The Irrational Bundle
by Dan Ariely · 3 Apr 2013 · 898pp · 266,274 words
caught . . . Market vendors, cab drivers, and cheating the blind . . . Fishing and tall tales . . . Striking a balance between truth and cheating. CHAPTER 2: Fun with the Fudge Factor Why some things are easier to steal than others . . . How companies pave the way for dishonesty . . . Token dishonesty . . . How pledges, commandments, honor codes, and paying
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beings. This balancing act is the process of rationalization, and it is the basis of what we’ll call the “fudge factor theory.” To give you a better understanding of the fudge factor theory, think of the last time you calculated your tax return. How did you make peace with the ambiguous and unclear
…
of us has a limit to how much we can cheat before it becomes absolutely “sinful.” Trying to figure out the inner workings of the fudge factor—the delicate balance between the contradictory desires to maintain a positive self-image and to benefit from cheating—is what we are going to turn
…
our attention to next. CHAPTER 2 Fun with the Fudge Factor Here’s a little joke for you: Eight-year-old Jimmy comes home from school with a note from his teacher that says, “Jimmy stole
…
activities can more easily loosen our moral standards. Perhaps, we thought, if we increased the psychological distance between a dishonest act and its consequences, the fudge factor would increase and our participants would cheat more. Of course, encouraging people to cheat more is not something we want to promote in general. But
…
need little reminders to keep ourselves on the right path. How to Get People to Cheat Less Now that we had figured out how the fudge factor works and how to expand it, as our next step we wanted to figure out whether we could decrease the
…
fudge factor and get people to cheat less. This idea, too, was spawned by a little joke: A visibly upset man goes to see his rabbi one
…
doing so would violate the separation of church and state). So we began to think of more general, practical, and secular ways to shrink the fudge factor, which led us to test the honor codes that many universities already use. To discover whether honor codes work, we asked a group of MIT
…
.* What are we to make of all this? First, we need to recognize that dishonesty is largely driven by a person’s fudge factor and not by the SMORC. The fudge factor suggests that if we want to take a bite out of crime, we need to find a way to change the way
…
in which we are able to rationalize our actions. When our ability to rationalize our selfish desires increases, so does our fudge factor, making us more comfortable with our own misbehavior and cheating. The other side is true as well; when our ability to rationalize our actions is
…
reduced, our fudge factor shrinks, making us less comfortable with misbehaving and cheating. When you consider the range of undesirable behaviors in the world from this standpoint—from banking
…
the tendency to behave immorally. If distance worked in the same way as the token experiment we discussed earlier (see chapter 2, “Fun with the Fudge Factor”), we would expect to have the lowest level of cheating when the movement was carried out explicitly with one’s hand; we would see higher
…
estimator would have dismissed the suggestion altogether. Second, remember that most people cheat just enough to still feel good about themselves. In that sense, the fudge factor was an extra $4 (or about 25 percent of the amount). The importance of this experiment, however, showed up in the third condition—the conflict
…
what about the effect of the disclosure on the advisers? Would the need to disclose eliminate their biased advice? Would disclosing their bias stretch the fudge factor? Would they now feel more comfortable exaggerating their advice to an even greater degree? And the billion-dollar question is this: which of these two
…
-the-hell effect, it is possible that one initial act of cheating could increase the executive’s general level of self-signaled dishonesty, increasing his fudge factor, which would give rise to further fraud. THE BOTTOM LINE is that we should not view a single act of dishonesty as just one petty
…
people were tempted with the opportunity to cheat. (This approach is related to our use of the Ten Commandments in chapter 2, “Fun with the Fudge Factor.”) Since our participants were clearly able to ignore the effect that the answer key had on their scores, we wondered what would happen if we
…
Lying When we lie for another person’s benefit, we call it a “white lie.” When we tell a white lie, we’re expanding the fudge factor, but we’re not doing it for selfish reasons. For example, consider the importance of insincere compliments. We all know the gold standard of white
…
measures of creativity, they had higher scores than those who cheated to a lower degree. Once again, their intelligence scores were no different. Stretching the Fudge Factor: The Case for Revenge Creativity is clearly an important means by which we enable our own cheating, but it’s certainly not the only one
…
of immoral behavior, we reflect on our own morality (similar to the Ten Commandments and the honor code experiments in chapter 2, “Fun with the Fudge Factor”). And as a consequence, we behave more honestly. A Fashion Statement Although those results were promising, we still wanted to get more direct support and
…
achieve both of these objectives at the same time—that we can’t have our cake and eat it too, so to speak—but the fudge factor theory we have developed in these pages suggests that our capacity for flexible reasoning and rationalization allows us to do just that. Basically, as long
…
main ways: it can take particular activities and transition them into and out of the moral domain, and it can change the magnitude of the fudge factor that is considered acceptable for any particular domain. Take plagiarism, for example. At American universities, plagiarism is taken very seriously, but in other cultures it
…
’t cheated on their spouses, the tabloid magazine and various entertainment news outlets would probably go belly-up (so to speak). In terms of the fudge factor theory, infidelity is most likely the prototypical illustration of all the characteristics of dishonesty that we have been talking about. To start with, it is
…
people of their obligations to be moral in various ways; recall, for example, the Jewish man with the tzitzit from chapter 2 (“Fun with the Fudge Factor”). Muslims use beads called tasbih or misbaha on which they recount the ninety-nine names of God several times a day. There’s also daily
…
). Nina Mazar and Dan Ariely, “Dishonesty in Everyday Life and Its Policy Implications,” Journal of Public Policy and Marketing (2006). Chapter 2. Fun with the Fudge Factor Based on Nina Mazar, On Amir, and Dan Ariely, “The Dishonesty of Honest People: A Theory of Self-concept Maintenance,” Journal of Marketing Research (2008
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interest in, 83–85, 93, 94 government regulation of, 234 fishing, lying about, 28 Frederick, Shane, 173 friends, invited to join in questionable behavior, 195 fudge factor theory, 27–29, 237 acceptable rate of lying and, 28–29, 91 distance between actions and money and, 34–37 getting people to cheat less
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, 14 self-cleansing, in resetting rituals, 250–52 Rather, Dan, 152 rationalization of selfish desires: of Austen characters, 154–55 fake products and, 134–35 fudge factor and, 27–28, 53, 237 link between creativity and dishonesty and, 172 revenge and, 177–84 tax returns and, 27–28 see also self-justification
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sports, 155–56 veterans’ false claims and, 152 white lies and, 159–61 self-flagellation, 250–52 self-image: amount of cheating and, 23, 27 fudge factor and, 27–29 self-indulgence, rational, 115–16 selfishness, see rationalization of selfish desires self-justification: creation of logical-sounding explanations and, 163–65 link
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, 114–15 Simple Model of Rational Crime (SMORC), 4–6, 11–29, 53, 201, 238, 248 author’s alternative theory to, 27–28; see also fudge factor theory guest lecturer’s satirical presentation on, 11–14 life in hypothetical world based on, 5–6 matrix task and, 15–23 tested in real
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and intricate human nature. * Readers of Predictably Irrational might recognize some of the material presented in this chapter and in chapter 2, “Fun with the Fudge Factor.” * X stands for the number of questions that the participants claimed to have solved correctly. * One important question about the usage of moral reminders is
The (Honest) Truth About Dishonesty: How We Lie to Everyone, Especially Ourselves
by Dan Ariely · 27 Jun 2012 · 258pp · 73,109 words
caught … Market vendors, cab drivers, and cheating the blind … Fishing and tall tales … Striking a balance between truth and cheating. Chapter 2 Fun with the Fudge Factor Why some things are easier to steal than others … How companies pave the way for dishonesty … Token dishonesty … How pledges, commandments, honor codes, and paying
…
beings. This balancing act is the process of rationalization, and it is the basis of what we’ll call the “fudge factor theory.” To give you a better understanding of the fudge factor theory, think of the last time you calculated your tax return. How did you make peace with the ambiguous and unclear
…
of us has a limit to how much we can cheat before it becomes absolutely “sinful.” Trying to figure out the inner workings of the fudge factor—the delicate balance between the contradictory desires to maintain a positive self-image and to benefit from cheating—is what we are going to turn
…
our attention to next. CHAPTER 2 Fun with the Fudge Factor Here’s a little joke for you: Eight-year-old Jimmy comes home from school with a note from his teacher that says, “Jimmy stole
…
activities can more easily loosen our moral standards. Perhaps, we thought, if we increased the psychological distance between a dishonest act and its consequences, the fudge factor would increase and our participants would cheat more. Of course, encouraging people to cheat more is not something we want to promote in general. But
…
need little reminders to keep ourselves on the right path. How to Get People to Cheat Less Now that we had figured out how the fudge factor works and how to expand it, as our next step we wanted to figure out whether we could decrease the
…
fudge factor and get people to cheat less. This idea, too, was spawned by a little joke: A visibly upset man goes to see his rabbi one
…
doing so would violate the separation of church and state). So we began to think of more general, practical, and secular ways to shrink the fudge factor, which led us to test the honor codes that many universities already use. To discover whether honor codes work, we asked a group of MIT
…
.* What are we to make of all this? First, we need to recognize that dishonesty is largely driven by a person’s fudge factor and not by the SMORC. The fudge factor suggests that if we want to take a bite out of crime, we need to find a way to change the way
…
in which we are able to rationalize our actions. When our ability to rationalize our selfish desires increases, so does our fudge factor, making us more comfortable with our own misbehavior and cheating. The other side is true as well; when our ability to rationalize our actions is
…
reduced, our fudge factor shrinks, making us less comfortable with misbehaving and cheating. When you consider the range of undesirable behaviors in the world from this stand-point—from
…
the tendency to behave immorally. If distance worked in the same way as the token experiment we discussed earlier (see chapter 2, “Fun with the Fudge Factor”), we would expect to have the lowest level of cheating when the movement was carried out explicitly with one’s hand; we would see higher
…
estimator would have dismissed the suggestion altogether. Second, remember that most people cheat just enough to still feel good about themselves. In that sense, the fudge factor was an extra $4 (or about 25 percent of the amount). The importance of this experiment, however, showed up in the third condition—the conflict
…
what about the effect of the disclosure on the advisers? Would the need to disclose eliminate their biased advice? Would disclosing their bias stretch the fudge factor? Would they now feel more comfortable exaggerating their advice to an even greater degree? And the billion-dollar question is this: which of these two
…
-the-hell effect, it is possible that one initial act of cheating could increase the executive’s general level of self-signaled dishonesty, increasing his fudge factor, which would give rise to further fraud. THE BOTTOM LINE is that we should not view a single act of dishonesty as just one petty
…
people were tempted with the opportunity to cheat. (This approach is related to our use of the Ten Commandments in chapter 2, “Fun with the Fudge Factor.”) Since our participants were clearly able to ignore the effect that the answer key had on their scores, we wondered what would happen if we
…
Lying When we lie for another person’s benefit, we call it a “white lie.” When we tell a white lie, we’re expanding the fudge factor, but we’re not doing it for selfish reasons. For example, consider the importance of insincere compliments. We all know the gold standard of white
…
measures of creativity, they had higher scores than those who cheated to a lower degree. Once again, their intelligence scores were no different. Stretching the Fudge Factor: The Case for Revenge Creativity is clearly an important means by which we enable our own cheating, but it’s certainly not the only one
…
of immoral behavior, we reflect on our own morality (similar to the Ten Commandments and the honor code experiments in chapter 2, “Fun with the Fudge Factor”). And as a consequence, we behave more honestly. A Fashion Statement Although those results were promising, we still wanted to get more direct support and
…
achieve both of these objectives at the same time—that we can’t have our cake and eat it too, so to speak—but the fudge factor theory we have developed in these pages suggests that our capacity for flexible reasoning and rationalization allows us to do just that. Basically, as long
…
main ways: it can take particular activities and transition them into and out of the moral domain, and it can change the magnitude of the fudge factor that is considered acceptable for any particular domain. Take plagiarism, for example. At American universities, plagiarism is taken very seriously, but in other cultures it
…
’t cheated on their spouses, the tabloid magazine and various entertainment news outlets would probably go belly-up (so to speak). In terms of the fudge factor theory, infidelity is most likely the prototypical illustration of all the characteristics of dishonesty that we have been talking about. To start with, it is
…
people of their obligations to be moral in various ways; recall, for example, the Jewish man with the tzitzit from chapter 2 (“Fun with the Fudge Factor”). Muslims use beads called tasbih or misbaha on which they recount the ninety-nine names of God several times a day. There’s also daily
…
). Nina Mazar and Dan Ariely, “Dishonesty in Everyday Life and Its Policy Implications,” Journal of Public Policy and Marketing (2006). Chapter 2. Fun with the Fudge Factor Based on Nina Mazar, On Amir, and Dan Ariely, “The Dishonesty of Honest People: A Theory of Self-concept Maintenance,” Journal of Marketing Research (2008
…
interest in, 83–85, 93, 94 government regulation of, 234 fishing, lying about, 28 Frederick, Shane, 173 friends, invited to join in questionable behavior, 195 fudge factor theory, 27–29, 237 acceptable rate of lying and, 28–29, 91 distance between actions and money and, 34–37 getting people to cheat less
…
, 14 self-cleansing, in resetting rituals, 250–52 Rather, Dan, 152 rationalization of selfish desires: of Austen characters, 154–55 fake products and, 134–35 fudge factor and, 27–28, 53, 237 link between creativity and dishonesty and, 172 revenge and, 177–84 tax returns and, 27–28 see also self-justification
…
sports, 155–56 veterans’ false claims and, 152 white lies and, 159–61 self-flagellation, 250–52 self-image: amount of cheating and, 23, 27 fudge factor and, 27–29 self-indulgence, rational, 115–16 selfishness, see rationalization of selfish desires self-justification: creation of logical-sounding explanations and, 163–65 link
…
, 114–15 Simple Model of Rational Crime (SMORC), 4–6, 11–29, 53, 201, 238, 248 author’s alternative theory to, 27–28; see also fudge factor theory guest lecturer’s satirical presentation on, 11–14 life in hypothetical world based on, 5–6 matrix task and, 15–23 tested in real
…
and intricate human nature. * Readers of Predictably Irrational might recognize some of the material presented in this chapter and in chapter 2, “Fun with the Fudge Factor.” * X stands for the number of questions that the participants claimed to have solved correctly. * One important question about the usage of moral reminders is
Principles of Corporate Finance
by Richard A. Brealey, Stewart C. Myers and Franklin Allen · 15 Feb 2014
Cost of Capital/Union Pacific’s Asset Beta 9-3 Analyzing Project Risk What Determines Asset Betas?/Don’t Be Fooled by Diversifiable Risk/Avoid Fudge Factors in Discount Rates/Discount Rates for International Projects 9-4 Certainty Equivalents—Another Way to Adjust for Risk Valuation by Certainty Equivalents/When to Use
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risk. Diversifiable risk can affect project cash flows but does not increase the cost of capital. Also don’t be tempted to add arbitrary fudge factors to discount rates. Fudge factors are too often added to discount rates for projects in unstable parts of the world, for example. Risk varies from project to project
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assets can be observed when the beta itself cannot be. 2. Don’t be fooled by diversifiable risk. 3. Avoid fudge factors. Don’t give in to the temptation to add fudge factors to the discount rate to offset things that could go wrong with the proposed investment. Adjust cash-flow forecasts first. What
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be worth less than the $909,100 you calculated before that worry arose. But how much less? There is some discount rate (10% plus a fudge factor) that will give the right value, but we do not know what that adjusted discount rate is. We suggest you reconsider your original $1 million
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whether diversified investors would regard the project as more or less risky than the average project. In this step only market risks are relevant. Avoid Fudge Factors in Discount Rates Think back to our example of project Z, where we reduced forecasted cash flows from $1 million to $900,000 to account
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failure of technology. The project’s PV was reduced from $909,100 to $818,000. You could have gotten the right answer by adding a fudge factor to the discount rate and discounting the original forecast of $1 million. But you have to think through the possible cash flows to get the
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fudge factor, and once you forecast the cash flows correctly, you don’t need the fudge factor. Fudge factors in discount rates are dangerous because they displace clear thinking about future cash flows. Here is an example. EXAMPLE
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optimistic. The forecasts and PVs should be reduced by 10% (lines 3 and 4). But adding a 10% fudge factor to the discount rate reduces PVs by far more than 10% (line 6). The fudge factor overcorrects for bias and would penalize long-lived projects. Project ZZ has level forecasted cash flows of 1
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, compared to the unadjusted PVs in line 2. Line 5 shows the correct adjustment for optimism (10%). Line 7 shows what happens when a 10% fudge factor is added to the discount rate. The effect on the first year’s cash flow is a PV “haircut” of about 8%, 2% less than
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the CFO expected. But later present values are knocked down by much more than 10%, because the fudge factor is compounded in the 22% discount rate. By years 10 and 15, the PV haircuts are 57% and 72%, far more than the 10% bias
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asked that question. If he was right in the first place, and the true bias is 10%, then adding a 10% fudge factor to the discount rate understates PV. The fudge factor also makes long-lived projects look much worse than quick-payback projects.18 Discount Rates for International Projects In this chapter we
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have concentrated on domestic investments. In Chapter 27 we say more about investments made internationally. Here we simply warn against adding fudge factors to discount rates for projects in developing economies. Such fudge factors are too often seen in practice. It’s true that markets are more volatile in developing economies, but much of
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be incorporated in the cash-flow forecasts. Also be careful not to offset worries about a project’s future performance by adding a fudge factor to the discount rate. Fudge factors don’t work, and they may seriously undervalue long-lived projects. There is one more fence to jump. Most projects produce cash flows
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diversifiable risks. What does “diversifiable” mean in this context? How should diversifiable risks be accounted for in project valuation? Should they be ignored completely? 7. Fudge factors John Barleycorn estimates his firm’s after-tax WACC at only 8%. Nevertheless he sets a 15% companywide discount rate to offset the optimistic biases
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other projects. b. Distant cash flows are riskier than near-term cash flows. Therefore long-term projects require higher risk-adjusted discount rates. c. Adding fudge factors to discount rates undervalues long-lived projects compared with quick-payoff projects. 10. Certainty equivalents A project has a forecasted cash flow of $110 in
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to offset political risk? b. How much is the $250,000 payment really worth if the odds of a coup d’état are 25%? 20. Fudge factors An oil company is drilling a series of new wells on the perimeter of a producing oil field. About 20% of the new wells will
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, the less you should worry about them! Can that be right? Should the sign of the cash flow affect the appropriate discount rate? Explain. 24. Fudge factors An oil company executive is considering investing $10 million in one or both of two wells: well 1 is expected to produce oil worth $3
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of each well with this adjusted discount rate. c. What do you say the NPVs of the two wells are? d. Is there any single fudge factor that could be added to the discount rate for developed wells that would yield the correct NPV for both wells? Explain. ● ● ● ● ● FINANCE ON THE WEB
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, then lambda = .08/.202 = 2. 21We will assume that they mean high market risk and that the difference between 25% and 10% is not a fudge factor introduced to offset optimistic cash-flow forecasts. Part 3 Best Practices in Capital Budgeting Project Analysis Having read our earlier chapters on capital budgeting, you
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projects that don’t subsequently earn 10%. She therefore directs project sponsors to use a 15% discount rate. In other words, she adds a 5% fudge factor in an attempt to offset forecast bias. But it doesn’t work; it never works. Brealey, Myers, and Allen’s Second Law1 explains why. The
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-steady at 85%. If you’re worried about bias in forecasted cash flows, the only remedy is careful analysis of the forecasts. Do not add fudge factors to the cost of capital.2 Postaudits Most firms keep a check on the progress of large projects by conducting postaudits shortly after the projects
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procedures to ensure that projects fit in with the company’s strategic plans and are developed on a consistent basis. (These procedures should not include fudge factors added to project hurdle rates in an attempt to offset optimistic forecasts.) Later, after a project has begun to operate, the firm can follow up
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value? ___________ 1There is no First Law. We think “Second Law” sounds better. There is a Third Law, but that is for another chapter. 2Adding a fudge factor to the cost of capital also favors quick-payback projects and penalizes longer-lived projects, which tend to have lower rates of return but higher
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NPVs. Adding a 5% fudge factor to the discount rate is roughly equivalent to reducing the forecast and present value of the first year’s cash flow by 5%. The impact
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on the present value of a cash flow 10 years in the future is much greater, because the fudge factor is compounded in the discount rate. The fudge factor is not too much of a burden for a 2- or 3-year project, but an enormous burden for a 10
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stock market is down. We take account of medical or clinical risks by multiplying future outcomes by the probability of success, not by adding a fudge factor to the discount rate. 22-6 A Conceptual Problem? In this chapter we have shown how option pricing models can help to value the real
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the theory that quick-payback projects are less exposed to political risks. But do not try to compensate for political risks by adding casual fudge factors to discount rates. Fudge factors spawn bias and confusion, as we explained in Chapter 9. ● ● ● ● ● SUMMARY The international financial manager has to cope with different currencies, interest rates
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. b. Specify probability distributions for forecast errors for these cash flows. c. Draw from the probability distributions to simulate the cash flows. 7. Adding a fudge factor to the discount rate pushes project analysts to submit more optimistic forecasts. CHAPTER 11 1. (a) False; (b) true; (c) true; (d) false. 3. First
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return (IRR) Discounted payback rule, 110–111 Discount factor, 20, 56–57 Discount notes, 795, 796 Discount rate. See also Opportunity cost of capital avoiding fudge factors in, 227, 230, 232, 247, 247n multiple, 235–237 single, 234–237 Discriminatory auctions, 385 Disney, 65, 222–224, 387, 824 Dittmann, I., 867, 867n
Elliptic Tales: Curves, Counting, and Number Theory
by Avner Ash and Robert Gross · 12 Mar 2012
) the local zeta-function of C. Now we can define the Hasse–Weil zeta-function of C, denoted Z(C, s), except for a certain fudge factor we will explain but not define. You simply substitute T = p−s in ζC,p (T) and then multiply all these local factors together: Z
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(C, s) = ζC,p (p−s ) × fudge. p good Here is a rough idea of where the fudge factor comes from. We call a prime p “good” for C if C modulo p is nonsingular, which means C(Fac p ) has no ac singular
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we can’t go into here. (However, when C is an elliptic curve, we will be able to tell you how to define the fudge factors.) The fudge factors are hard to define, but they are essential to flesh out our understanding of C modulo p for all primes p. In particular, they are
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numerator of the Hasse–Weil zetafunction of C is the product over good primes of polynomials of degree 2g evaluated at p−s , times a fudge factor from the bad primes. The reciprocal of this numerator is called the L-function of C, and is written L(C, s). In the case
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p good 1 + c1,p p−s + c2,p p−2s + · · · + c2g,p p−2gs . (Remember that although we don’t say here what the fudge factor is, it is known and can be determined.) Using long division for each term in the product, divide the denominator into 1, and you will
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out the details of constructing the L-function of an elliptic curve E defined over Q. In this case, we can even say what the fudge factors are. In this section, and for the remainder of this book, we use the so-called “minimal model” for E. This is an equation for
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E with smallest possible |E | chosen among all possible equations defining E. Using the minimal model allows us to specify the fudge factors correctly. Recall from chapter 8 that E (mod p) is an elliptic curve defined over Fp for any p not dividing the discriminant E . That
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, it depends only on ap and Hasse showed the formula that gives you the local zetafunction in terms of ap . We also can determine the fudge factors for the bad primes, and putting it all together we obtain: THEOREM 13.2: Let S be the set of primes for which E(Fp
Ruby by example: concepts and code
by Kevin C. Baird · 1 Jun 2007 · 309pp · 65,118 words
the approximate ratio of the word processor’s 62 C ha pt er 4 word count versus the output of wc (I call this the fudge factor), and I could certainly do the math, but I wanted something that would do all of this for me automatically. Let’s take a look
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.split(thing_to_match).size - 1 end # num_matches end # String BAR_LENGTH = 20 # to match these calculations with the output of some word processors FUDGE_FACTOR = 0.82 def word_count(files) Multiplying Strings output = '' total_word_count = 0 files.each do |filename| file_word_count = word_count_for_file(filename
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} words.\n" total_word_count += file_word_count end # each file return output + '-' * BAR_LENGTH + "\n" + "Total word count = #{total_word_count}" + " (#{(total_word_count * FUDGE_FACTOR)})" end # word_count def word_count_for_file(filename) f = File.new(filename, 'r') contents = f.read() f.close() spaces = contents.num_matches(' ') breaks = contents
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of times the argument appears within the calling String. I also define top-level constants called BAR_LENGTH ( ), which is just for visual formatting, and FUDGE_FACTOR ( ), which I already noted is the ratio between the two different word-counting programs I was working with. We then define the word_count method
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seen. We add a String consisting of 20 hyphen characters to the overall expression returned. The returned expression closes with the total multiplied by the FUDGE_FACTOR constant in parentheses. Before finishing with this script, we need to understand how it calculates the word count for each file. Let’s examine the
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which use techniques described in Jeffrey Friedl’s Mastering Regular Expressions. However, this script is intended for quick, approximate results, given that it uses a fudge factor. This script shows that just adding one new method to an existing class can be very handy even for a short, back-of-the-envelope
In the Age of the Smart Machine
by Shoshana Zuboff · 14 Apr 1988
regularly with the calculator models de- scribed his frustration at not having access to their underlying assump- tions and algorithms, which he called "fudge factors": 278 AUTHORITY: THE SPIRITUAL DIMENSION OF POWER The models use equations, fudge factors, put in there to make sure you make quality pulp. If you don't know these
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fudge factors, they can work against you. I had to talk the engineers into explaining the fudge factors to me. The assumptions of the designers are never explained to us. You cannot really be controlling the process if you
Relevant Search: With Examples Using Elasticsearch and Solr
by Doug Turnbull and John Berryman · 30 Apr 2016 · 593pp · 118,995 words
vector space model Although the vector space model provides a general framework for discussing Lucene’s scoring, it’s far from a complete picture. Numerous fudge factors have been shown to improve scoring in practice. Perhaps most fundamentally, the ways matches are combined by compound queries into a larger score isn’t
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equation to account for features that tend to have high weights, and those that tend to have smaller weights.[3] For search, given all the fudge factors in Lucene scoring and the peculiarities of field statistics, you should never attempt to compare scores between queries without a great deal of deep customization
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’s BM25 similarity will be rolling out as the default similarity for Solr/Elasticsearch, even as you read this book. What is BM25? Instead of “fudge factors” as discussed previously, BM25 bases its TF × IDF “fudges” on more-robust information retrieval findings. This includes forcing the impact of TF to reach a
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be inaccurate. To optimize the signal, you’re tweaking the math itself, not just TF × IDF and other text-scoring factors (what you might call fudge factors, we call score shaping). Yet even with the increased mathematical freedom, the imperatives are the same: you need to make sure your signals are accurate
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-style collaborative overview using co-occurrence counting score shaping vs. boosting finite state transducer fire token first_name field floating-point numbers fragment_size parameter fudge factors full bulk command full search string full-text search full_name field function decay function queries, multiplicative boosting with Boolean queries vs. combining high-value
UNIX® Network Programming, Volume 1: The Sockets Networking API, 3rd Edition
by W. Richard Stevens, Bill Fenner, Andrew M. Rudoff · 8 Jun 2013
. The historical definition in this bullet is the Berkeley implementation, dating back to 4.2BSD, and copied by many others. • Berkeley-derived implementations add a fudge factor to the backlog: It is multiplied by 1.5 (p. 257 of TCPv1 and p. 462 of TCPv2). For example, the commonly specified backlog of
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5 really allows up to 8 queued entries on these systems, as we show in Figure 4.10. The reason for adding this fudge factor appears lost to history [Joy 1994]. But if we consider the backlog as specifying the maximum number of completed connections that the kernel will queue
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for a socket ([Borman 1997b], as discussed shortly), then the reason for the fudge factor is to take into account incomplete connections on the queue. • Do not specify a backlog of 0, as different implementations interpret this differently (Figure 4
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routing table or the number of interfaces can change between the two calls to sysctl, the value returned by the first call contains a 10% fudge factor (pp. 639 – 640 of TCPv2). Section 18.5 get_ifi_info Function (Revisited) 501 Figure 18.16 shows the first half of the get_ifi
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fsetpos function, 400 fstat function, 406 fstat program, 897 FTP (File Transfer Protocol), 20, 62, 201, 311 – 312, 360, 362, 366, 375, 662, 914, 947 fudge factor, 106, 500 full-duplex, 36, 415 Fuller, V., 874, 949 fully buffered standard I/O stream, 401 fully qualified domain name, see FQDN function destructor
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and financial markets are perfectly efficient. To get anything like the current slump into their models, New Keynesians are forced to introduce some kind of fudge factor that for reasons unspecified temporarily depresses private spending. (I’ve done exactly that in some of my own work.) And if the analysis of where
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we are now rests on this fudge factor, how much confidence can we have in the models’ predictions about where we are going? The state of macro, in short, is not good. So
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Newton’s Theory of Color’. Isis (1962): 339–58. ———. Never at Rest: A Biography of Isaac Newton. Cambridge: Cambridge University Press, 1980. ———. ‘Newton and the Fudge Factor’. Science 179 (1973): 751–8. ———. ‘Science and Technology during the Scientific Revolution: An Empirical Approach’. In Renaissance and Revolution. Humanists, Scholars, Craftsmen and Natural Philosophers
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Experience (1995), 15, 180; for an example published by Riccioli in 1651, 78. 50. Palmerino, ‘Experiments, Mathematics, Physical Causes’ (2010); and Westfall, ‘Newton and the Fudge Factor’ (1973). 51. The legal issues and their history were recently summarized in the House of Lords judgement on Regina v. Pendleton, 13 Dec. 2001. 52
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