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Many of these studies used a wordassociation technique treatment lichen sclerosis purchase 100 ml mentat ds syrup otc, which involves presenting subjects with a target stimulus medicine in the 1800s cheap 100 ml mentat ds syrup visa, usually a word or very brief phrase and asking them to symptoms esophageal cancer buy mentat ds syrup 100 ml cheap provide the first thought or image that comes to 3 medications that cannot be crushed safe mentat ds syrup 100 ml mind. Following the elicitation of images, subjects are asked to rate each image they give on a scale ranging from very positive. This imagery method has been used successfully to measure the affective meanings that influence people’s preferences for different cities and states (Slovic et al. The cities in this example show a clear affective preference for San Diego over Denver. In one study, they found that the image score predicted the location of actualvacations during the next 18 months. Images, Ratings, and Summation Scores for One Respondent Note: Based on these summation scores, this person’s predicted preference for a vacation site would be San Diego. Subsequent studies have found affect-laden imagery elicited by word associations to be predictive of preferences for investing in new companies on the stock market (MacGregor, Slovic, Dreman, & Berry, 2000) and predictive of adolescents’ decisions to take part in health threatening and health-enhancing behaviors such as smoking and exercise, respectively (Benthin et al. However, the impressions themselves may vary not only in their valence, but also in the precision with which they are held. It turns out that the precision of an affective impression substantially impacts judgments. We refer to the distributional qualities of affective impressions and responses as affective mappings. In contrast, obnoxiousness will likely produce a more precise and more negative impression. Anderson (1981) has shown that the integration of multiple pieces of information into an impression of this sort can be described well by a weighted average model where separate weights are given to intelligence and obnoxiousness, respectively. Thus we would expect the impression produced by the combination of these two traits to be closer to the impression formed by obnoxiousness alone, reflecting greater weight given to obnoxiousness due to its smaller variance (more precise affective mapping). The meaning of a stimulus image appears to be reflected in the precision of the affective feelings associated with that image. More precise affective impressions reflect more precise meanings and carry more weight in impression formation, judgment, and decision making. Hsee (1996a, 1996b, 1998) developed the notion of evaluability to describe the interplay between the precision of an affective impression and its meaning or importance for judgment and decision making. Evaluability is illustrated by an experiment in which Hsee asked people to assume they were music majors looking for a used music dictionary. In a joint-evaluation condition, participants were shown two dictionaries, A and B (Table 23. Willingness-to-pay was far higher for Dictionary B, presumably because of its greater number of entries. However, when one group of participants evaluated only A and another group evaluated only B, the mean willingness to pay was much higher for Dictionary A. He argues that, without a direct comparison, the number of entries is hard to evaluate, because the evaluator does not have a precise notion of how good or how bad 10,000 (or 20,000) entries is. However, the defects attribute is evaluable in the sense that it translates easily into a precise good/bad response and thus it carries more weight in the independent evaluation. Most people find a defective dictionary unattractive and a like-new one attractive. Under joint evaluation, the buyer can see that B is far superior on the more important attribute, number of entries. According to the evaluability principle, the weight of a stimulus attribute in an evaluative judgment or choice is proportional to the ease or precision with which the value of that attribute (or a comparison on the attribute across alternatives) can be mapped into an affective impression. Evaluability can thus be seen as an extension of the general relationship between the variance of an impression and its weight in an impression-formation task (Mellers et al. Hsee’s work in evaluability is noteworthy because it shows that even very important attributes may not be used by a judge or decision maker unless they can be translated precisely into an affective frame of reference. As described in the next section, Hsee finds evaluability effects even with familiar attributes such as the amount of ice cream in a cup (Hsee, 1998). We also demonstrate similar effects with other familiar concepts such as amounts of money or human lives. This is a representation characterizing an attribute as a proportion or percentage of something, or as a probability. At the suggestion of Chris Hsee (personal communication), we refer to the strong effects of this type of representation asproportion dominance. Proportion (or probability) dominance was evident in the studies of gambles described at the beginning of this chapter. Ratings of a gamble’s attractiveness tend to be determined far more strongly by the probabilities of winning and losing than by the monetary payoffs. The curious finding that adding a small loss to a gamble increases its rated attractiveness, explained originally as a compatibility effect, can now be seen to fit well with the notions of affective mapping and evaluability. According to this view, a probability maps relatively precisely onto the attractiveness scale because probability has a lower and upper bound (0 and 1) and a midpoint below which a probability is “poor” or “bad”. People know where a given value, such as 7/36, falls within the bounds, and exactly what it means – “I’m probably not going to win. Thus, the impression formed by the gamble offering $9 to win with no losing payoff is dominated by the relatively precise and unattractive impression produced by the 7/36 probability of winning. However, adding a very small loss to the payoff dimension brings the $9 payoff into focus and thus gives it meaning. The combination of a possible $9 gain and a 5 loss is a very attractive win/loss ratio, leading to a relatively precise mapping onto the upper end of the scale. Whereas the imprecise mapping of the $9 carries little weight in the averaging process, the more precise and now favorable impression of ($9, 5) carries more weight, thus leading to an increase in the overall favorability of the gamble. The effect of adding a small loss to the gamble can also be explained by norm theory (Kahneman & Miller, 1986; Kahneman & Miller, Chapter 20, this volume). It asserts that the gamble with no loss is a relatively mediocre representative of the set of all positive gambles, whereas the gamble with a small loss is a relatively attractive member of the class of mixed (win/loss) gambles. Proportion dominance surfaces in a powerful way in a very different context, the life saving interventions studied by Fetherstonhaugh, Slovic, Johnson, and Friedrich (1997), Baron (1997), Jenni and Loewenstein (1997), and Friedrich et al. However, when two or more interventions were directly compared, number of lives saved become more important than proportion saved. Thus, number of lives saved, standing alone, appears to be poorly evaluable, as was the case for number of entries in Hsee’s music dictionaries. With a side-by-side comparison, the number of lives became clearly evaluable and important, as also happened with the number of dictionary entries. Slovic (unpublished), drawing on proportion dominance and the limited evaluability of numbers of lives, predicted (and found) that people, in a between-groups design, would more strongly support an airport-safety measure expected to save 98% of 150 lives at risk than a measure expected to save 150 lives. Saving 150 lives is diffusely good, and therefore only weakly evaluable, whereas saving 98% of something is clearly very good because it is so close to the upper bound on the percentage scale, and hence is readily evaluable and highly weighted in the support judgment. Subsequent reduction of the percentage of 150 lives that would be saved to 95%, 90%, and 85% led to reduced support for the safety measure but each of these percentage conditions still garnered a higher mean level of support than did the Save 150 Lives Condition (Table 23. Proportion Dominance and Airport Safety: Saving a Percentage of 150 Lives Receives Higher Support Ratings Than Does Saving 150 Lives. The Save 98% and Save 95% conditions were both significantly different from the Save 150 Lives condition atp <. Turning to a more mundane form of proportion dominance, Hsee (1998) found that an overfilled ice cream container with 7 oz of ice cream was valued more highly (measured by willingness to pay) than an underfilled container with 8 oz of ice cream (Fig. This “less is better effect” reversed itself when the options were juxtaposed and evaluated together. Thus, the proportion of the serving cup that was filled appeared to be more evaluable (in separate judgments) than the absolute amount of ice cream. When consequences carry sharp and strong affective meaning, as is the case with a lottery jackpot or a cancer, the opposite phenomenon occurs – variation in probability often carries too little weight. As Loewenstein, Weber, Hsee, and Welch (2001) observe, one’s images and feelings toward winning the lottery are likely to be similar whether the probability of winning is 1 in 10 million or 1 in 10,000. They further note that responses to uncertain situations appear to have an all or none characteristic that is sensitive to the possibility rather than the probability of strong positive or negative consequences, causing very small probabilities to carry great weight. This they argue, helps explain many paradoxical findings such as the simultaneous prevalence of gambling and the purchasing of insurance. It also explains why societal concerns about hazards such as nuclear power and exposure to extremely small amounts of toxic chemicals fail to recede in response to information about the very small probabilities of the feared consequences from such hazards. Support for these arguments comes from Rottenstreich and Hsee (2001), who show that, if the potential outcome of a gamble is emotionally powerful, its attractiveness or unattractiveness is relatively insensitive to changes in probability as great as from.

A Moreover medications of the same type are known as buy generic mentat ds syrup 100 ml line, parameters such as moisture content medicine nobel prize 2015 cheap mentat ds syrup 100 ml without prescription, material is in essence industrially compostable if it aeration symptoms rheumatoid arthritis order generic mentat ds syrup online, pH medications xl cheap mentat ds syrup line, and carbon to nitrogen ratio do not meets the following four criteria: need to be controlled. Each certifcation body produces its own labels which, though • Disintegration: it fragments into pieces smaller referring to the same norms, can be confusing for than 2 mm under controlled composting citizens. In addition, as outlined above this report gives preference to the term ‘compostable’ over ‘biodegradable’. The term ‘biodegradable’ itself describes only that a material can biodegrade into natural elements with the help of micro-organisms (see Appendix B). However, as such fossil-based compostable plastics represent a smaller segment of the market, they are not represented in Figure 17. Actual recyclability and compostability depends on after-use infrastructure in place. Incineration/energy recovery and landfll pathways not shown (possible with all plastics). Home composting not shown either (limited uptake today) 2 ‘Recyclable’ is used here as short-hand for ‘mechanically recyclable’. The alternative, chemical recycling, is not applied at scale today and has – with today’s technologies – typically signifcant economic and environmental limitations 3 Some fossil-based plastics are industrially compostable. First, the packaging up in plastics recycling streams since compostable is prone to be mixed with organic contents such packaging can interfere with recycling processes as food after use. Making packaging compostable with current material technology and after-use for such applications helps to return additional infrastructure. Even if only a fraction of this biological nutrients to re-enter the biosphere food waste could be returned to the soil through safely for decomposition to regenerate the soil and compostable packaging, this would make a big become valuable feedstock for a new cycle. Compostable packaging can be an important Compostable bags can be an important enabler enabler to return more nutrients of packaged in the collection of food waste from households contents to the soil. While plastic packaging itself and reduce the risk that non-compostable plastic contains little nutrients, the packaged contents bags fnd their way to industrial composting and often contain valuable organic nutrients. In certain that in Milan (see Box 10) have proven that both applications, food might be difcult to separate the amount of food waste collected separately from the packaging by default such as in cofee 206 Other applications are and the quality of the fnished compost can be capsules and teabags. Minimum compost quality levels for general events, fast food restaurants and canteens). In 2011, Milan had a separated food waste collection of 28 kg per inhabitant per year, resulting in a food waste collection rate of 19%. Food waste from private households was not collected and most of it could not be home composted since 80% of Milan’s inhabitants live in high-rise buildings with no outside space. As part of a project to increase the food waste collection rate, households were equipped with a vented bin with compostable plastic bags made with Novamont’s Mater-Bi material. People could then purchase further compostable bags or use compostable shopping bags from supermarkets. In order to promote the adoption of industrially compostable plastic bags, single-use non-compostable plastic bags were banned. The project has been successful and raised the separated food waste collection per inhabitant per year to 95 kg, more than tripling the collection of food waste. The number of plants in and recyclable after-use plastic streams should be Europe, for example, has increased from 3 in 1990 avoided. Hence, compostable packaging is more to 290 in 2015 with a combined capacity of 9 suitable in controlled or closed environments where 225 million tonnes per year. While critical today, the biogas yield, biogas production and electrical as certain plastics are both (technically) recyclable power equivalents have grown at an even faster and compostable, this constraint might become 226 pace (up to twice as fast). While non on the anaerobic digestion process can be found in compostable plastics could potentially be separated Appendix C. Second, appropriate home composting After collection, compostable packaging and the infrastructure might not be available, for example, biological nutrients from the packaged content in urban areas. For composting conditions allow for full degradation home compostable materials, there is the additional and the fnished compost fnds a use. As in industrial facilities are controlled and more a result, the anaerobic digestion process yields ‘favourable’ for the degradation process, more biogas in addition to the digestate that can be materials are industrially compostable than home used as fertiliser. Unless all materials in a region would natural gas that can be exported to the grid (biogas be home compostable (which is highly unlikely), to grid, BtG). One tonne of food waste (at 60% moisture) produces typically 300–500 tonnes of biogas (with methane concentration around 60%) and hence produces 1,260 kWh. This alignment can be digestion and composting food waste along with ensured by, amongst others, (fnancial) incentives industrially compostable packaging at large scale to foster cooperation. These initiatives have targets between composters and event organisers), shown integrated value chains, from individuals or, in the documented cases, synchronisation to material management companies and farmers was facilitated by local authorities providing a using the fertiliser. Further scale leveraged to further optimise processes and scale up of industrially compostable packaging could up the implementation of these initiatives. The main build on the lessons learnt from these successful take-away is that stakeholders along the value chain initiatives. Achieving a drastic reduction in leakage would require coordinated eforts along three dimensions: frst, improving after-use infrastructure in high-leakage countries, an urgently needed short term measure. Second, increasing the economic attractiveness of keeping the materials in the system. Third, reducing the negative efects of any likely remaining leakage by steering innovation towards truly ‘bio-benign’ materials, which represents an ambitious innovation challenge. The economic 8 million tonnes of plastics (of which estimates costs of these impacts need further assessment. The negative externalities remain there for centuries resulting in high also include entanglement and ingestion of plastics economic costs and causing harm to natural by various species. While the total economic impact is still 260 species are already known to be afected by unclear, initial studies suggest that it is at least in plastic debris through entanglement or ingestion’. As a consequence of such be to urgently improve after-use infrastructure in stabilised leakage, the cumulative total volume high-leakage countries. However, this measure in of plastics in the ocean would continue to rise isolation is likely not sufcient. Hence, ensuring that plastics do not escape Ocean Conservancy’s 2015 report Stemming the collection and reprocessing systems and end up Tide, even under the very best current scenarios in the ocean or other natural systems requires a for improving infrastructure, such measures would coordinated efort on multiple fronts. In addition, would contribute to a root-cause solution to dematerialisation and reuse are levers to ‘do more leakage. Improved economics make the build-up of with less plastics’ and hold the potential to reduce after-use collection and reprocessing infrastructure leakage proportionally with the amount of plastics economically more attractive. Such materials would avoid harm to natural mediated fragmentation in its current reincarnation systems in case they escape collection systems. Current ‘oxo leaves that have fallen from a tree or a banana peel degradable’ (or rather ‘oxo-fragmentable’) plastics that has been separated from its packaged content (as further explained in Appendix B) have not — the banana — such bio-benign materials would been proven truly benign, but rather have mostly safely and completely degrade after their useful led to fragmentation — increasing the quantity of life. However, its bio-benign characteristic step in reducing the harm of plastics that escape would reduce the negative efects on natural the collection system. Paper are materials that, besides full biodegradation in ofers inspiration — a widely used and recycled a composting test, reach 20% biodegradation in a packaging material that is relatively benign if leaked marine test within a period of six months, and at into natural systems (unless it contains substances least 70% disintegration. Diferent avenues might help reduce the harm No fnished product has yet been approved as of (unintentionally) leaked plastics. More product infuences the biodegradation time, which research would be needed to assess the exact is one of the criteria of marine biodegradability. Certain of these substances raise concerns about complex long-term exposure and compound efects on human health, as well as about their impact upon leakage into natural systems such as the ocean. While scientifc evidence on the exact implications of substances of concern is not always conclusive, there are sufcient indications that warrant further research into and accelerated development and application of safe alternatives. These research and innovation eforts would need to be complemented with enhanced transparency on the material content of plastics and, where relevant, the application of the precautionary principle to phase out specifc (sets of) substances raising concerns of acute negative efects. The concerns and potential upside for the industry and broader society associated with management of substances of concern are motivators for stakeholder action. These additives, which include fame led the plastic additives market in 2013 and is retardants, plasticisers, pigments, fllers, and projected to continue to be the largest market, with stabilisers, are used to improve the diferent an annual growth of 4. This concept involves risk associated with context and exposure, for which insights continue to evolve as the science progresses. Concerns about hazards of substances are inherently related to risk, context, and exposure. Individually, certain substances may cause harm if concentrations or length of exposure exceed a certain threshold.

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For example treatment 7th march bournemouth discount mentat ds syrup generic, Zillman and colleagues (for a review medications to treat bipolar quality mentat ds syrup 100 ml, see Zillman treatment junctional tachycardia cheap 100 ml mentat ds syrup otc, 1978) had subjects engage in various forms of exercise treatment yeast infection home generic mentat ds syrup 100 ml with mastercard. Shortly after the exercise, subjects’ heightened excitation level did not affect evaluative judgments, presumably reflecting that subjects were still aware of the source of their arousal. After some delay, however, judgments were affected by the residual arousal, suggesting that subjects misinterpreted their arousal as a reaction to the target, once the temporal distance of the exercise rendered this alternative source less accessible and plausible. Finally, the informational value of cognitive experiences, like ease or difficulty of recall, has also been found to depend on individuals’ assumptions about their source, as reviewed by Schwarz and Vaughn (Chapter 5, this volume). Throughout, the accumulating findings indicate that feelings and phenomenal experiences are an important source of information that individuals draw on in forming evaluative judgments, unless their informational value is called into question. Although the findings bearing on well-defined formal reasoning tasks (such as syllogistic reasoning, puzzles, or anagrams) are complex and inconsistent (see Clore et al. In general, individuals in a sad mood are more likely to use a systematic, data-driven strategy of information processing, with considerable attention to detail. In contrast, individuals in a happy mood are more likely to rely on preexisting general knowledge structures, using a top-down, heuristic strategy of information processing, with less attention to detail. These differences can again be traced to the informative functions of affective states (Bless, 1997; Schwarz, 1990, 2001). We usually feel bad when we encounter a threat of negative or a lack of positive outcomes, and feel good when we obtain positive outcomes and are not threatened by negative ones. As a result, our moods reflect the state of our environment and being in a bad mood signals a problematic situation, whereas being in a good mood signals a benign situation. A growing body of research suggests that individuals’ thought processes are tuned to meet the situational requirements signalled by their feelings. When negative feelings signal a problematic situation, the individual is likely to attend to the details at hand, investing the effort necessary for a careful analysis. In contrast, when positive feelings signal a benign situation, the individual may see little need to engage in cognitive effort, unless this is required by other current goals. Therefore, the individual may rely on preexisting knowledge structures that worked well in the past, and may prefer simple heuristics over more effortful, detail-oriented judgmental strategies. Numerous studies are compatible with this general perspective, as illustrated later. Importantly, mood effects on processing style are eliminated when the informational value of the mood is undermined (Sinclair, Mark, & Clore 1994), paralleling the findings in the judgment domain discussed previously. This finding supports the informative functions logic and is difficult to reconcile with competing approaches that trace mood effects on processing style to differential influences of happy and sad moods on individuals’ cognitive capacity. Both approaches would predict main effects of mood, rather than effects that are contingent on the mood’s perceived informational value. Impression Formation and Stereotyping In forming an impression of others, we may either rely on detailed information about the target person or simplify the task by drawing on preexisting knowledge structures, such as stereotypes pertaining to the target’s social category. Consistent with the mentioned perspective, being in a good mood has been found to increase stereotyping consistently. In contrast, being in a sad mood reliably decreases stereotyping and increases the use of individuating information (for a review, see Bless, Schwarz, & Kemmelmeier, 1996). Across many person-perception tasks, individuals in a chronic or temporary sad mood have been found to make more use of detailed individuating information, show less halo effects, and are less influenced by the order of information presentation and more accurate in performance appraisals than individuals in a happy mood, with individuals in a neutral mood falling in between (see Sinclair & Mark, 1992 for a review). Similar findings have been obtained for individuals’ reliance on scripts pertaining to typical situations (such as having dinner in a restaurant) versus their reliance on what actually transpired in the situation (Bless et al. Throughout, individuals in a good mood are more likely to rely on preexisting general knowledge structures, proceeding on a “businessas-usual” routine; conversely, individuals in a sad mood are more likely to pay close attention to the specifics at hand, much as one would expect when negative feelings provide a problem signal. In general, a message that presents strong arguments is more persuasive than a message that presents weak arguments, provided that recipients are motivated to process the content of the message and to elaborate on the arguments. If recipients do not engage in message elaboration, the advantage of strong over weak arguments is eliminated (for reviews, see Eagly & Chaiken, 1993; Petty & Cacioppo, 1986). Numerous studies demonstrate that sad individuals are more likely to engage in spontaneous message elaboration than happy individuals, with individuals in a neutral mood falling in between (for a review see Schwarz, Bless, & Bohner, 1991). As a result, sad individuals are strongly influenced by compelling arguments and not influenced by weak arguments, whereas happy individuals are moderately, but equally, influenced by both. Therefore, a strong message fares better with a sad than with a happy audience, but if communicators have nothing compelling to say they better put recipients into a good mood. More important, happy individuals’ spontaneous tendency not to think about the arguments in much detail can be overridden by other goals. What characterizes the information processing of happy individuals is not a general cognitive or motivational impairment, but a tendency to spontaneously rely on simplifying heuristics and general knowledge structures in the absence of goals that require otherwise (Bless & Schwarz, 1999). Other Judgment and Decision Tasks these mood-induced differences in spontaneous processing style are likely to affect individuals’ performance on many judgment and decision tasks. For example, Luce, Bettman, and Payne (1997) observed that “decision processing under increasing negative emotion both becomes more extensive and proceeds more by focusing on one attribute at a time” (p. Moreover, Hertel, Neuhof, Theuer, and Kerr (2000) observed pronounced mood effects on individuals’ decision behavior in a chicken game. Consistent with the present theorizing, their findings suggest that individuals in a happy mood are likely to heuristically imitate the behavior of other players, whereas individuals in a sad mood base their moves on a rational analysis of the structure of the game. Note, however, that more extensive reasoning about a task does not always result in better solutions. As an example, consider the well-known phenomenon of anchoring effects in quantitative judgments (Tversky & Kahneman, 1974). As Strack and Mussweiler (1997; Mussweiler & Strack, 1999) demonstrated, this bias is due to a process of positive hypothesis testing. If so, this bias may be exaggerated the more individuals engage in elaborative hypothesis testing. Confirming this prediction, Bodenhausen, Gabriel, and Lineberger (1999) observed that sad individuals showed more pronounced anchoring effects than individuals in a neutral mood, presumably because their sad mood fostered more elaborative hypothesis testing, thus rendering more hypothesis-consistent information accessible. As these examples illustrate, the differential processing styles elicited by being in a happy or sad mood can increase as well as decrease judgmental biases, depending on the nature of the task. Future research will benefit from testing the impact of affective states across a wider variety of tasks. Beyond Moods As in the case of evaluative judgment, the conceptual logic can be extended from global moods to other feelings, including specific emotions and bodily sensations. Theoretically, experiencing a specific emotion can be expected to inform the individual that the appraisal pattern underlying this emotion has been met (Schwarz, 1990): Feeling angry, for example, informs us that somebody has faulted us and angry individuals have been found to assign more responsibility to human actors than to situational circumstances, as noted earlier (Keltner et al. We may therefore expect that specific emotions elicit processing strategies that are tuned to meet the requirements entailed by the appraisal pattern that underlies the respective emotion. To date, experimental research bearing on this possibility is limited, although the available data are generally consistent with this proposal. Recall that earlier research into mood and persuasion documented more systematic message processing under sad rather than happy moods. Extending this work, Tiedens and Linton (in press) noted that the appraisal pattern underlying sadness entails a sense of uncertainty, whereas other negative emotions, like anger or disgust, do not. Consistent with this proposal, they found that uncertainty-related emotions elicited more systematic message processing, whereas other negative emotions did not. Presumably, when we are angry or disgusted, we know what our feeling is about and see no need to engage in detailed processing of unrelated information. Sadness or anxiety, however, entail a sense of uncertainty and hence motivate the kind of detail-oriented systematic processing observed in earlier research. Although sadness and anxiety share an uncertainty appraisal, they differ in other respects. In general, sadness is a response to the loss or absence of a reward, whereas anxiety is a response to threats. As a result, sadness may prompt a goal of reward acquisition, whereas anxiety may prompt a goal of uncertainty reduction. They provided sad or anxious participants with a choice task that required a trade-off between risk and rewards. As expected, they observed that sad individuals pursued a goal of reward acquisition and preferred high risk/high reward options over any other combination. Conversely, anxious individuals pursued a goal of uncertainty reduction and preferred low-risk/low-reward options over any other combination. These findings demonstrate that incidental feelings, induced by an unrelated task, can influence which goal an individual pursues.

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Subjects then estimated the probability that Linda works as either a journalist or realtor symptoms 2dpo discount mentat ds syrup on line. Whereas the description of Linda may appear highly similar to medicine garden best buy for mentat ds syrup journalist symptoms 5dp5dt fet buy mentat ds syrup 100 ml amex, it may in fact appear less similar to symptoms 0f colon cancer order cheapest mentat ds syrup and mentat ds syrup the disjunction journalist or realtor, because the nonmatching componentrealtor dilutes the strong similarity with journalist. Such dilution is unlikely to occur in class judgments, where similarity does not form the basis of the judgments. Consistent with their predictions, judgment based on similarity yielded extreme forms of subadditivity. Judgments based on similarity often showed nonmonotonicity of support, in which support for a disjunction is less than the support for one of its components – a pattern analogous to the conjunction fallacy, but evaluated at the level of support rather than probability (cf. Another stream of research has examined the determinants of subadditivity for residual hypotheses, defined as the complement of a particular hypothesis. Specifically, they tested a linear discounting model in which the subadditivity weightwA for a residual hypothesis decreases with the support for the focal hypothesis that defines the residual: the subadditivity weightwA represents the degree of subadditivity for the residual hypothesis A (read as “notA” or “the complement of A”). For example, if there are four mutually exclusive and exhaustive hypothesesA, B, C, and D, then wA = s(A)/[s(B) + s(C) + s(D)]. The linear discounting model was intended to capture the intuition that when evidence for the focal possibility is strong, the residual hypothesis. Brenner and Koehler (1999) examined subadditivity of residual hypotheses in greater detail. Rather than measuring subadditivity for a residual hypothesis with the global weight wA, Brenner and Koehler examined local weights that measure the specific contribution of each component included within the residual. Using local weights, the total support for a residual hypothesis can be expressed as a weighted sum of its components’ support values: In this formulation, the local weightw(B, A) is interpreted as, “the weight of componentB within the residual hypothesisA. Properties analogous to subadditivity and enhancement were found to hold for local weights as well as global weights. A generalization of the linear discounting model was able to successfully account for most of the variability in these local weights, yielding a parsimonious model of the “microstructure” of support for residual hypotheses. Koehler (2000) examined the effects of several evidential features on the degree of subadditivity. In a simulated medical diagnosis task, participants judged the likelihood of a designated diagnosis (flu strain 1, 2, or 3) on the basis of a pattern of symptoms. Over many trials, participants judged the likelihood of each of the three possible flu strains for a given pattern of symptoms; the total of these judged probabilities reflects the degree of subadditivity of the residual hypothesis. Subadditivity was greater when symptoms were in conflict with each other – for example when a pattern of symptoms included both cough (implicating flu strain 1) and sore throat (implicating flu strain 2). The effect of cue conflict was largely accounted for by the linear discounting model of Koehler et al. According to this interpretation, cue conflict leads to greater perceived support for the focal hypothesis, which in turn produces greater discounting of the residual hypothesis. Previous studies have found that the degree of subadditivity reliably depends on several factors, including the number of components in a hypothesis, the similarity of those components to each other and to the evidence, the strength of the focal hypothesis, the conflict among evidential cues, and whether the judgment is elicited in terms of probability or relative frequency. These seemingly unrelated factors all influence either (1) the ease with which a hypothesis is naturally or spontaneously broken into pieces, or (2) the extent to which compelling evidence is seen to support the components of a disjunctive hypothesis. The more easily evidence is seen to support individual components of a “packed” hypothesis, the less subadditivity is expected. Put another way: When a hypothesis is unpacked into components, the unpacking effect should be greatest when the act of unpacking recruits evidence for the unpacked components that would not be brought to mind by the packed hypothesis. Thus, evidence that encourages spontaneous unpacking of a hypothesis and supports individual components should yield little or no subadditivity. Extensions of Support Theory We now consider two recent attempts to expand the scope of support theory. The first extends support theory to predict the accuracy or calibration of subjective probabilities; the second incorporates support theory into a belief-based model of choice under uncertainty. Support theory, as discussed thus far, addresses the coherence of a set of probability judgments rather than their correspondence to the actual likelihood of outcomes. The theory makes no commitment, for example, to whether unpacking a hypothesis will yield more or less accurate judgments of its actual probability. As formulated, support theory cannot be used to investigate the calibration of subjective probabilities, a topic of considerable interest in the field of judgment under uncertainty (for reviews, see Harvey, 1997; McClelland & Bolger, 1994, Lichtenstein, Fischhoff, & Phillips, 1982; Wallsten & Budescu, 1983). Calibration is defined as the match between the subjective probability of an event and the corresponding objective probability of that event, as measured either by empirical relative frequencies or via a normative model such as Bayes theorem. To apply support theory to the study of calibration, Brenner (1995) developed a random support model that allows prediction of the accuracy of subjective probabilities. The random support model assumes that the support for a particular hypothesis is likely to vary from judgment occasion to judgment occasion; consequently, support is represented as a random variable to reflect variability in evidence strength. Similar to the approach of Ferrell and McGoey (1980), the random support model uses a signal-detection framework, in which different distributions of support represent the strength of evidence for correct and incorrect hypotheses. The separation between these distributions reflects the judge’s ability to discriminate correct from incorrect hypotheses. Unlike signal detection theory and the Ferrell and McGoey (1980) approach, however, the random support model does not invoke thresholds for converting the underlying random variable into a judgment; rather, support is mapped directly into a probability judgment based on the support theory representation P(A, B) = s(A)/[s(A) + s(B)]. This yields a parsimonious model in which the parameters describing the underlying distributions of support can be used to characterize the judgment domain. Furthermore, because direct assessments of support can be elicited (as described previously), the distributions of support derived from probability judgments may be validated against these direct support assessments. Brenner (1995) applied the random support model to predicting calibration performance in a number of different judgment domains and contexts. A twoparameter version of the model closely reproduces calibration curves observed in the standard two-alternative judgment task, in which the judge selects which of two alternatives is correct and then assesses the probability of that alternative on a “half-range” (50 to 100%) probability scale. An extension with additional parameters likewise produces a close fit to data for zero-alternative. Koehler, Brenner, and Griffin (Chapter 39, this volume) use the random support model to estimate patterns of miscalibration by experts making probability judgments in their domains of expertise. One attractive feature of the random support model is that its parameters have meaningful psychological interpretations. In the case of judging a designated hypothesis (such as the likelihood of rain), for instance, the parameters represent the judge’s discrimination ability. These parameters provide a convenient language for evaluating sources of observed miscalibration, and could also guide attempts to develop corrective procedures. One of the primary motivations for the study of subjective probability is the presumption that people’s likelihood judgments of uncertain events influence the decisions that depend on those events. Accordingly, support theory has recently been used as the basis for a belief-based account of decision making under uncertainty (Fox & Tversky, 1998; Tversky & Fox, 1995; Wu & Gonzalez, 1999). This work focuses on people’s choices among uncertain prospects in which the probabilities of different outcomes are not known but instead must be assessed by the decision maker. By varying the value of the certain gain and examining its effect on people’s choices, a certainty equivalent can be determined such that the decision maker is indifferent between the sure gain and the uncertain prospect. A number of studies (Fox, 1999; Fox, Rogers, & Tversky, 1996; Fox & Tversky, 1998; Tversky & Fox, 1995; Wu & Gonzalez, 1999) using this method have revealed what Tversky and Wakker (1995) call bounded subadditivity: An event has greater impact on choices when it turns impossibility into possibility, or possibility into certainty than when it merely makes a possibility more likely in the intermediate range of the probability scale. Bounded subadditivity implies that decomposing an uncertain prospect into subprospects by unpacking the event on which the payoffs are contingent increases the attractiveness of the set of prospects. This pattern for certainty equivalents is directly analogous to the effect of unpacking on probability judgments. For example, unpacking the hypothesis “Microsoft’s stock price will close below $94” into two component hypotheses, “Microsoft’s stock price will close below $88” and “Microsoft’s stock price will close between $88 and $94,” produced a greater total judged probability. Fox and Tversky (1998) and Wu and Gonzalez (1999) offer a two-stage belief-based model of decision making under uncertainty that combines insights from both support theory and prospect theory (Kahneman & Tversky, 1979; Tversky & Kahneman, 1992). The model assumes that the judged probabilities of the events involved in uncertain prospects are assessed in a manner consistent with support theory, and that the resulting subjective probabilities are then incorporated into choices according to the decision weighting function of prospect theory. Furthermore, Fox (1999) showed that such choices can even be reconstructed from direct support ratings of the kind discussed previously. Several applied studies have also shown that unpacking uncertain events can influence decisions in domains such as sports prediction (Ayton, 1997), insurance (Johnson, Hershey, Meszaros, & Kunreuther, 1993), and medical diagnosis (Redelmeier, Koehler, Liberman, & Tversky, 1995). For example, in an analysis of bookmakers’ published odds on soccer matches, Ayton (1997) found that the implied probability associated with an outcome such as England beating Switzerland in their upcoming match increased when the outcome was unpacked (based on half-time leader or on specific final scores). To the extent that published odds are driven by the market for various gambles, this observation implies that unpacking a hypothesis makes it appear more attractive as a wager. These studies suggest that the effect of unpacking captured by support theory has predictable consequences for decisions under uncertainty as well as for judgments of probability. The belief-based model of Fox and Tversky (1998) provides a detailed quantitative framework for applying support theory to predicting choices.

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