Program Evaluation Quotes

Task complete. Shut it down." Unable to comply, the computer responded. "I finished." Inaccurate statement. Previous command stipulated all listed reports and evaluations must be complete before system rest. This command by Dallas, Lieutenant Eve, priority basis, can only be countermanded at her order by fire, terrorist attack, alien invasion or an open and active case requiring her attention ... Jesus, had she really programmed that? "I changed my mind." Previous command specifies changes of mind, fatigue, boredom, and other lame excuses not acceptable for countermand ... "Bite me," Eve muttered.

When you evaluate, it allows you to assess your current programming and determine your re-programming.

When we stand before Christ and He evaluates our ministries, He will not be asking us how many people sat in the pews, watched our TV programs, gave in our telethons or filled out response cards. He is not going to evaluate us based on how many people fell under the power of God or how many healings we counted in each service. He will ask how many faithful disciples we made. I pray we make this our priority.

Nerds are used to transparency. They add value by becoming expert at a technical skill like computer programming. In engineering disciplines, a solution either works or it fails. You can evaluate someone else’s work with relative ease, as surface appearances don’t matter much. Sales is the opposite: an orchestrated campaign to change surface appearances without changing the underlying reality. This strikes engineers as trivial if not fundamentally dishonest. They know their own jobs are hard, so when they look at salespeople laughing on the phone with a customer or going to two-hour lunches, they suspect that no real work is being done. If anything, people overestimate the relative difficulty of science and engineering, because the challenges of those fields are obvious. What nerds miss is that it takes hard work to make sales look easy. SALES

Mental toughness fundamental #5 is to complete daily performance evaluations. COMPLETE

Performance evaluations include three very distinct components:       1. What is being done well     2. What needs to be improved     3. How improvements will be made Although

The main weakness of competitiveness policy as currently practiced in Latin America is deficient implementation and lack of evaluation of programs, rooted in lack of coordination among state agencies.

Scientists have repeatedly confirmed that our emotional reactions show up in brain activity before we even have time to think. We evaluate everything emotionally as we perceive it. We think about it afterwards

There is NO LIFE if it’s a programmed mind. Listen to the struggling kid inside, and follow the innocent unbiased zeal; YOU ARE ONE STEP CLOSER TO YOU. Never fall in to the trap of traditional rationales, which only evaluates in terms of transactions which leads to somebody else's goals someday. Time is Man-Made, Calendar is Man-Made to help us, not to disturb us, Set your own time, and allow the inner explosion to express itself. YOU ARE ONE STEP CLOSER TO YOU

...a bad diet will eventually kill our dreams. It's essential that we constantly evaluate the nutritional value of what we are feeding ourselves. It may come down to how many hours of television we're viewing, the quality of the programs we're watching, what music we're listening to, the material we're reading, the conversations we're having, the movies we're seeing, the Web sites we're visiting, the video games we're playing, or the people with whom we're associating. As harmless as these may sometimes seem, excessive consumption of things that induce negative thinking, bad habits, and wrong behavior will thwart our potential. A good litmus test is to ask yourself if you're giving more airtime to the media, educators, politicians, economists, pop stars, friends, or tradition than you are to God's Word. To see our dreams actualized, God's Word and His will must take precedence over everything else.

Ultimately, each church will be evaluated by only one thing—its disciples. Your church is only as good as her disciples. It does not matter how good your praise, preaching, programs or property are; if your disciples are passive, needy, consumeristic, and not [moving in the direction of radical obedience,] your church is not good.

It is important to note that the design of an entire brain region is simpler than the design of a single neuron. As discussed earlier, models often get simpler at a higher level—consider an analogy with a computer. We do need to understand the detailed physics ofsemiconductors to model a transistor, and the equations underlying a single real transistor are complex. A digital circuit that multiples two numbers requires hundreds of them. Yet we can model this multiplication circuit very simply with one or two formulas. An entire computer with billions of transistors can be modeled through its instruction set and register description, which can be described on a handful of written pages of text and formulas. The software programs for an operating system, language compilers, and assemblers are reasonably complex, but modeling a particular program—for example, a speech recognition programbased on hierarchical hidden Markov modeling—may likewise be described in only a few pages of equations. Nowhere in such a description would be found the details ofsemiconductor physics or even of computer architecture. A similar observation holds true for the brain. A particular neocortical pattern recognizer that detects a particular invariant visualfeature (such as a face) or that performs a bandpass filtering (restricting input to a specific frequency range) on sound or that evaluates the temporal proximity of two events can be described with far fewer specific details than the actual physics and chemicalrelations controlling the neurotransmitters, ion channels, and other synaptic and dendritic variables involved in the neural processes. Although all of this complexity needs to be carefully considered before advancing to the next higher conceptual level, much of it can be simplified as the operating principles of the brain are revealed.

I objected anytime a student was automatically dismissed for having a B on a transcript or for having gone to a less prestigious undergraduate program. If we were serious about bringing in minority lawyers, I asserted, we’d have to look more holistically at candidates. We’d need to think about how they’d used whatever opportunities life had afforded them rather than measuring them simply by how far they’d made it up an elitist academic ladder. The point wasn’t to lower the firm’s high standards: It was to realize that by sticking with the most rigid and old-school way of evaluating a new lawyer’s potential, we were overlooking all sorts of people who could contribute to the firm’s success. We needed to interview more students, in other words, before writing them off.

We know from the work of television critics and from the responses of our friends and from our own that there is little pride in the quality of television programs and less in the habit of extensive viewing. The television viewer’s implication in technology typically takes the form of complicity as defined in Chapter 15. We feel uneasiness about our passivity and guilt and sorrow at the loss of our traditions or alternatives.68 There is a realization that we are letting great things and practices drift into oblivion and that television fails to respond to our best aspirations and fails to engage the fullness of our powers. These impressions generally agree with more systematic findings that show that television is “not rated particularly highly as a general way of spending time, and in fact was evaluated below average compared to other free-time activities.”69

Impressive, indeed. Evaluations of the Memphis CIT program reveal improvements in community safety, reduced officer call time on mental illness (MI) dispatches, and reduced response times. Injuries to officers dropped from over five per thousand events to under one per thousand. And, most impressive: prior to the introduction of the program, officers were jailing 20 percent of the mentally ill people they encountered; today it’s 2 percent.8

Joan McCord was a pioneer iconoclast who was willing to question whether well-meaning, beneficial-sounding programs truly met the goal of helping their subjects. McCord found that social programs almost never constructed the procedures needed to reliably evaluate their success. In fact, she found that those working in social interventions often took affront to anyone who wanted to evaluate their programs, since they felt good intentions alone should have been a guarantee of their effectiveness.

Mental toughness is the ability to focus on and execute solutions, especially in the face of adversity. Greatness rarely happens on accident. If you want to achieve excellence, you will have to act like you really want it. How? Quite simply: by dedicating time and energy into consistently doing what needs to be done. Excuses are the antithesis of accountability. Important decisions aren’t supposed to be easy, but don’t let that stop you from making them. When it comes to decisions, decide to always decide. The second we stop growing, we start dying. Stagnation easily morphs into laziness, and once a person stops trying to grow and improve, he or she is nothing more than mediocre. Develop the no-excuse mentality. Do not let anything interrupt those tasks that are most critical for growth in the important areas of your life. Find a way, no matter what, to prioritize your daily process goals, even when you have a viable excuse to justify not doing it. “If you don’t evaluate yourself, how in the heck are you ever going to know what you are doing well and what you need to improve? Those who are most successful evaluate themselves daily. Daily evaluation is the key to daily success, and daily success is the key to success in life. If you want to achieve greatness, push yourself to the limits of your potential by continuously looking for improvements. Within 60 seconds, replace all problem-focused thought with solution-focused thinking. When people focus on problems, their problems actually grow and reproduce. When you train your mind to focus on solutions, guess what expands? Talking about your problems will lead to more problems, not to solutions. If you want solutions, start thinking and talking about your solutions. Believe that every problem, no matter how large, has at the very least a +1 solution, you will find it easier to stay on the solution side of the chalkboard. When you set your mind to do something, find a way to get it done…no matter what! If you come up short on your discipline, keep fighting, kicking, and scratching to improve. Find the nearest mirror and look yourself in the eye while you tell yourself, “There is no excuse, and this will not happen again.” Get outside help if needed, but never, ever give up on being disciplined. Greatness will not magically appear in your life without significant accountability, focus, and optimism on your part. Are you ready to commit fully to turning your potential into a leadership performance that will propel you to greatness. Mental toughness is understanding that the only true obstacles in life are self-imposed. You always have the choice to stay down or rise above. In truth, the only real obstacles to your ultimate success will come from within yourself and fall into one of the following three categories: apathy, laziness and fear. Laziness breeds more laziness. When you start the day by sleeping past the alarm or cutting corners in the morning, you’re more likely to continue that slothful attitude later in the day.

Take for example job applications. In the 21st century the decision wherever to hire somebody for a job while increasingly be made by algorithms. We cannot rely on the machines to set the relevant ethical standards, humans will still need to do that, but once we decide on an ethical standard in the job market, that it is wrong to discriminate against blacks or against women for example, we can rely on machines to implement and maintain these standards better than humans. A human manager may know and even agree that is unethical to discriminate against blacks and women but then when a black woman applies for a job the manager subconsciously discriminate against her and decides not to hire her. If we allow a computer to evaluate job applications and program computers to completely ignore race and gender we can be certain that the computer will indeed ignore these factors because computers do not have a subconscious. Of course it won't be easy to write code for evaluating job applications and there is always the danger that the engineers will somehow program their own subconscious biases into the software, yet once we discover such mistakes it would probably be far easier to debug the software than to get rid humans of their racist and misogynist biases.

legislatures at different levels of government, researchers, journalists, and judges involved in one or more aspects of the process. Each of these actors (either individual or corporate) has potentially different values/interests, perceptions of the situation, and policy preferences. 2. This process usually involves time spans of a decade or more, as that is the minimum duration of most policy cycles, from emergence of a problem through sufficient experience with implementation to render a reasonably fair evaluation of a program's impact (Kirst and Jung 1982; Sabatier and Jenkins-Smith 1993). A number of studies suggest that periods of twenty to forty years may be required to obtain a reasonable

But influential business leaders were eager proponents of numbers-driven merit pay for teachers. Ross Perot, for example, pushed Dallas to implement a plan to use test scores alone to evaluate teachers and distribute pay increases. So it was ironic that private industry had, by the 1980s, mostly turned away from efforts to pay white-collar workers according to strict productivity measures, finding that such formal evaluation programs were too expensive and time-consuming to create and implement. Research showed that companies with merit pay schemes did not perform better financially than did organizations without it, nor were their employees happier. Instead, management gurus recommended that workers be judged primarily by the holistic standards of individual supervisors.

Since our civilization is irreversibly dependent on electronics, abolition of EMR is out of the question. However, as a first step toward averting disaster, we must halt the introduction of new sources of electromagnetic energy while we investigate the biohazards of those we already have with a completeness and honesty that have so far been in short supply. New sources must be allowed only after their risks have been evaluated on the basis of the knowledge acquired in such a moratorium. 
With an adequately funded research program, the moratorium need last no more than five years, and the ensuing changes could almost certainly be performed without major economic trauma. It seems possible that a different power frequency—say 400 hertz instead of 60—might prove much safer. Burying power lines and providing them with grounded shields would reduce the electric fields around them, and magnetic shielding is also feasible. 
A major part of the safety changes would consist of energy-efficiency reforms that would benefit the economy in the long run. These new directions would have been taken years ago but for the opposition of power companies concerned with their short-term profits, and a government unwilling to challenge them. It is possible to redesign many appliances and communications devices so they use far less energy. The entire power supply could be decentralized by feeding electricity from renewable sources (wind, flowing water, sunlight, georhermal and ocean thermal energy conversion, and so forth) into local distribution nets. This would greatly decrease hazards by reducing the voltages and amperages required. Ultimately, most EMR hazards could be eliminated by the development of efficient photoelectric converters to be used as the primary power source at each point of consumption. The changeover would even pay for itself, as the loss factors of long-distance power transmission—not to mention the astronomical costs of building and decommissioning short-lived nuclear power plants—were eliminated. Safety need not imply giving up our beneficial machines. 
Obviously, given the present technomilitary control of society in most parts of the world, such sane efficiency will be immensely difficult to achieve. Nevertheless, we must try. Electromagnetic energy presents us with the same imperative as nuclear energy: Our survival depends on the ability of upright scientists and other people of goodwill to break the military-industrial death grip on our policy-making institutions.

Any program about highlighting benevolence, protecting the innocent, or sacrificing time to help the underdog grew in popularity. Included in our list of reality viewing were shows about police or bounty hunters apprehending evil criminals. These too became some of the most-watched programs. To sum it all up, our entertainment is often centered on the good of humanity. Sales and Marketing 101 teaches us that a product must feel, look, sound, taste, or smell good in order to succeed in the marketplace. It must elevate the consumer’s senses or emotions to a better and happier state. We know that good items will sell. After all, who would want to purchase something bad? And only twisted people would desire to procure evil. We hear comments such as “he’s a good man” or “she’s a good woman,” and we normally accept this evaluation at face value. The vulnerable quickly let down their guard and embrace every statement or action from those proclaimed to be good as safe and trustworthy. But are these assessments always accurate? Could we ever fall into the delusional state of calling what’s right wrong or what’s wrong right? Doesn’t everybody know the difference? And we certainly could never fall into the deceived state of calling good evil or evil good. Correct?

Try this exercise: Make a list of whatever is going wrong in your life, from the biggest events to the most trivial items, and then beside that list write down everything and everyone you want to blame for that particular problem. For instance, let's say you think you're too fat. If you want to blame it on McDonald's cheeseburgers, then write that down. Perhaps you just don't normally feel well. If you want to blame that feeling on a bad doctor or on the pollen in the air, then write that down. Maybe you can't find a suitable partner. If you want to blame that on the argument that "men are creeps," then write that down. Now look at your list. Ask yourself if you are any different now that you know exactly what or who to blame, and then ask yourself if that has helped you come up with a more constructive program to solve your problems. Not a very positive picture, is it? Wouldn't it be better simply to decide to eliminate all blame from your life and focus instead on what you can do to rid yourself of the unhappiness that afflicts you? Wouldn't it be better to evaluate all the stones that you are carrying in your own bag of life--your stones of resentment, anger, and spite? Blaming will not change you. It only gives you some shallow justification for continuing to look outside yourself, rather than turning inward and rebuilding your life.

Creating “Correct” Children in the Classroom One of the most popular discipline programs in American schools is called Assertive Discipline. It teaches teachers to inflict the old “obey or suffer” method of control on students. Here you disguise the threat of punishment by calling it a choice the child is making. As in, “You have a choice, you can either finish your homework or miss the outing this weekend.” Then when the child chooses to try to protect his dignity against this form of terrorism, by refusing to do his homework, you tell him he has chosen his logical, natural consequence of being excluded from the outing. Putting it this way helps the parent or teacher mitigate against the bad feelings and guilt that would otherwise arise to tell the adult that they are operating outside the principles of compassionate relating. This insidious method is even worse than outand-out punishing, where you can at least rebel against your punisher. The use of this mind game teaches the child the false, crazy-making belief that they wanted something bad or painful to happen to them. These programs also have the stated intention of getting the child to be angry with himself for making a poor choice. In this smoke and mirrors game, the children are “causing” everything to happen and the teachers are the puppets of the children’s choices. The only ones who are not taking responsibility for their actions are the adults. Another popular coercive strategy is to use “peer pressure” to create compliance. For instance, a teacher tells her class that if anyone misbehaves then they all won’t get their pizza party. What a great way to turn children against each other. All this is done to help (translation: compel) children to behave themselves. But of course they are not behaving themselves: they are being “behaved” by the adults. Well-meaning teachers and parents try to teach children to be motivated (translation: do boring or aversive stuff without questioning why), responsible (translation: thoughtless conformity to the house rules) people. When surveys are conducted in which fourth-graders are asked what being good means, over 90% answer “being quiet.” And when teachers are asked what happens in a successful classroom, the answer is, “the teacher is able to keep the students on task” (translation: in line, doing what they are told). Consulting firms measuring teacher competence consider this a major criterion of teacher effectiveness. In other words if the students are quietly doing what they were told the teacher is evaluated as good. However my understanding of ‘real learning’ with twenty to forty children is that it is quite naturally a bit noisy and messy. Otherwise children are just playing a nice game of school, based on indoctrination and little integrated retained education. Both punishments and rewards foster a preoccupation with a narrow egocentric self-interest that undermines good values. All little Johnny is thinking about is “How much will you give me if I do X? How can I avoid getting punished if I do Y? What do they want me to do and what happens to me if I don’t do it?” Instead we could teach him to ask, “What kind of person do I want to be and what kind of community do I want to help make?” And Mom is thinking “You didn’t do what I wanted, so now I’m going to make something unpleasant happen to you, for your own good to help you fit into our (dominance/submission based) society.” This contributes to a culture of coercion and prevents a community of compassion. And as we are learning on the global level with our war on terrorism, as you use your energy and resources to punish people you run out of energy and resources to protect people. And even if children look well-behaved, they are not behaving themselves They are being behaved by controlling parents and teachers.

Several principles are illustrated by this experience. The value of a program intended to reduce injuries is not necessarily a function of the good intentions of the program's proponents. Skill or behavior change programs can have unintended harmful effects and those effects are often found only by well-designed research. This is particularly true of programs that have the potential to increase exposure to hazards. Once a program becomes institutionalized, it is difficult to remove it no matter how ineffective or harmful its consequences.    A major barrier to the scientific evaluation of programs is the reluctance of those who develop, advocate or profit from programs to have them evaluated objectively. In some cases, their investment in the programs is only psychological, but in others it is economic.

works. Scala decides precedence based on the first character of the methods used in operator notation (there's one exception to this rule, which will be discussed below). If the method name starts with a *, for example, it will have a higher precedence than a method that starts with a +. Thus 2 + 2 * 7 will be evaluated as 2 + (2 * 7), and a +++ b *** c (in which a, b, and c are variables, and +++ and *** are methods) will be evaluated a +++ (b *** c), because the *** method has a higher precedence than the +++ method.

The << method starts with the character <, which appears lower in Table 5.3 than the character +, which is the first and only character of the + method. Thus << will have lower precedence than +, and the expression will be evaluated by first invoking the + method, then the << method, as in 2 << (2 + 2). 2 + 2 is 4, by our math, and 2 << 4 yields 32.

The mission of the Incarnate Word High School Library is to stimulate and support learning with appropriate resources and programs in order for students to become critical thinkers. Students are encouraged to become lifelong learners who not only love reading but also have the skills to find, analyze and use information. The Library supports the School curriculum, promotes the enjoyment of reading, and develops skills in critical and effective use of information resources by providing instruction to foster competence in acquiring, evaluating and using information and ideas; stimulating interest in reading and appreciation of literature; and providing intellectual and physical access to materials in multiple formats.

violations of regression assumptions, and strategies for examining and remedying such assumptions. Then we extend the preceding discussion and will be able to conclude whether the above results are valid. Again, this model is not the only model that can be constructed but rather is one among a family of plausible models. Indeed, from a theoretical perspective, other variables might have been included, too. From an empirical perspective, perhaps other variables might explain more variance. Model specification is a judicious effort, requiring a balance between theoretical and statistical integrity. Statistical software programs can also automatically select independent variables based on their statistical significance, hence, adding to R-square.2 However, models with high R-square values are not necessarily better; theoretical reasons must exist for selecting independent variables, explaining why and how they might be related to the dependent variable. Knowing which variables are related empirically to the dependent variable can help narrow the selection, but such knowledge should not wholly determine it. We now turn to a discussion of the other statistics shown in Table 15.1. Getting Started Find examples of multiple regression in the research literature. Figure 15.1 Dependent Variable: Productivity FURTHER STATISTICS Goodness of Fit for Multiple Regression The model R-square in Table 15.1 is greatly increased over that shown in Table 14.1: R-square has gone from 0.074 in the simple regression model to 0.274. However, R-square has the undesirable mathematical property of increasing with the number of independent variables in the model. R-square increases regardless of whether an additional independent variable adds further explanation of the dependent variable. The adjusted R-square (or ) controls for the number of independent variables. is always equal to or less than R2. The above increase in explanation of the dependent variable is due to variables identified as statistically significant in Table 15.1. Key Point R-square is the variation in the dependent variable that is explained by all the independent variables. Adjusted R-square is often used to evaluate model explanation (or fit). Analogous with simple regression, values of below 0.20 are considered to suggest weak model fit, those between 0.20 and 0.40 indicate moderate fit, those above 0.40 indicate strong fit, and those above 0.65 indicate very strong model fit. Analysts should remember that choices of model specification are driven foremost by theory, not statistical model fit; strong model fit is desirable only when the variables, and their relationships, are meaningful in some real-life sense. Adjusted R-square can assist in the variable selection process. Low values of adjusted R-square prompt analysts to ask whether they inadvertently excluded important variables from their models; if included, these variables might affect the statistical significance of those already in a model.3 Adjusted R-square also helps analysts to choose among alternative variable specifications (for example, different measures of student isolation), when such choices are no longer meaningfully informed by theory. Empirical issues of model fit then usefully guide the selection process further. Researchers typically report adjusted R-square with their

Recommendation 7: Build human capital in government. While Moneyball uses big data and advanced statistics, the endeavor ultimately depends on people. To take one example: rapid-cycle evaluation at a service-delivery agency requires policy experts to identify plausible new approaches; program managers to implement them; technologists to create or modernize data systems to capture effects; social scientists or statisticians to analyze the data on effects; and crosscutting leaders who know how to bring these pieces together with inspiration and precision.

When evaluating aftercare homes to support (beyond the six featured in the IN PLAIN SIGHT documentary), we encourage you to ask these types of questions. Good intentions are not enough. Professionalism and accountability are critical when working with survivors of sex trafficking.    Does the program include trauma-informed counseling by a licensed professional?    Is the identity of each child/woman kept confidential?    Are minors used to fundraise for the organization?    Are females and males housed on completely separate properties?    Is the facility licensed so there is accountability for policies and procedures?    Do those working and volunteering for the facility have to undergo a stringent vetting process?    Is the location undisclosed?

Class Quality Abstract Data Types Have you thought of the classes in your program as abstract data types and evaluated their interfaces from that point of view? Abstraction Does the class have a central purpose? Is the class well named, and does its name describe its central purpose? Does the class's interface present a consistent abstraction? Does the class's interface make obvious how you should use the class? Is the class's interface abstract enough that you don't have to think about how its services are implemented? Can you treat the class as a black box? Are the class's services complete enough that other classes don't have to meddle with its internal data? Has unrelated information been moved out of the class? Have you thought about subdividing the class into component classes, and have you subdivided it as much as you can? Are you preserving the integrity of the class's interface as you modify the class? Encapsulation Does the class minimize accessibility to its members? Does the class avoid exposing member data? Does the class hide its implementation details from other classes as much as the programming language permits? Does the class avoid making assumptions about its users, including its derived classes? Is the class independent of other classes? Is it loosely coupled? Inheritance Is inheritance used only to model "is a" relationships—that is, do derived classes adhere to the Liskov Substitution Principle? Does the class documentation describe the inheritance strategy? Do derived classes avoid "overriding" non-overridable routines? Are common interfaces, data, and behavior as high as possible in the inheritance tree? Are inheritance trees fairly shallow? Are all data members in the base class private rather than protected? Other Implementation Issues Does the class contain about seven data members or fewer? Does the class minimize direct and indirect routine calls to other classes? Does the class collaborate with other classes only to the extent absolutely necessary? Is all member data initialized in the constructor? Is the class designed to be used as deep copies rather than shallow copies unless there's a measured reason to create shallow copies?

We resort to a series of programs and practices like job rotation, reverse evaluation, and self-management. They’re intended to help people tap their reservoir of talent and to preclude the need for weeding out. We never assume there are weeds among us.

Home Affordable Unemployment Program Under the Unemployment Program, for a certain period of time, you pay either reduced mortgage payments (equal to less than 31% of your gross income) or none at all. This period is called a forbearance and typically lasts for 12 months (less if you start working again, or more if the servicer extends the period). To be eligible for UP: • You must meet the same eligibility requirements as for HAMP (see below). • You must be unemployed and be eligible to receive unemployment benefits when you request UP. • The servicer can require you to receive at least three months of unemployment benefits before it starts the forbearance period. • You must make the request before you become 12 months late with your mortgage payments. The servicer cannot proceed with foreclosure after you request UP, while you are in any UP plan or extension of it, or while you are being evaluated for HAMP or HAFA (see below for descriptions of these programs). If your unemployment situation will be more than short-term, the servicer is required to evaluate whether you qualify for one of the long-term programs, like HAMP or HAFA (both described below).

If any part of a program is messy or complicated, the programmer should attempt to modularize it and to generalize the parts. He or she should expect to use higher-order functions and lazy evaluation as the tools for doing this

Schedule a comprehensive evaluation to not only provide a formal diagnosis, but to also delineate a clear picture of your strengths and weaknesses. You will then be ready to participate in designing a total treatment plan that meets your unique needs. Get Treatment An effective, total treatment program is essential to future success. Such programs usually include a combination of medication, psychotherapy, coaching, alternative treatments, and necessary related services (support groups, counseling, family therapy, etc.). ADHD can have serious consequences, but it is treatable with safe and effective medications that can change people’s lives. (See Question 35 for a more in-depth discussion of medications used to treat ADHD.)

The approach shown... is a common pattern for testing exception-throwing behavior with JUnit. @Test public void missingValueRaisesException() throws Exception { try { new Template("${foo}").evaluate(); fail("evaluate() should throw an exception if " + "a variable was left without a value!"); } catch (MissingValueException expected) { } }

Program Evaluation and Educational Research (PEER) Associates, they created the Place-based Education Evaluation Collaborative (PEEC). Findings about student achievement are still preliminary, but PEEC’s work regarding other impacts of place-based education on students and teachers reiterates much that has surfaced from earlier studies about the positive effect that situating learning in authentic contexts can have on student motivation and involvement.

When running a Python program, the interpreter spends most of its time figuring out what low-level operation to perform, and extracting the data to give to this low-level operation. Given Python’s design and flexibility, the Python interpreter always has to determine the low-level operation in a completely general way, because a variable can have any type at any time. This is known as dynamic dispatch, and for many reasons, fully general dynamic dispatch is slow.[5] For example, consider what happens when the Python runtime evaluates a + b: The interpreter inspects the Python object referred to by a for its type, which requires at least one pointer lookup at the C level. The interpreter asks the type for an implementation of the addition method, which may require one or more additional pointer lookups and internal function calls. If the method in question is found, the interpreter then has an actual function it can call, implemented either in Python or in C. The interpreter calls the addition function and passes in a and b as arguments. The addition function extracts the necessary internal data from a and b, which may require several more pointer lookups and conversions from Python types to C types. If successful, only then can it perform the actual operation that adds a and b together. The result then must be placed inside a (perhaps new) Python object and returned. Only then is the operation complete. The situation for C is very different. Because C is compiled and statically typed, the C compiler can determine at compile time what low-level operations to perform and what low-level data to pass as arguments. At runtime, a compiled C program skips nearly all steps that the Python interpreter must perform. For something like a + b with a and b both being fundamental numeric types, the compiler generates a handful of machine code instructions to load the data into registers, add them, and store the result.

WHY HABITS ARE GOOD FOR BUSINESS If our programmed behaviors are so influential in guiding our everyday actions, surely harnessing the same power of habits can be a boon for industry. Indeed, for those able to shape them in an effective way, habits can be very good for the bottom line. Habit-forming products change user behavior and create unprompted user engagement. The aim is to influence customers to use your product on their own, again and again, without relying on overt calls to action such as ads or promotions. Once a habit is formed, the user is automatically triggered to use the product during routine events such as wanting to kill time while waiting in line. However, the framework and practices explored in this book are not “one size fits all” and do not apply to every business or industry. Entrepreneurs should evaluate how user habits impact their particular business model and goals. While the viability of some products depends on habit-formation to thrive, that is not always the case. For example, companies selling infrequently bought or used products or services do not require habitual users—at least, not in the sense of everyday engagement. Life insurance companies, for instance, leverage salespeople, advertising, and word-of-mouth referrals and recommendations to prompt consumers to buy policies. Once the policy is bought, there is nothing more the customer needs to do. In this book I refer to products in the context of businesses that require ongoing, unprompted user engagement and therefore need to build user habits. I exclude companies that compel customers to take action through

For example, to print the lines 13, 19, 88, 290, and 999, you do this: perl -ne 'print if $. == 13 || $. == 19 || $. == 88 || $. == 290 || $. == 999' If you want to print more lines, you can put them in a separate array and then test whether $. is in this array: perl -ne '   @lines = (13, 19, 88, 290, 999, 1400, 2000);   print if grep { $_ == $. } @lines ' This one-liner uses grep to test if the current line $. is in the @lines array. If the current line number is found in the @lines array, the grep function returns a list of one element that contains the current line number and this list evaluates to true.

scripting language is a programming language that provides you with the ability to write scripts that are evaluated (or interpreted) by a runtime environment called a script engine (or an interpreter). A script is a sequence of characters that is written using the syntax of a scripting language and used as the source for a program executed by an interpreter. The interpreter parses the scripts, produces intermediate code, which is an internal representation of the program, and executes the intermediate code. The interpreter stores the variables used in a script in data structures called symbol tables. Typically, unlike in a compiled programming language, the source code (called a script) in a scripting language is not compiled but is interpreted at runtime. However, scripts written in some scripting languages may be compiled into Java bytecode that can be run by the JVM. Java 6 added scripting support to the Java platform that lets a Java application execute scripts written in scripting languages such as Rhino JavaScript, Groovy, Jython, JRuby, Nashorn JavaScript, and so on. Two-way communication is supported. It also lets scripts access Java objects created by the host application. The Java runtime and a scripting language runtime can communicate and make use of each other’s features. Support for scripting languages in Java comes through the Java Scripting API. All classes and interfaces in the Java Scripting API are in the javax.script package. Using a scripting language in a Java application provides several advantages: Most scripting languages are dynamically typed, which makes it simpler to write programs. They provide a quicker way to develop and test small applications. Customization by end users is possible. A scripting language may provide domain-specific features that are not available in Java. Scripting languages have some disadvantages as well. For example, dynamic typing is good to write simpler code; however, it turns into a disadvantage when a type is interpreted incorrectly and you have to spend a lot of time debugging it. Scripting support in Java lets you take advantage of both worlds: it allows you to use the Java programming language for developing statically typed, scalable, and high-performance parts of the application and use a scripting language that fits the domain-specific needs for other parts. I will use the term script engine frequently in this book. A script engine is a software component that executes programs written in a particular scripting language. Typically, but not necessarily, a script engine is an implementation of an interpreter for a scripting language. Interpreters for several scripting languages have been implemented in Java. They expose programming interfaces so a Java program may interact with them.

Faith in Sobriety department of health in Houston offering pretrial Services related to Intensive Outpatient Program, Relapse Prevention, Substance Abuse Evaluation

So, to return to the title chapter, what is the point of learning statistics? To summarize huge quantities of data. To make better decisions. To answer important social questions. To recognize patterns that can refine how we do everything from selling diapers to catching criminals. To catch cheaters and prosecute criminals. To evaluate the effectiveness of policies, programs, drugs, medical procedures, and other innovations. And to spot the scoundrels who use these very same powerful tools for nefarious ends.

This is the Prius,” he said. The car he pointed to was a shell with wires hanging out. “It is an example of what they look like when we are done,” he said. This particular examination had proven exceedingly useful because when the second-generation Prius was released in the mid-2000s, some wondered whether Toyota had cheated on the fuel economy tests. Hillebrand’s team had showed that, if the company wanted to, it in fact could game federal evaluators. That was because the car could be programmed with advance knowledge of the curves, stops, and hazards that all automakers knew the test featured. So armed, it could adjust and conserve gasoline. Hillebrand’s team did not demonstrate that the Prius folks did cheat. But the opportunity to do so was sufficient. He sent word to the Environmental Protection Agency, which devised a randomized test that was harder to con.

Knowing, glorifying and loving God are difficult to quantify, so we seldom include them in the evaluation process. We are tempted to evaluate goals that are easy to measure but that are much less significant. The final evaluation of leadership and of organizations is to ask, Did our efforts, programs, finances, structures and leadership style bring glory to God? Did these help people to know and love God? Too often we merely ask, Did the organization grow under my leadership? Did the budget increase? Did we plant more churches? Instead we must ask, Did the budget make God glad? Do people in the churches we planted truly love God more deeply? The fact that we will never be able to precisely quantify and evaluate the ultimate purpose must not dissuade us from being passionate about God’s glory. The Lord will likely give us glimpses or indications of leadership effectiveness, but most of the critical outcomes will only be known in eternity.

we examined return on investment for communication expenditures for “most-excellent” and “least-excellent” programs. 6 In the survey, CEOs were asked to estimate benefits that their organizations received from the dollars or pounds invested in communication. If the CEO said the organization received one dollar back for each dollar spent on communication, then communication benefits were even with costs. If two dollars in benefits were received for each communication dollar spent, then communication provided the organization with a positive return on investment. The CEO's evaluation of return on investment is, admittedly, subjective. But consider this: The CEO's judgments about costs and benefits are the very judgments that will determine if your budget and staff increase or decrease next year! Further, no other manager in the organization has the same vantage point as the CEO. The average return on investment from the CEOs in organizations with most-excellent communication programs was $2.66 for every dollar invested in communication. In contrast, CEOs of organizations with least-excellent communication programs reported only a $1.46 average return on investment for each dollar spent on communication. CEOs with most-excellent communication programs—as defined by the Excellence Study and as isolated in the Excellence Factor—see greater return on investment for communication expenditures than do CEOs with least-excellent programs.

One downfall of numpy’s optimization of vector operations is that it only occurs on one operation at a time. That is to say, when we are doing the operation A * B + C with numpy vectors, first the entire A * B operation completes, and the data is stored in a temporary vector; then this new vector is added with C. The in-place version of the diffusion code in Example 6-14 shows this quite explicitly. However, there are many modules that can help with this. numexpr is a module that can take an entire vector expression and compile it into very efficient code that is optimized to minimize cache misses and temporary space used. In addition, the expressions can utilize multiple CPU cores (see Chapter 9 for more information) and specialized instructions for Intel chips to maximize the speedup. It is very easy to change code to use numexpr: all that’s required is to rewrite the expressions as strings with references to local variables. The expressions are compiled behind the scenes (and cached so that calls to the same expression don’t incur the same cost of compilation) and run using optimized code. Example 6-19 shows the simplicity of changing the evolve function to use numexpr. In this case, we chose to use the out parameter of the evaluate function so that numexpr doesn’t allocate a new vector to which to return the result of the calculation.

It’s safe to predict this result, and not just because I have seen it many times in the companies I work with. It is a straightforward prediction of the Lean Startup theory itself. When people are used to evaluating their productivity locally, they feel that a good day is one in which they did their job well all day. When I worked as a programmer, that meant eight straight hours of programming without interruption. That was a good day. In contrast, if I was interrupted with questions, process, or—heaven forbid—meetings, I felt bad. What did I really accomplish that day? Code and product features were tangible to me; I could see them, understand them, and show them off. Learning, by contrast, is frustratingly intangible.

Francine’s face. “We don’t really use the word ‘teaching’,” she said, using her fingers to form quotation marks. “We train NGO leaders to better manage their organizations.” “Right,” I said, although still not certain how “teaching” was different from “training”. Maybe I wasn’t so smart, after all. “We facilitate staff to be better project managers, financial managers, better people managers.” Francine leaned into the desk to emphasize the word “facilitate”. “And we facilitate organizations to develop long-term strategies, to create sound work plans, and to evaluate their programs. Among other things, of course. So our role is that of a facilitator, not a teacher, as such.” I’d never heard the word “facilitate” used so many times in the same breath. Back then, I had no idea how many times I, myself, would breathlessly use that word during my work in Africa.

At the same time states across the country were rushing to adopt the Common Core, they were also adopting a new tool for evaluating teachers: the Danielson Framework. Like the Common Core, the framework is so laden with technocratic language that one might imagine its sole purpose is to confuse its readers. And as with the Common Core, if a teacher does not meet its demands, she may be out of a job. Taking its name from the education consultant Charlotte Danielson, the framework divides the teaching process into four “domains”: “planning and preparation,” “classroom environment,” “instruction,” and “professional responsibilities.” Each of these domains is then broken into four or five subcategories ranging from “using questioning and discussion techniques” to “showing professionalism.” Subcategories are then separated into a series of components. For example, the components of the subcategory “participating in the professional community” are: “relationships with colleagues,” “involvement in a culture of professional inquiry,” “service to the school,” and “participation in school and district projects.” Danielson describes “proficient” (tolerable) instruction in the “communicating with families” subcategory of the “professional responsibilities” domain as follows: “The teacher provides frequent and appropriate information to families about the instructional program and conveys information about individual student progress in a culturally sensitive manner.

networks, system operators and satellite broadcasters, are annually evaluated for their programming and areas of activity, and the

stratejiler iş fırsatları gelir gider para kazanılır kaybedilir. Ama sürdürülebilir başarının temeli değerlerdir. Yani çalışma kültürü iki insanlardır ve kültür dediğim zaman da size ne kastediyorum onu göstereceğim ben bu konuşmayı bırakacağım. Kültür bir sürü faktörün dokumasından çıkıyor komünikasyon, Compensation. HR Programs İnsan Kaynakları, Performance Evaluation Employment Relationship Endüstri İlişkileri veya Performans Analizi. Burada vizyon ve değişim için tolerans hoşgörü organizasyon yeteneği, Individual Competencies karar alabilme en önemlisi değerler kültür moral liderlik structure bütün bunların hepsi bu çalışma kültürünü oluşturuyor. İşte sürdürülebilir başarının temeli buralardan geçiyor.

When the recruiting team gathered in a conference room in Chicago with a pile of student résumés to review, I objected anytime a student was automatically dismissed for having a B on a transcript or for having gone to a less prestigious undergraduate program. If we were serious about bringing in minority lawyers, I asserted, we’d have to look more holistically at candidates. We’d need to think about how they’d used whatever opportunities life had afforded them rather than measuring them simply by how far they’d made it up an elitist academic ladder. The point wasn’t to lower the firm’s high standards: It was to realize that by sticking with the most rigid and old-school way of evaluating a new lawyer’s potential, we were overlooking all sorts of people who could contribute to the firm’s success. We needed to interview more students, in other words, before writing them off.

We also changed our recruiting practices to improve our digital talent pool. Formerly, we had sought out digital talent from the best, name-brand colleges and universities. Now we focused on attracting members of a small subset of elite programmers who were capable of producing ten times the output of the typical programmer. To attract these premier programmers, or “multipliers” as we called them, we began evaluating potential hires on specific skills related to programming, collaboration, and teamwork, observing their actual behavior rather than just relying on their academic record. We took a similar approach to hiring data scientists as well. Our efforts in this area helped us significantly up our game as we developed software as a business and incorporated it into more of our existing products.

What would we think of a pollster who issued a definitive report on how the American people felt about a new television special, if we discovered later that he had interviewed only one person who had seen only ten minutes of the program? We would dismiss the conclusions as frivolous. Yet that is exactly the kind of evidence that too many Christians accept as the final truth about much more important matters-matters such as answered prayer, God's judgment, Christ's forgiveness, eternal salvation. The only person they consult is themselves, and the only experience they evaluate is the most recent ten minutes. But we need other experiences, the community of experience of brothers and sisters in the church, the centuries of experience provided by our biblical ancestors. A Christian who has David in his bones, Jeremiah in his bloodstream, Paul in his fingertips and Christ in his heart will know how much and how little value to put on his own momentary feelings and the experience of the past week.

More recently, physicist Edwin May, who directed the ESP research at SRI after 1986 and then headed the program researching “anomalous cognition” (May’s preferred term) after it was transferred to SAIC, and psychologist Sonali Bhatt Marwaha have also argued that all forms of ESP are likely precognition misinterpreted or misidentified.29 Unlike Feinberg, they do not assume precognition is solely an “inside the head” phenomenon30; but reducing anomalous cognition to precognition is a bold step that may move the field of parapsychology forward by, as they say, “collaps[ing] the problem space”31 of these phenomena. What has always seemed like several small piles of interesting but perhaps not overwhelming data supporting various diverse forms of psi or anomalous cognition may really be a single, impressively large pile of evidence for the much more singular, astonishing, and as I hope to show, physically plausible ability of people to access information arriving from their own future. In Part Two, where I address the possible “nuts and bolts” of this ability, I will be making a case for precognition being something close to Feinberg’s “memory of things future”—an all-in-the-head information storage and retrieval process, but one that is not limited to short-term memory. Evidence from life and laboratory suggests it may be possible, within limits, to “premember” experiences days, months, and years in our future, albeit dimly and obliquely, in a manner not all that different from how we remember experiences in our past. The main qualitative difference would be that, unlike memory for past experiences, we have no context for recognizing information from our future, let alone interpreting or evaluating it, and thus will seldom even notice its existence. We would also have little ability to directly search our memory for things future, the way we can rummage in our mental attic for information we know we acquired earlier in life. Yet things we will learn in our future may “inform” us in many non-conscious ways, and this information may be accessed in dreams and art and tasks like ESP experiments that draw on ill-defined intuitive abilities.

He laid out the defining characteristics, workflow, and management as follows. A two-pizza team will: Be small. No more than ten people. Be autonomous. They should have no need to coordinate with other teams to get their work done. With the new service-based software architecture in place, any team could simply refer to the published application programming interfaces (APIs) for other teams. (More on this new software architecture to follow.) Be evaluated by a well-defined “fitness function.” This is the sum of a weighted series of metrics. Example: a team that is in charge of adding selection in a product category might be evaluated on: a)  how many new distinct items were added for the period (50 percent weighting) b)  how many units of those new distinct items were sold (30 percent weighting) c)  how many page views those distinct items received (20 percent weighting) Be monitored in real time. A team’s real-time score on its fitness function would be displayed on a dashboard next to all the other two-pizza teams’ scores. Be the business owner. The team will own and be responsible for all aspects of its area of focus, including design, technology, and business results. This paradigm shift eliminates the all-too-often heard excuses such as, “We built what the business folks asked us to, they just asked for the wrong product,” or “If the tech team had actually delivered what we asked for and did it on time, we would have hit our numbers.” Be led by a multidisciplined top-flight leader. The leader must have deep technical expertise, know how to hire world-class software engineers and product managers, and possess excellent business judgment. Be self-funding. The team’s work will pay for itself. Be approved in advance by the S-Team. The S-Team must approve the formation of every two-pizza team.

Any one-level theory of objective reality that ignores the separate reality-tunnels in which these people are living existentially has no validity in psychology, and, with a little analysis, it is obvious that no such one-level theory has any general validity in sociology either. To understand human behavior, we have to understand human evaluations (neuro-linguistic programs) and modern social scientists of all schools increasingly recognize that human evaluations (internal reality-tunnels) depend on both the external environment (setting) and the internal environment (neuro-linguistic programs).

When people say an artist has a thick skin, what they mean is not that the person is dense or numb, but that he has seated his professional consciousness in a place other than his personal ego. It takes tremendous strength of character to do this, because our deepest instincts run counter to it. Evolution has programmed us to feel rejection in our guts. This is how the tribe enforced obedience, by wielding the threat of expulsion. Fear of rejection isn't just psychological; it's biological. It's in our cells. Resistance knows this and uses it against us. It uses fear of rejection to paralyze us and prevent us, if not from doing our work, then from exposing it to public evaluation.

Just as the United States helped create the prosperity that enabled the Party’s control, U.S. technology has been copied, repurposed, and enhanced to secure that control—sometimes with investment from U.S. venture capital. Across China, a program known as Police Cloud allows for the collection and integration of previously unimaginable amounts of information: who you’re in contact with, what you buy, where you travel, when you shop, whether you pay your parking tickets, and so on. A “social credit” system allows the government to affix a score to someone: How reliable are you? Could you pose a threat of some sort? You live your life with the knowledge that the sum total of your actions could be evaluated by someone, somewhere, with some purpose. This creates incentives and disincentives, given the reach of the Party into people’s lives. Disincentives are clear: Say the wrong thing, and you could end up detained. But the incentives may be even more powerful: Want a good job? Want your kids to get into a good school? You may have to consider those aspirations with everything you do.

Just as the Five Tribes and others were formalizing their tribal governments and running their own programs, legal aid groups were helping nonrecognized tribes do the same: the two were on a collision course. One result was the Federal Acknowledgment Process, establsiehd within the BIA in 1978. Its rigorous criteria and evaluation process reflected the desires of the Five Tribes and many other reservation tribes to have a stringent regimen, on that protected their rights, economic resources, and overall ability to define ‘Indians” and “tribes.” Throughout these debates pulsed questions of “authenticity” and being “real” or “bona fide” Indians and tribes. While academics and unrecognized tribes questioned the ability of any party to accurately define “Indian” and “tribe,” as a practical political and cultural matter tribes and their federal allies groped toward a way to measure and define these highly problematic terms. By 1978 leaders of federally recognized tribes felt they had found the answer in the new Federal Acknowledgment Process, with many unrecognized groups agreeing that finally a way had been found to determine what group were “real” tribes.

It is possible to identify numerous ways that students with disabilities are controlled and taught their place: (1) labeling; (2) symbols (e.g., white lab coats, “Handicapped Room” signs); (3) structure (pull-out programs, segregated classrooms, “special” schools, inaccessible areas); (4) curricula especially designed for students with disabilities (behavior modification for emotionally disturbed kids, training skills without knowledge instruction for significantly mentally retarded students and students with autistic behavior) or having significant implications for these students; (5) testing and evaluation biased toward the functional needs of the dominant culture (Stanford-Binet and Wexler tests); (6) body language and disposition of school culture (teachers almost never look into the eyes of students with disabilities and practice even greater patterns of superiority and paternalism than they do with other students); and (7) discipline (physical restraints, isolation/time-out rooms with locked doors, use of Haldol and other sedatives).11

Monte Carlo tree search makes predictions by generating examples (rollouts) and then makes a prediction based on the experience of this algorithm with these examples. Modern variations of Monte Carlo tree search further combine tree search with reinforcement learning and deep learning in order to improve predictions. Deep learning is used in order to learn the evaluation function instead of using domain knowledge. For example, AlphaZero uses Monte Carlo tree search for rollouts, while also using deep learning to evaluate the quality of the moves and guide the search. The Monte Carlo tree together with the deep learning models form the hypothesis used by the program in order to move moves. Note that these hypotheses are created using the statistical patterns of empirical behavior in games.

Monte Carlo trees tend to explore a few promising branches deeper based on evaluations from previous experience, whereas minimax trees explore all unpruned branches in a roughly similar way. The human approach to chess is similar to the former, wherein humans evaluate a small number of promising directions of play rather than exhaustively considering all possibilities. The result is that the style of chess from Monte Carlo tree search is more similar to humans than that from minimax trees. The programs resulting from Monte Carlo trees can often take more risks in game playing, if past experience has shown that such risks are warranted over the longer term. On the other hand, minimax trees tend to discourage any risks beyond the horizon of tree exploration, especially since the evaluations at leaf levels are imperfect.

Many females have a problem not only with stereotypes, but with other people’s opinions of them in general. They trust them too much... This vulnerability afflicts many of the most able, high-achieving females. Why should this be? When they’re little, these girls are often so perfect, and they delight in everyone’s telling them so. They’re so well behaved, they’re so cute, they’re so helpful, and they’re so precocious. Girls learn to trust people’s estimates of them. “Gee, everyone’s so nice to me; if they criticize me, it must be true.” Even females at the top universities in the country say that other people’s opinions are a good way to know their abilities. Boys are constantly being scolded and punished. When we observed in grade school classrooms, we saw that boys got eight times more criticism than girls for their conduct. Boys are also constantly calling each other slobs and morons. The evaluations lose a lot of their power. Even when women reach the pinnacle of success, other people’s attitudes can get them... The fixed mindset, plus stereotyping, plus women’s trust in people’s assessments: I think we can begin to understand why there’s a gender gap in math and science. That gap is painfully evident in the world of high tech. Julie Lynch, a budding techie, was already writing computer code when she was in junior high school. Her father and two brothers worked in technology, and she loved it, too. Then her computer programming teacher criticized her. She had written a computer program and the program ran just fine, but he didn’t like a shortcut she had taken. Her interest evaporated. Instead, she went on to study recreation and public relations. Math and science need to be made more hospitable places for women. And women need all the growth mindset they can get to take their rightful places in these fields.

Now, those who enjoy theological and/or demonological speculations may continue to enjoy them, as far as I care. This book merely attempts to clarify the difference between theological speculations and actual experiences in space-time, so that we do not wander into theology without realizing where we have gotten ourselves. The Supreme Court, for instance, wandered into theology (or demonology) when it proclaimed that "fuck" "is" an indecent word. The most one can say about that in scientific E-Prime would read: "The word 'fuck' appears indecent in the evaluations of X per cent of the population," X found by normal polling methods.

General Semantics has influenced recent psychology and social science greatly but has had little effect on physical sciences or education and virtually no effect on the problems it attempted to alleviate — i.e., the omnipresence of unacknowledged bigotry and unconscious prejudice in most human evaluations.

There is nothing magical about effective intervention strategies. They are based on over forty years of evaluations of hundreds of programs.

We can freely imagine several teleological futures before we act, each with a roughly equal likelihood of being enacted, and then evaluate them and reach our decision as to which is best. The smarter, the more imaginative and creative we are, the more futures we can conceive. Until we carry out our evaluation of the futures that we have freely conceived, we cannot know what we will do. An android cannot conceive futures, and carries out a program written for him by its Creator (programmer). Sam Harris keeps slipping into the tacit claim that humans are programmed machines rather than free people.

When people are used to evaluating their productivity locally, they feel that a good day is one in which they did their job well all day. When I worked as a programmer, that meant eight straight hours of programming without interruption. That was a good day. In contrast, if I was interrupted with questions, process, or—heaven forbid—meetings, I felt bad. What did I really accomplish that day? Code and product features were tangible to me; I could see them, understand them, and show them off. Learning, by contrast, is frustratingly intangible. The Lean Startup asks people to start measuring their productivity differently.

At the organizational level, this value can take the form of acquiring the capacity to sustain ongoing evaluative inquiry. This outcome is more likely when participants experience evaluation as a meaningful and productive way to enhance patterns of work and communication. Participatory, collaborative, appreciative, and empowering mechanisms are often at the heart of evaluations where process use is a high priority. These mechanisms can promote stakeholder ownership of the evaluation processes and products and thus enhance process use, as well as use of evaluation findings. For some organizations, evaluation capacity building means that evaluation stakeholders learn how to work effectively with external evaluators. This organizational learning further facilitates the contributions that external evaluation processes and findings can make to the organization’s growth and productivity.

To initiate its EIR program, USCIS would also turn to an agitator. Brad Feld, an early-stage investor and prolific blogger, had become exasperated when officers of two promising startups under his watch were forced to return to their home countries because they couldn’t secure visas. He shared their story on a blog, attracting the attention of other entrepreneurs, including Ries, who couldn’t understand why there was no visa category for an entrepreneur with American investors and employees. In lieu of that category, many entrepreneurs were at the mercy of visa examiners who didn’t understand how they operated. At the point of visa application, many startups had not hired many employees or generated much revenue. This confused traditional visa examiners, who would then ask odd and irrelevant questions, often before a denial. To give just one example, it’s been years since AOL required a compact disc to use its service. And yet, visa examiners were demanding proof of a warehouse, where software startups would store their CD inventory for shipping to customers. As Feld’s idea of a “startup visa” became intertwined with, and paralyzed by, the broader debate on comprehensive immigration reform, the USCIS, with White House support, sought to accomplish something administratively within the existing law. It instituted an EIR program, to organize and educate a specialty unit of immigration officers to handle entrepreneur and startup nonimmigrant visa cases.22 The project also called for educating entrepreneurs about the available options, one of which they may have overlooked. For instance, the O-1 visa, which was reserved “for those with extraordinary ability,” had proven a successful channel for actors, athletes, musicians, directors, scientists, artists, businessmen, engineers, and others who could provide ample evidence of their unique and impressive abilities, attributes, awards, and accolades. It had even created some controversy, when visa evaluators took the term “model” to an extreme, awarding a visa to one of Hugh Hefner’s ex-girlfriends, a Playboy centerfold from Canada named Shera Berchard.23 If she was confident enough to assert and explain her “extraordinary ability,” why weren’t entrepreneurs?

A program in Madagascar that simply told parents about the average income gains from spending one more year in school for children from backgrounds similar to theirs had a sizable positive effect on test scores, and, in the case of parents who found out that they had underestimated the benefits of education, the gains were twice as large.40 An earlier study in the Dominican Republic produced similar results with high school students.41 Since it is essentially free to have teachers simply pass on information to parents, this is so far the cheapest known way to improve test scores, among all the interventions that have been evaluated

Standard A1 acknowledges that accuracy in evaluation contexts is not established in a universal sense. Ideas and meanings expressed in specific languages can change over time, places, individuals, and groups. For conclusions to be accurate in a practical sense such that their consequences are justified, they must be understood within the contexts where the languages and concepts that support them can be applied. Part of the rationale for Standard A1 is to call attention to this practicality while emphasizing the key importance of sound methods in specific contexts.

When Bouchard’s twin-processing operation was in full swing, he amassed a staff of eighteen—psychologists, psychiatrists, ophthalmologists, cardiologists, pathologists, geneticists, even dentists. Several of his collaborators were highly distinguished: David Lykken was a widely recognized expert on personality, and Auke Tellegen, a Dutch psychologist on the Minnesota faculty, was an expert on personality measuring. In scheduling his twin-evaluations, Bouchard tried limiting the testing to one pair of twins at a time so that he and his colleagues could devote the entire week—with a grueling fifty hours of tests—to two genetically identical individuals. Because it is not a simple matter to determine zygosity—that is, whether twins are identical or fraternal—this was always the first item of business. It was done primarily by comparing blood samples, fingerprint ridge counts, electrocardiograms, and brain waves. As much background information as possible was collected from oral histories and, when possible, from interviews with relatives and spouses. I.Q. was tested with three different instruments: the Wechsler Adult Intelligence Scale, a Raven, Mill-Hill composite test, and the first principal components of two multiple abilities batteries. The Minnesota team also administered four personality inventories (lengthy questionnaires aimed at characterizing and measuring personality traits) and three tests of occupational interests. In all the many personality facets so laboriously measured, the Minnesota team was looking for degrees of concordance and degrees of difference between the separated twins. If there was no connection between the mean scores of all twins sets on a series of related tests—I.Q. tests, for instance—the concordance figure would be zero percent. If the scores of every twin matched his or her twin exactly, the concordance figure would be 100 percent. Statistically, any concordance above 30 percent was considered significant, or rather indicated the presence of some degree of genetic influence. As the week of testing progressed, the twins were wired with electrodes, X-rayed, run on treadmills, hooked up for twenty-four hours with monitoring devices. They were videotaped and a series of questionnaires and interviews elicited their family backgrounds, educations, sexual histories, major life events, and they were assessed for psychiatric problems such as phobias and anxieties. An effort was made to avoid adding questions to the tests once the program was under way because that meant tampering with someone else’s test; it also would necessitate returning to the twins already tested with more questions. But the researchers were tempted. In interviews, a few traits not on the tests appeared similar in enough twin pairs to raise suspicions of a genetic component. One of these was religiosity. The twins might follow different faiths, but if one was religious, his or her twin more often than not was religious as well. Conversely, when one was a nonbeliever, the other generally was too. Because this discovery was considered too intriguing to pass by, an entire additional test was added, an existing instrument that included questions relating to spiritual beliefs. Bouchard would later insist that while he and his colleagues had fully expected to find traits with a high degree of heritability, they also expected to find traits that had no genetic component. He was certain, he says, that they would find some traits that proved to be purely environmental. They were astonished when they did not. While the degree of heritability varied widely—from the low thirties to the high seventies— every trait they measured showed at least some degree of genetic influence. Many showed a lot.

We even evaluated rebates and points-based programs similar to the airlines’, but there’s an important difference between airlines and retailers. Once a plane takes off, its empty seats have no value. Therefore, airlines, in exchange for loyalty, can give away marginal inventory that would otherwise go unsold. Whereas in retail, giving away either product or shipping fees always has a cost. None of the ideas made it very far because they could not meet the three essential criteria.

The purpose of any program evaluation is to provide some kind of counterfactual against which a treatment or intervention can be measured. In the case of a randomized, controlled experiment, the control group is the counterfactual. In cases where a controlled experiment is impractical or immoral, we need to find some other way of approximating the counterfactual. Our understanding of the world depends on finding clever ways to do that.

Natural Ways to Help Depression Depression is not one illness. Like anxiety, the pandemic spawned a whole new level of people being diagnosed with depression and placed on antidepressant medication, without ever getting a proper evaluation or trying simple fixes. Here are nine common things I do for patients before prescribing antidepressant medication. 1. Check for and (if necessary) correct thyroid hormone abnormalities. 2. Work with a nutritionally informed physician to optimize your folate, vitamin B12, vitamin D, homocysteine, and omega-3 fatty acids. I’m convinced that without doing these nutritional fixes, patients are less likely to respond to the medications. 3. Try an elimination diet for three weeks. 4. Add colorful fruits and vegetables into your diet. 5. Eliminate the ANTs (automatic negative thoughts). See days 22, 116–117. 6. Exercise—walk like you are late for 45 minutes four times a week. This has been found to be as effective as antidepressant medication.[1] 7. Add one of the following supplements to your daily routine: Saffron 30 mg/day; curcumin, not as turmeric root but as Longvida, which is much more efficiently absorbed; zinc as citrate or glycinate 30 mg (tolerable upper level is 40 mg/day for adults, 34 mg/day for adolescents, less for younger kids); or magnesium glycinate, citrate, or malate, 100–500 mg with 30 mg of vitamin B6. 8. Consume probiotics daily. 9. Try morning bright light therapy with a therapeutic lamp of 10,000 lux for 20–30 minutes. If someone comes to me with depression, I order screening labs, teach them not to believe every negative thought they have, give them basic supplements (saffron, zinc, curcumins, and omega-3s), and encourage them to exercise. Many people never need medication if they follow through with the program. If the above interventions are ineffective, I’ll try other nutraceuticals or medications targeted to their specific type of depression (take the test at brainhealthassessment.com).

Nerds are used to transparency. They add value by becoming expert at a technical skill like computer programming. In engineering disciplines, a solution either works or it fails. You can evaluate someone else’s work with relative ease, as surface appearances don’t matter much. Sales is the opposite: an orchestrated campaign to change surface appearances without changing the underlying reality. This strikes engineers as trivial if not fundamentally dishonest. They know their own jobs are hard, so when they look at salespeople laughing on the phone with a customer or going to two-hour lunches, they suspect that no real work is being done. If anything, people overestimate the relative difficulty of science and engineering, because the challenges of those fields are obvious. What nerds miss is that it takes hard work to make sales look easy.

Prioritizing Your Email Roadmap Chances are you’ll need a Hail Mary. And a Net Promoter Score survey email. And a newsletter. And… And… And… If you are getting started with your email program, the list of emails you’ll need will probably be very long. Do you need to do everything at once? Definitely not. In fact, it’s best to start your program by aligning with business priorities and getting results before thinking about expanding. What areas are most troublesome in your business right now? What metric are you expected to move with email? Is it: Engagement? Retention? Conversion? Revenue? Signups? If none of those stick out above the rest, start from the top. Welcome and onboarding emails set the tone for product usage. Better onboarding and value communication lead to reductions in churn and disengagement down the road. Welcome and onboarding emails are also sent to most, if not all, of your users, thus they have a greater potential to influence user behaviors. At Highlights, for example, we set up a welcome email, five onboarding emails, and an upsell email the week before we launched the product. The goal was to maximize the number of people in a position to convert. It also allowed us to start getting some data to optimize performance. In general, you’ll want to prioritize emails that: send a lot (large volume of sends); send consistently (every day, or every week at least); and have the potential to have a big impact on a key business goal. In the beginning especially, you want to make sure that you have a clear goal or metric to monitor with the aim of evaluating performance with user data. Start implementing a first sequence, test, gather data, and move on to the next sequence.

Does It “Really” Need to Be an Email? By this point, you’ve probably figured out that I love email. Well, in spite of my love for email marketing, not every communication needs to be an email. In fact, there are times when emails really aren’t the best solution. So, if not email, what else? Other solutions include: In-App messages like popups, sidebars, site notifications, chat messages, browser or push notifications, desktop notifications, text messages, and even product tours and onboarding flows. Email is great when the user isn’t currently using your product. It’s great to drive them back in, but when they are right there using your product, you can’t expect them to be checking their emails at the same time. Before setting up a new email campaign, ask yourself if email is the best way to achieve your objective and drive the user behavior you seek. Maybe a popup or site notification would be more effective. Users can’t typically unsubscribe from popups, sidebars, site notifications, chat messages, or onboarding flows. They are usually better embedded into your app and more contextual. Because of this, they tend to reach users more directly than email can. That means that they can often be more effective to influence user behaviors. Push notifications, desktop notifications, and text messages still have some novelty to them. They can also reach users in different contexts from email. Although sometimes it’s better to use a different communication type, sometimes combining email with other options is the best way to go. For this reason, it’s important to consider the mix. For example, an email followed on-site by an In-App message, or an onboarding flow followed by an email summing up the process may be more effective than a single email. It will allow you to follow up on user actions, and make it really clear what needs to get done. By breaking down the steps one at a time, there’s more chances for users to learn. At LANDR, we often followed feature launch emails on-site with In-App messages. This helped to keep communications simple and goal-focused (one goal per message). The email was about getting people in the product, while the In-App message was about getting them to engage with the product. This approach allows you to evaluate and optimize each step of the process independently. Automation platforms like Intercom, ActiveCampaign and HubSpot generally allow you to combine messaging types. If your platform doesn’t currently have site messaging or onboarding functionalities, you may have to use multiple tools in conjunction in order to maximize results. This will make it trickier to track pacing, sequencing, and goals but it isn’t impossible. You also need to consider tracking effort when adding new communication types to your mix. As your program becomes more complex, it can be easy to lose track of the overall user experience: Are your users getting spammed? Are you creating a disjointed customer experience? Test things from your users’ perspective. Keep an eye out for social media messages and support requests as you do. In the next chapter we will look at setting up automations to minimize issues and maximize outcomes.

Naturally occurring processes are often informally modeled by priority queues. Single people maintain a priority queue of potential dating candidates, mentally if not explicitly. One’s impression on meeting a new person maps directly to an attractiveness or desirability score, which serves as the key field for inserting this new entry into the “little black book” priority queue data structure. Dating is the process of extracting the most desirable person from the data structure (Find-Maximum), spending an evening to evaluate them better, and then reinserting them into the priority queue with a possibly revised score.

Once we’ve evaluated sensory input as worth paying attention to, interpreted (created meaning) and consciously or subconsciously decided (created a belief and expectations) on what to do with this information, our brain stops being curious and runs the now established program instead.

The idea of saving 200 people in Program A is literally a “no-brainer,” says Gonzales. Because Program A is framed as a sure gain, “it’s a simple alternative that can be evaluated at very low cognitive cost,” she explains. And this frame suggests no emotional cost, since it calls your attention to the lives saved rather than the lives lost. You can see how little effort the brain takes to evaluate this choice in the top left of Figure 6.1. On the other hand, when a risk is framed negatively—for instance, by stressing those 400 lost lives—then it incites images and ignites emotions. The thought of losing money, like losing lives, is so inherently alarming that it ends up triggering intense activation in an area of your brain called the intraparietal sulcus. This curving wrinkle of tissue, located toward the top of your head behind your ears, appears to function somewhat like a mental movie screen. It enables you to visualize and imagine the consequences of actions not yet taken. The more uncertain the consequences are, the more active the intraparietal sulcus becomes.

More often, then, we will be doing evaluation of programs not with respect to one another but with respect to a situation—a total situation —in which they are developed. Looking honestly at the situation, we are never looking for the best program, seldom looking for a good one, but always looking for one that meets the requirements.

management as follows. A two-pizza team will: Be small. No more than ten people. Be autonomous. They should have no need to coordinate with other teams to get their work done. With the new service-based software architecture in place, any team could simply refer to the published application programming interfaces (APIs) for other teams. (More on this new software architecture to follow.) Be evaluated by a well-defined “fitness function.” This is the sum of a weighted series of metrics.

Based on the initial analysis, I recommend that the company expand Program B in the short term for the following reasons: Currently, Program A is losing money and cannot sustain itself. Program B is highly profitable. If we can expand the program by just X percent, the company can break even quickly. There are risks involved in expanding Program B, in particular the reputation risk. But due to the short-term nature of the expansion, these risks can be minimized. Given more time, we should evaluate options to turn around Program A and to unwind Program B.

However, little evidence exists to suggest that doctoral programs support the development of doctoral students as teachers, let alone as interculturally aware teachers. Teaching development is not integrated in program requirements. We are not aware of doctoral-level qualifying exams that evaluate one’s capacity to teach in addition to theory, content, and research capabilities. Even when teaching assistantships are available for funding and accruing experience, they rarely occur in the context of a programmatic approach to using that assistantship/practice to develop graduate students as educators, to generate reflection toward future and ongoing development.

His name is C. J. Skender, and he is a living legend. Skender teaches accounting, but to call him an accounting professor doesn’t do him justice. He’s a unique character, known for his trademark bow ties and his ability to recite the words to thousands of songs and movies on command. He may well be the only fifty-eight-year-old man with fair skin and white hair who displays a poster of the rapper 50 Cent in his office. And while he’s a genuine numbers whiz, his impact in the classroom is impossible to quantify. Skender is one of a few professors for whom Duke University and the University of North Carolina look past their rivalry to cooperate: he is in such high demand that he has permission to teach simultaneously at both schools. He has earned more than two dozen major teaching awards, including fourteen at UNC, six at Duke, and five at North Carolina State. Across his career, he has now taught close to six hundred classes and evaluated more than thirty-five thousand students. Because of the time that he invests in his students, he has developed what may be his single most impressive skill: a remarkable eye for talent. In 2004, Reggie Love enrolled in C. J. Skender’s accounting class at Duke. It was a summer course that Love needed to graduate, and while many professors would have written him off as a jock, Skender recognized Love’s potential beyond athletics. “For some reason, Duke football players have never flocked to my class,” Skender explains, “but I knew Reggie had what it took to succeed.” Skender went out of his way to engage Love in class, and his intuition was right that it would pay dividends. “I knew nothing about accounting before I took C. J.’s class,” Love says, “and the fundamental base of knowledge from that course helped guide me down the road to the White House.” In Obama’s mailroom, Love used the knowledge of inventory that he learned in Skender’s class to develop a more efficient process for organizing and digitizing a huge backlog of mail. “It was the number-one thing I implemented,” Love says, and it impressed Obama’s chief of staff, putting Love on the radar. In 2011, Love left the White House to study at Wharton. He sent a note to Skender: “I’m on the train to Philly to start the executive MBA program and one of the first classes is financial accounting—and I just wanted to say thanks for sticking with me when I was in your class.

Despite his harsh criticisms Gates admired programmers and invariably put them in charge of projects, where they could both manage and program. While this double duty was stressful, Gates wanted to avoid a situation in which professional managers, with either no programming experience or out-of-date knowledge, held sway. It was destructive to rely on management pros to run software teams—or the company. They could not distinguish a promising program from a bust or evaluate schedules or product designs. At companies run by professionals, managers almost always came to mistrust their programmers, whom they could neither understand nor control. Gates

Others, such as Alan Lightman, or Erez Lieberman, who earned fame by the age of thirty-one through his combination of mathematics and cultural studies, or Esther Duflo, who won a MacArthur “Genius Grant” for her work evaluating anti-poverty programs, didn’t make the cut for the book, but still weigh heavily on my thinking about how to best shape my own career. It

under the law, schools were required to evaluate a child and formulate an individualized education program, or an IEP, to set forth the services and support he was supposed to receive and to help him achieve in his areas of need.

Discussed in this chapter are the major elements of how to develop adaptive leaders for the future. They include: (1) the adaptive course model (ACM); (2) the ACM Program of Instruction (POI); (3) the establishment of teachers of adaptability (TA), through a certification process and implementation of tools they can employ to develop adaptability; and (4) the Leader Evaluation System, or LES. Taken together, they form the beginning of the new leader education revolution.

Just as you need to dedicate time in your schedule to complete your process goals and success logs, you need to enter time for quarterly evaluations on your calendar. Identify

Using a reality-based evaluation, assess exactly where you are on each one of your three product goals. On

slip. When you do your evaluations (whether daily or quarterly), use only the true reality of results and avoid letting your mind make judgments based on potential.

Make the commitment to the daily and quarterly performance evaluations, and you will be well on your way to developing your accountability and becoming the person you so desire to become.

One of the little-known secrets of successful individuals is that those who are most successful evaluate themselves daily. Daily evaluation is the key to daily success, and daily success is the key to success in life and career.

Exercise 1.3: Experiment to measure the difference in running time between our potentially inefficient versions and the one that uses strings.Join. (Section 1.6 illustrates part of the time package, and Section 11.4 shows how to write benchmark tests for systematic performance evaluation.)