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Brain cells' multitasking key to understanding overall brain function | Machines Like Us

Brain cells' multitasking key to understanding overall brain function | Machines Like Us | Bounded Rationality and Beyond | Scoop.it

A region of the brain known to play a key role in visual and spatial processing has a parallel function: sorting visual information into categories, according to a new study by researchers at the University of Chicago. ....

"There has long been a tendency to look at the many distinct anatomical areas of the cerebral cortex of the brain and to assume that each area is like a specialized module that plays a very specific function." Freedman said. "Our results support the growing sense that most, if not all, of these brain areas have multiple overlapping roles."

A brain that includes such overlapping functional centers may be more efficient, Freedman suggests. "It makes mapping these regions more complicated for scientists like us, but it may boost the brain's capacity. If each area can do a number of different things, you can squeeze a lot more function into the same space."

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News on the effects of bounded rationality in economics and business, relationships and politics
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Tax Compliance and Public Goods Provision -- An Agent-based Econophysics Approach

We calculate the dynamics of tax evasion within a multi-agent econophysics model which is adopted from the theory of magnetism and previously has been shown to capture the main characteristics from agent-based based models which build on the standard Allingham and Sandmo approach. In particular, we implement a feedback of public goods provision on the decision-making of selfish agents which aim to pursue their self interest. Our results imply that such a feedback enhances the moral attitude of selfish agents thus reducing the percentage of tax evasion. Two parameters govern the behavior of selfish agents, (i) the rate of adaption to changes in public goods provision and (ii) the threshold of perception of public goods provision. Furtheron we analyze the tax evasion dynamics for different agent co mpositions and under the feedback of public goods provision. We conclude that policymakers may enhance tax compliance behavior via the threshold of perception by means of targeted public relations.

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Time-Inconsistent Planning: A Computational Problem in Behavioral Economics

In many settings, people exhibit behavior that is inconsistent across time --- we allocate a block of time to get work done and then procrastinate, or put effort into a project and then later fail to complete it. An active line of research in behavioral economics and related fields has developed and analyzed models for this type of time-inconsistent behavior. 
Here we propose a graph-theoretic model of tasks and goals, in which dependencies among actions are represented by a directed graph, and a time-inconsistent agent constructs a path through this graph. We first show how instances of this path-finding problem on different input graphs can reconstruct a wide range of qualitative phenomena observed in the literature on time-inconsistency, including procrastination, abandonment of long-range tasks, and the benefits of reduced sets of choices. We then explore a set of analyses that quantify over the set of all graphs; among other results, we find that in any graph, there can be only polynomially many distinct forms of time-inconsistent behavior; and any graph in which a time-inconsistent agent incurs significantly more cost than an optimal agent must contain a large "procrastination" structure as a minor. Finally, we use this graph-theoretic model to explore ways in which tasks can be designed to help motivate agents to reach designated goals.

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Improving detection of influential nodes in complex networks

Recently an increasing amount of research is devoted to the question of how the most influential nodes (seeds) can be found effectively in a complex network. There are a number of measures proposed for this purpose, for instance, high-degree centrality measure reflects the importance of the network topology and has a reasonable runtime performance to find a set of nodes with highest degree, but they do not have a satisfactory dissemination potentiality in the network due to having many common neighbors (CN(1)) and common neighbors of neighbors (CN(2)). This flaw holds in other measures as well. In this paper, we compare high-degree centrality measure with other well-known measures using ten datasets in order to find a proportion for the common seeds in the seed sets obtained by them. We, thereof, propose an improved high-degree centrality measure (named \textit{DegreeDistance}) and improve it to enhance accuracy in two phases, FIDD and SIDD, by put a threshold on the number of common neighbors of already-selected seed nodes and a non-seed node which is under investigation to be selected as a seed as well as considering the influence score of seed nodes directly or through their common neighbors over the non-seed node. To evaluate the accuracy and runtime performance of DegreeDistance, FIDD, and SIDD, they are applied to eight large-scale networks and it finally turns out that SIDD dramatically outperforms other well-known measures and evinces comparatively more accurate performance in identifying the most influential nodes.
  
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Ants Swarm Like Brains Think - Issue 23: Dominoes - Nautilus

Ants Swarm Like Brains Think - Issue 23: Dominoes - Nautilus | Bounded Rationality and Beyond | Scoop.it

Deborah Gordon spent the morning of August 27 watching a group of harvester ants foraging for seeds outside the dusty town of Rodeo, N.M. Long before the first rays of sun hit the desert floor, a group of patroller ants was already on the move. Their task was to find out whether the area near the nest was free from flash floods, high winds, and predators. If they didn’t return to the nest, departing foragers would know it wasn’t safe to go search for food.

When the patrollers returned and the first foragers did leave, they scattered in all directions, hunting for the fat-laden, energy-rich seeds on which the colony depends. Other foragers waited in the entrance of the nest for the first wave to return. If lots of food were nearby, foragers would return and depart quickly, creating a massive chain reaction. If food was scarce, however, the second group of foragers might not leave the nest at all.

“It’s a brilliant system. The ants can take advantage of sudden windfalls of food but they don’t waste energy and resources if there’s nothing there,” said Gordon, who is an ecologist at Stanford University.

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Konstantinos Katsikopoulos on decision theory - YouTube

At the Summer Institute on Bounded Rationality junior researchers discuss how people make everyday decisions. This forum for PhD students and postdocs took place from July 3 2012 at the Max Planck Institute for Human Development in Berlin. In his talk Konstantinos Katsikopoulos, professor at the Max Planck Institute for Human Development, argues that standard decision theory should be combined with rules of thumb and how this can be achieved. 

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What Works Cities

What Works Cities | Bounded Rationality and Beyond | Scoop.it

BUT THEY SHARE THE SAME MISSION:
TO SERVE CITIZENS IN THE MOST EFFECTIVE WAYS POSSIBLE.

Join leading cities across America that are using data and evidence to improve results for their residents.

What Works Cities helps you build on the work you're doing—to go further with what you've got.

What Works Cities is designed to accelerate Cities’ use of data and evidence to improve people’s lives. Bloomberg Philanthropies has assembled an unparalleled group of leading practitioners to focus on your goals and your citizens. They are, simply, world-class partners for world-class cities. Behavioural Insights Team Harvard Kennedy School Government Performance Lab Results for America …
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Destructive Behavior in a Fragile Public Good Game

Abstract: Socially destructive behavior in a public good environment - like damaging public goods - is an underexposed phenomenon in economics. In an experiment we investigate whether such behavior can be influenced by the very nature of an environment. To that purpose we use a Fragile Public Good (FPG) game which puts the opportunity for destructive behavior (taking) on a level playing field with constructive behavior (contributing). We find substantial evidence of destructive decisions, sometimes leading to sour relationships characterized by persistent hurtful behavior. While positive framing induces fewer destructive decisions, shifting the selfish Nash towards minimal taking doubles its share to more than 20%. Female subjects are found to be more inclined to use destructive decisions. Finally, subjects’ social value orientation turns out to be partly predictive of (at least initial) destructive choices.

 

Downloads: (external link)
ftp://ftp.gate.cnrs.fr/RePEc/2014/1429.pdf 

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Cognitive Bubble

Abstract: Smith et al. (1988) reported large bubbles and crashes in experimental asset markets, a result that has been replicated by a large literature. Here we test whether the occurrence of bubbles depends on the experimental subjects' cognitive sophistication. In a two-part experiment, we rst run a battery of tests to assess the subjects' cognitive sophistication and classify them into low or high levels of cognitive sophistication. We then invite them separately to two asset market experiments populated only by subjects with either low or high cognitive sophistication. We observe classic bubble- crash patterns in the sessions populated by subjects with low levels of cognitive sophistication. Yet, no bubbles or crashes are observed with our sophisticated subjects. This result lends strong support to the view that the usual bubbles and crashes in experimental asset markets are caused by subjects' confusion and, therefore, raises some doubts about the external validity of this type of experiments.Downloads: (external link)
http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2015-006.pdf  ;
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Major health benefits of music uncovered | Newsroom - McGill University

Major health benefits of music uncovered | Newsroom - McGill University | Bounded Rationality and Beyond | Scoop.it

In the first large-scale review of 400 research papers in the neurochemistry of music, a team led by Prof. Daniel J. Levitin of McGill University’s Psychology Dept. has been able to show that playing and listening to music has clear benefits for both mental and physical health. In particular, music was found both to improve the body’s immune system function and to reduce levels of stress. Listening to music was also found to be more effective than prescription drugs in reducing anxiety prior to surgery.
 
“We’ve found compelling evidence that musical interventions can play a health care role in settings ranging from operating rooms to family clinics,” says Prof. Levitin. “But even more importantly, we were able to document the neurochemical mechanisms by which music has an effect in four domains: management of mood, stress, immunity and as an aid to social bonding.”

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[cs/0405018] Modeling Chaotic Behavior of Stock Indices Using Intelligent Paradigms

The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using several connectionist paradigms and soft computing techniques. To demonstrate the different techniques, we considered Nasdaq-100 index of Nasdaq Stock MarketS and the S&P CNX NIFTY stock index. We analyzed 7 year's Nasdaq 100 main index values and 4 year's NIFTY index values. This paper investigates the development of a reliable and efficient technique to model the seemingly chaotic behavior of stock markets. We considered an artificial neural network trained using Levenberg-Marquardt algorithm, Support Vector Machine (SVM), Takagi-Sugeno neuro-fuzzy model and a Difference Boosting Neural Network (DBNN). This paper briefly explains how the different connectionist paradigms could be formulated using different learning methods and then investigates whether they can provide the required level of performance, which are sufficiently good and robust so as to provide a reliable forecast model for stock market indices. Experiment results reveal that all the connectionist paradigms considered could represent the stock indices behavior very accurately.
  
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A meta-analysis of state-of-the-art electoral prediction from Twitter data

Electoral prediction from Twitter data is an appealing research topic. It seems relatively straightforward and the prevailing view is overly optimistic. This is problematic because while simple approaches are assumed to be good enough, core problems are not addressed. Thus, this paper aims to (1) provide a balanced and critical review of the state of the art; (2) cast light on the presume predictive power of Twitter data; and (3) depict a roadmap to push forward the field. Hence, a scheme to characterize Twitter prediction methods is proposed. It covers every aspect from data collection to performance evaluation, through data processing and vote inference. Using that scheme, prior research is analyzed and organized to explain the main approaches taken up to date but also their weaknesses. This is the first meta-analysis of the whole body of research regarding electoral prediction from Twitter data. It reveals that its presumed predictive power regarding electoral prediction has been rather exaggerated: although social media may provide a glimpse on electoral outcomes current research does not provide strong evidence to support it can replace traditional polls. Finally, future lines of research along with a set of requirements they must fulfill are provided.
  
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Social Media and the Elections

In the United States, social media sites—such as Facebook, Twitter, and YouTube—are currently being used by two out of three people (1), and search engines are used daily (2). Monitoring what users share or search for in social media and on the Web has led to greater insights into what people care about or pay attention to at any moment in time. Furthermore, it is also helping segments of the world population to be informed, to organize, and to react rapidly. However, social media and search results can be readily manipulated, which is something that has been underappreciated by the press and the general public.

In times of political elections, the stakes are high, and advocates may try to support their cause by active manipulation of social media. For example, altering the number of followers can affect a viewer's conclusion about candidate popularity. Recently, it was noted that the number of followers for a presidential candidate in the United States surged by over 110 thousand within one single day, and analysis showed that most of these followers are unlikely to be real people (3).

 
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The Upside to Right-Sizing

The Upside to Right-Sizing | Bounded Rationality and Beyond | Scoop.it
As counter intuitive as it may seem, many financial advisors have achieved substantial breakthroughs on a multitude of levels by disassociating from certain clients who were no longer a good fit. Especially for an advisor who has hit a plateau with his or her business, often the best way to increase the amount of money they were managing was to decrease the number of relationships they were managing. And in the process, these same advisors were able to project scarcity to their clients and prospective clients and ensure those people focus on what the advisors are worth rather than what they c
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Prospect Theory for Online Financial Trading

Prospect theory is widely viewed as the best available descriptive model of how people evaluate risk in experimental settings. According to prospect theory, people are risk-averse with respect to gains and risk-seeking with respect to losses, a phenomenon called "loss aversion". Despite of the fact that prospect theory has been well developed in behavioral economics at the theoretical level, there exist very few large-scale empirical studies and most of them have been undertaken with micro-panel data. Here we analyze over 28.5 million trades made by 81.3 thousand traders of an online financial trading community over 28 months, aiming to explore the large-scale empirical aspect of prospect theory. By analyzing and comparing the behavior of winning and losing trades and traders, we find clear evidence of the loss aversion phenomenon, an essence in prospect theory. This work hence demonstrates an unprecedented large-scale empirical evidence of prospect theory, which has immediate implication in financial trading, e.g., developing new trading strategies by minimizing the effect of loss aversion. Moreover, we introduce three risk-adjusted metrics inspired by prospect theory to differentiate winning and losing traders based on their historical trading behavior. This offers us potential opportunities to augment online social trading, where traders are allowed to watch and follow the trading activities of others, by predicting potential winners statistically based on their historical trading behavior rather than their trading performance at any given point in time.
  
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Quantum Information Biology: from information interpretation of quantum mechanics to applications in molecular biology and cognitive psychology

We discuss foundational issues of quantum information biology (QIB) -- one of the most successful applications of the quantum formalism outside of physics. QIB provides a multi-scale model of information processing in bio-systems: from proteins and cells to cognitive and social systems. This theory has to be sharply distinguished from "traditional quantum biophysics". The latter is about quantum bio-physical processes, e.g., in cells or brains. QIB models the dynamics of information states of bio-systems. It is based on the quantum-like paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all scales, from molecular biology and genetics/epigenetics to cognitive psychology and behavioral economics. We argue that the information interpretation of quantum mechanics (its various forms were elaborated by Zeilinger and Brukner, Fuchs and Mermin, and D' Ariano) is the most natural interpretation of QIB. We also point out that QBIsm (Quantum Bayesianism) can serve to find a proper interpretation of bio-quantum probabilities. Biologically QIB is based on two principles: a) adaptivity; b) openness (bio-systems are fundamentally open). These principles are mathematically represented in the framework of a novel formalism -- quantum adaptive dynamics which, in particular, contains the standard theory of open quantum systems as a special case of adaptivity (to environment).

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Online Social Network Analysis: A Survey of Research Applications in Computer Science

The emergence and popularization of online social networks suddenly made available a large amount of data from social organization, interaction and human behaviour. All this information opens new perspectives and challenges to the study of social systems, being of interest to many fields. Although most online social networks are recent (less than fifteen years old), a vast amount of scientific papers was already published on this topic, dealing with a broad range of analytical methods and applications. This work describes how computational researches have approached this subject and the methods used to analyse such systems. Founded on a wide though non-exaustive review of the literature, a taxonomy is proposed to classify and describe different categories of research. Each research category is described and the main works, discoveries and perspectives are highlighted.
  
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The Pychology of Economic Forecasting

Is the imprecision of economic forecasts due to the judgments of ‘biased’ decision makers? This study explores decision-making among expert forecasters in Sweden using semi-structured interviews. The results indicate that forecasters’ decision
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Outsmart Your Own Biases

Outsmart Your Own Biases | Bounded Rationality and Beyond | Scoop.it

How to broaden your thinking and make better decisions. 

Suppose you’re evaluating a job candidate to lead a new office in a different country. On paper this is by far the most qualified person you’ve seen. Her responses to your interview questions are flawless. She has impeccable social skills. Still, something doesn’t feel right. You can’t put your finger on what—you just have a sense. How do you decide whether to hire her?

You might trust your intuition, which has guided you well in the past, and send her on her way. That’s what most executives say they’d do when we pose this scenario in our classes on managerial decision making. The problem is, unless you occasionally go against your gut, you haven’t put your intuition to the test. You can’t really know it’s helping you make good choices if you’ve never seen what happens when you ignore it.

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Computational Neuropsychology, Studying Emergence | SciTech Connect

Computational Neuropsychology, Studying Emergence | SciTech Connect | Bounded Rationality and Beyond | Scoop.it
Warren Tryon, author of Cognitive Neuroscience and Psychotherapy, dives into computational neuropsychology, discussing emergence and synaptic reorganization.

It is not enough to call for the study of emergence as I have done in my appeal for a paradigm shift in my book,Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory and in some of my previous blogs. One must also provide tools and some direction for using them to get the ball rolling.

Every parallel-distributed processing connectionist neural network (PDP-CNN) model that I have encountered has focused on the properties of the fully trained “adult” model rather than the process by which these properties emerged. This is because the authors of these simulations have presented their models as demonstration proofs that artificial neural networks are capable of performing certain functions. I agree that this is a necessary first step. It would be premature to study the emergent process unless, or until, one first demonstrated that the network in question is capable of generating the desirable psychological properties. But now that so many psychological and behavioral phenomena have been effectively simulated using PDP-CNN models, it is time to ask how these properties emerge. This line of inquiry is needed to generate full scientific explanations of these psychological and behavioral phenomena.

 
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How Does Aging Affect Financial Decision Making? | Center for Retirement Research

How Does Aging Affect Financial Decision Making? | Center for Retirement Research | Bounded Rationality and Beyond | Scoop.it
Abstract: The brief’s key findings are: *With the shift from traditional pensions to 401(k) plans, the welfare of retirees depends increasingly on their ability to make sound financial decisions. *Using a dataset that follows a group of older individuals in the Chicago area, the analysis examines how aging affects financial decision making. *Participants who suffer cognitive decline experience a reduction in their financial literacy but no change in their confidence in managing their money. *Perhaps not surprisingly then, while they are more likely to get help with financial decisions, more than half retain primary responsibility for managing their money. 
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The Dark Side of Competition for Status

Abstract: Unethical behavior within organizations is not rare. We investigate experimentally the role of status-seeking behavior in sabotage and cheating activities aiming at improving one’s performance ranking in a flat-wage environment. We find that average effort is higher when individuals are informed about their relative performance. However, ranking feedback also favors disreputable behavior. Some individuals do not hesitate to incur a cost to improve their rank by sabotaging others’ work or by increasing artificially their own performance. Introducing sabotage opportunities has a strong detrimental effect on performance. Therefore, ranking incentives should be used with care. Inducing group identity discourages sabotage among peers but increases in-group rivalry.

ftp://ftp.gate.cnrs.fr/RePEc/2014/1431.pdf

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15 Lessons from Behavioural Economics

The following deck was used by @tjalve in our internal #teachme session. It covers 15 lessons from Behavioural Economics you can apply to your ongoing projects. 
The concepts covered are: 
1. The Endowment Effect 
2. Hyperbolic Discounting 
3. The IKEA effect 
4. Anchoring Bias 
5. The Von Restorff Effect 
6. Loss Aversion 
7. Hedonic Adaption 
8. The Bandwagon Effect 
9. The Inaction inertia effect 
10. The Zeigarnik Effect 
11. The Framing Effect 
12. The Goal Gradient Effect 
13. The Choice Paradox 
14. Round Pricing Preference 
15. Reciprocity

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[1504.02656] A complex network approach to cloud computing

Cloud computing has become an important means to speed up computing. One problem influencing heavily the performance of such systems is the choice of nodes as servers responsible for executing the users' tasks. In this article we report how complex networks can be used to model such a problem. More specifically, we investigate the performance of the processing respectively to cloud systems underlain by Erdos-Renyi and Barabasi-Albert topology containing two servers. Cloud networks involving two communities not necessarily of the same size are also considered in our analysis. The performance of each configuration is quantified in terms of two indices: the cost of communication between the user and the nearest server, and the balance of the distribution of tasks between the two servers. Regarding the latter index, the ER topology provides better performance than the BA case for smaller average degrees and opposite behavior for larger average degrees. With respect to the cost, smaller values are found in the BA topology irrespective of the average degree. In addition, we also verified that it is easier to find good servers in the ER than in BA. Surprisingly, balance and cost are not too much affected by the presence of communities. However, for a well-defined community network, we found that it is important to assign each server to a different community so as to achieve better performance.

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Web Spam, Social Propaganda an the Evolution of Search Engine Rankings

Search Engines have greatly influenced the way we experience the web. Since the early days of the web, users have been relying on them to get informed and make decisions. When the web was relatively small, web directories were built and maintained using human experts to screen and categorize pages according to their characteristics. By the mid 1990’s, however, it was apparent that the human expert model of categorizing web pages does not scale. The first search engines appeared and they have been evolving ever since, taking over the role that web directories used to play. But what need makes a search engine evolve? Beyond the financial objectives, there is a need for quality in search results. Search engines know that the quality of their ranking will determine how successful they are. Search results, however, are not simply based on well-designed scientific principles, but they are influenced by web spammers. Web spamming, the practice of introducing artificial text and links into web pages to affect the results of web searches, has been recognized as a major search engine problem. It is also a serious users problem because they are not aware of it and they tend to confuse trusting the search engine with trusting the results of a search. In this paper, we analyze the influence that web spam has on the evolution of the search engines and we identify the strong relationship of spamming methods on the web to propagandistic techniques in society. Our analysis provides a foundation for understanding why spamming works and offers new insight on how to address it. In particular, it suggests that one could use social anti-propagandistic techniques to recognize web spam.

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Impossible scenarios: how do we make decisions in complexity? | Spark the Change

Impossible scenarios: how do we make decisions in complexity? | Spark the Change | Bounded Rationality and Beyond | Scoop.it

The General Manager (GM) of a municipal department was repeatedly getting bad press for the all-too apparent failings in maintaining city roads, drainage, sewage, and water. Continuous breakdowns in water supply, blockages in main drains and sewers were inconveniencing city residents and creating high costs in property damage. City Council was being taken to court for several cases of significant damage exacerbated by its insurer’s reluctance to settle claims promptly or on a reasonable basis.

The GM was being accused and abused by the press, the residents, his superiors, elected councilors and by his managers and staff who were taking much of the heat. He fell seriously ill.  While on sick leave the Mayor called him to discuss what he was going to do to address the growing storm of protest that was negatively affecting his chances of re-election. What did he have to say?

Up until now, his decisions were based on his lengthy experience with how to fix issues. In this new dilemma he was expected to come up with a ‘silver bullet’. But how?

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