computational modelling of visual attention. Nature reviews neuroscience, 2(3), pp.194-203.
Jost, J.T., Glaser, J., Sulloway, F.J. and Kruglanski, A.W., 2018. Political conservatism as motivated social cognition (pp. 129-204). Routledge.
Kahneman, D. and Tversky, A., 1984. Choices, values, and frames. American psychologist, 39(4), p.341.
Kahneman, D. and Tversky, A., 2013. Prospect theory: An analysis of decision under risk. In Handbook of the fundamentals of financial decision making: Part I (pp. 99-127).
Kahneman, D., Knetsch, J.L. and Thaler, R.H., 1986. Fairness and the assumptions of economics. Journal of business, pp.S285-S300.
Kim, H.Y., Shin, Y. and Han, S., 2014. The reconstruction of choice value in the brain: A look into the size of consideration sets and their affective consequences. Journal of cognitive neuroscience, 26(4), pp.810-824.
Krajbich, I., Armel, C. and Rangel, A., 2010. Visual fixations and the computation and comparison of value in simple choice. Nature neuroscience, 13(10), pp.1292-1298.
Krajbich, I., Lu, D., Camerer, C. and Rangel, A., 2012. The attentional drift-diffusion model extends to simple purchasing decisions. Frontiers in psychology, 3, p.193.
Krajbich, I., Lu, D., Camerer, C. and Rangel, A., 2012. The attentional drift-diffusion model extends to simple purchasing decisions. Frontiers in psychology, 3, p.193.
Lim, S.L., O'Doherty, J.P. and Rangel, A., 2011. The decision value computations in the vmPFC and striatum use a relative value code that is guided by visual attention. Journal of Neuroscience, 31(37), pp.13214-13223.
Liu, D., Diorio, J., Day, J.C., Francis, D.D. and Meaney, M.J., 2000. Maternal care, hippocampal synaptogenesis and cognitive development in rats. Nature neuroscience, 3(8), pp.799-806.
Löckenhoff, C.E. and Carstensen, L.L., 2007. Aging, emotion, and health-related decision strategies: motivational manipulations can reduce age differences. Psychology and aging, 22(1), p.134.
Mani, A., Mullainathan, S., Shafir, E. and Zhao, J., 2013. Poverty impedes cognitive function. science, 341(6149), pp.976-980.
McAlister, A.R. and Cornwell, T.B., 2010. Children's brand symbolism understanding: Links to theory of mind and executive functioning. Psychology & Marketing, 27(3), pp.203-228.
McClure, S.M., Li, J., Tomlin, D., Cypert, K.S., Montague, L.M. and Montague, P.R., 2004. Neural correlates of behavioral preference for culturally familiar drinks. Neuron, 44(2), pp.379-387.
McGuire, J.T. and Kable, J.W., 2012. Decision makers calibrate behavioral persistence on the basis of time-interval experience. Cognition, 124(2), pp.216-226.
McNeil, B.J., Pauker, S.G., Sox Jr, H.C. and Tversky, A., 1982. On the elicitation of preferences for alternative therapies. New England journal of medicine, 306(21), pp.1259-1262.
Mendez, M.F., 2017. A neurology of the conservative-liberal dimension of political ideology. The Journal of neuropsychiatry and clinical neurosciences, 29(2), pp.86-94.
Navalpakkam, V., Koch, C., Rangel, A. and Perona, P., 2010. Optimal reward harvesting in complex perceptual environments. Proceedings of the National Academy of Sciences, 107(11), pp.5232-5237.
Pärnamets, P., Johansson, P., Hall, L., Balkenius, C., Spivey, M.J. and Richardson, D.C., 2015. Biasing moral decisions by exploiting the dynamics of eye gaze. Proceedings of the National Academy of Sciences, 112(13), pp.4170-4175.
Rachlinski, J.J., 1996. Gains, losses, and the psychology of litigation. S. Cal. L. Rev., 70, p.113.
Rustichini, A., 2021. Working memory and attention in choice. Available at SSRN 3964802.
Samanez-Larkin, G.R. and Knutson, B., 2015. Decision making in the ageing brain: changes in affective and motivational circuits. Nature Reviews Neuroscience, 16(5), pp.278-289.
Shah, A.K., Mullainathan, S. and Shafir, E., 2012. Some consequences of having too little. Science, 338(6107), pp.682-685.
Shimojo, S., Simion, C., Shimojo, E. and Scheier, C., 2003. Gaze bias both reflects and influences preference. Nature neuroscience, 6(12), pp.1317-1322.
Shocker, A.D., Ben-Akiva, M., Boccara, B. and Nedungadi, P., 1991. Consideration set influences on consumer decision-making and choice: Issues, models, and suggestions. Marketing letters, 2(3), pp.181-197.
Skurnik, I., Yoon, C., Park, D.C. and Schwarz, N., 2005. How warnings about false claims become recommendations. Journal of Consumer Research, 31(4), pp.713-724.
Slovic, P. and Lichtenstein, S., 1983. Preference reversals: A broader perspective. The American Economic Review, 73(4), pp.596-605.
Steinberg, L., 2017. A social neuroscience perspective on adolescent risk-taking. In Biosocial Theories of Crime (pp. 435-463). Routledge.
Story, M. and French, S., 2004. Food advertising and marketing directed at children and adolescents in the US. International Journal of Behavioral Nutrition and Physical Activity, 1(1), pp.1-17.
Towal, R.B., Mormann, M. and Koch, C., 2013. Simultaneous modeling of visual saliency and value computation improves predictions of economic choice. Proceedings of the National Academy of Sciences, 110(40), pp.E3858-E3867.
Tranel, D., Bechara, A. and Denburg, N.L., 2002. Asymmetric functional roles of right and left ventromedial prefrontal cortices in social conduct, decision-making, and emotional processing. Cortex, 38(4), pp.589-612.
Tversky, A. and Kahneman, D., 1983. Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological review, 90(4), p.293.
Tversky, A. and Kahneman, D., 1985. The framing of decisions and the psychology of choice. In Behavioral decision making (pp. 25-41). Springer, Boston, MA.
Tversky, A. and Kahneman, D., 1989. Rational choice and the framing of decisions. In Multiple criteria decision making and risk analysis using microcomputers (pp. 81-126). Springer, Berlin, Heidelberg.
van de Vijver, I., Ridderinkhof, K.R., Harsay, H., Reneman, L., Cavanagh, J.F., Buitenweg, J.I. and Cohen, M.X., 2016. Frontostriatal anatomical connections predict age-and difficulty-related differences in reinforcement learning. Neurobiology of aging, 46, pp.1-12.
van Holst, R.J., van den Brink, W., Veltman, D.J. and Goudriaan, A.E., 2010. Why gamblers fail to win: a review of cognitive and neuroimaging findings in pathological gambling. Neuroscience & Biobehavioral Reviews, 34(1), pp.87-107.
Van Koppen, P.J., 1990. Risk taking in civil law negotiations. Law and Human Behavior, 14(2), pp.151-165.
