How To Use Parentheses In Quotes

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You want to stay here and sleep your life away? That's it?" "If you knew what would make you happy, wouldn't you do it?" I asked her. "See, you do want to be happy. Then why did you tell me that being happy is dumb?" she asked. "You said that to me more than once." "Let me be dumb," I said, glugging the NyQuil. "You go be smart and tell me how great it is. I'll be here, hibernating." Reva rolled her eyes. "It's natural," I told her. "People used to hibernate all the time." "People never hibernated. Where are you getting this?" She could look really pathetic when she was outraged. She got up and stood there holding her stupid knockoff Kate Spade bag or whatever it was, her hair pulled back into a ponytail and crowned with a useless, plastic, tortoiseshell headband. She was always getting her hair blown out, her eyebrows waxed into thin, arched, parentheses, her fingernails painted various shades of pink and purple, as though all of this made her a wonderful person. "It's not up for discussion, Reva. This is what I'm doing. If you can't accept it, then you don't have to.
Ottessa Moshfegh (My Year of Rest and Relaxation)
Regular expressions are widely used for string matching. Although regular-expression systems are derived from a perfectly good mathematical formalism, the particular choices made by implementers to expand the formalism into useful software systems are often disastrous: the quotation conventions adopted are highly irregular; the egregious misuse of parentheses, both for grouping and for backward reference, is a miracle to behold. In addition, attempts to increase the expressive power and address shortcomings of earlier designs have led to a proliferation of incompatible derivative languages.
Chris Hanson (Software Design for Flexibility: How to Avoid Programming Yourself into a Corner)
A Poetry Reading at West Point I read to the entire plebe class, in two batches. Twice the hall filled with bodies dressed alike, each toting a copy of my book. What would my shrink say, if I had one, about such a dream, if it were a dream? Question and answer time. “Sir,” a cadet yelled from the balcony, and gave his name and rank, and then, closing his parentheses, yelled “Sir” again. “Why do your poems give me a headache when I try to understand them?” he asked. “Do you want that?” I have a gift for gentle jokes to defuse tension, but this was not the time to use it. “I try to write as well as I can what it feels like to be human,” I started, picking my way care- fully, for he and I were, after all, pained by the same dumb longings. “I try to say what I don’t know how to say, but of course I can’t get much of it down at all.” By now I was sweating bullets. “I don’t want my poems to be hard, unless the truth is, if there is a truth.” Silence hung in the hall like a heavy fabric. My own head ached. “Sir,” he yelled. “Thank you. Sir.
Anthony Holden (Poems That Make Grown Men Cry: 100 Men on the Words That Move Them)
COEFFICIENT The nonparametric alternative, Spearman’s rank correlation coefficient (r, or “rho”), looks at correlation among the ranks of the data rather than among the values. The ranks of data are determined as shown in Table 14.2 (adapted from Table 11.8): Table 14.2 Ranks of Two Variables In Greater Depth … Box 14.1 Crime and Poverty An analyst wants to examine empirically the relationship between crime and income in cities across the United States. The CD that accompanies the workbook Exercising Essential Statistics includes a Community Indicators dataset with assorted indicators of conditions in 98 cities such as Akron, Ohio; Phoenix, Arizona; New Orleans, Louisiana; and Seattle, Washington. The measures include median household income, total population (both from the 2000 U.S. Census), and total violent crimes (FBI, Uniform Crime Reporting, 2004). In the sample, household income ranges from $26,309 (Newark, New Jersey) to $71,765 (San Jose, California), and the median household income is $42,316. Per-capita violent crime ranges from 0.15 percent (Glendale, California) to 2.04 percent (Las Vegas, Nevada), and the median violent crime rate per capita is 0.78 percent. There are four types of violent crimes: murder and nonnegligent manslaughter, forcible rape, robbery, and aggravated assault. A measure of total violent crime per capita is calculated because larger cities are apt to have more crime. The analyst wants to examine whether income is associated with per-capita violent crime. The scatterplot of these two continuous variables shows that a negative relationship appears to be present: The Pearson’s correlation coefficient is –.532 (p < .01), and the Spearman’s correlation coefficient is –.552 (p < .01). The simple regression model shows R2 = .283. The regression model is as follows (t-test statistic in parentheses): The regression line is shown on the scatterplot. Interpreting these results, we see that the R-square value of .283 indicates a moderate relationship between these two variables. Clearly, some cities with modest median household incomes have a high crime rate. However, removing these cities does not greatly alter the findings. Also, an assumption of regression is that the error term is normally distributed, and further examination of the error shows that it is somewhat skewed. The techniques for examining the distribution of the error term are discussed in Chapter 15, but again, addressing this problem does not significantly alter the finding that the two variables are significantly related to each other, and that the relationship is of moderate strength. With this result in hand, further analysis shows, for example, by how much violent crime decreases for each increase in household income. For each increase of $10,000 in average household income, the violent crime rate drops 0.25 percent. For a city experiencing the median 0.78 percent crime rate, this would be a considerable improvement, indeed. Note also that the scatterplot shows considerable variation in the crime rate for cities at or below the median household income, in contrast to those well above it. Policy analysts may well wish to examine conditions that give rise to variation in crime rates among cities with lower incomes. Because Spearman’s rank correlation coefficient examines correlation among the ranks of variables, it can also be used with ordinal-level data.9 For the data in Table 14.2, Spearman’s rank correlation coefficient is .900 (p = .035).10 Spearman’s p-squared coefficient has a “percent variation explained” interpretation, similar
Evan M. Berman (Essential Statistics for Public Managers and Policy Analysts)
Key to the Pronunciations This dictionary uses a simple respelling system to show how entries are pronounced, using the symbols listed below. Generally, only the first of two or more identical headwords will have a pronunciation respelling. Where a derivative simply adds a common suffix such as -less, -ness, or -ly to the headword, the derivative may not have a pronunciation respelling unless some other element of the pronunciation also changes. as in hat //, fashion // as in day //, rate // as in lot //, father //, barn // as in big // as in church //, picture // as in dog //, bed // as in men //, bet //, ferry // as in feet //, receive // as in air //, care // as in soda //, mother /, her // as in free //, graph //, tough // as in get //, exist // as in her //, behave // as in fit //, women // as in time /t/, hire //, sky // as in ear //, pierce // as in judge //, carriage // as in kettle //, cut //, quick // as in lap //, cellar //, cradle // as in main //, dam // as in need //, honor //, maiden // as in sing //, anger // as in go //, promote // as in law //, thought //, lore // as in boy //, noisy // as in wood //, sure // as in food //, music // as in mouse //, coward // as in put //, cap // as in run //, fur //, spirit // as in sit //, lesson //, face // as in shut //, social // as in top //, seat //, forty // as in thin //, truth // as in then //, father // as in very //, never // as in wait //, quit // as in when //, which // as in yet //, accuse // as in zipper //, musician // as in measure //, vision // Foreign Sounds as in Bach // as in en route //, Rodin / / as in hors d’oeuvre //, Goethe // as in Lully //, Utrecht // Stress Marks Stress (or accent) is represented by marks placed before the affected syllable. The primary stress mark is a short, raised vertical line // which signifies that the heaviest emphasis should be placed on the syllable that follows. The secondary stress mark is a short, lowered vertical line // which signifies a somewhat weaker emphasis than on the syllable with primary stress. Variant Pronunciations There are several ways in which variant pronunciations are indicated in the respellings. Some respellings show a pronunciation symbol within parentheses to indicate a possible variation in pronunciation; for example, in sandwich //. Variant pronunciations may be respelled in full, separated by semicolons. The more common pronunciation is listed first, if this can be determined, but many variants are so common and widespread as to be ofequal status. Variant pronunciations may be indicated by respelling only the part of the word that changes. A hyphen will replace the part of the pronunciation that has remained the same. Note: A hyphen sometimes serves to separate syllables where the respelling might otherwise look confusing, as at reinforce //.
Oxford University Press (The New Oxford American Dictionary)
Surely a young beauty like yourself is lonely, too. It can be a part of the game, if you like.” “Get off,” she said, thoroughly done with this. His answer was to lean in closer. So she kneed him in the groin. As hard as she could. “Aw, ow, dammit!” He doubled over and thudded onto his knees. Jane brushed off her knee, feeling like it had touched something dirty. “Aw, ow, dammit indeed! What’re you thinking?” Jane heard hurried footsteps coming down the stairs. It was Mr. Nobley. “Miss Erstwhile!” He was barefoot in his breeches, his shirt untucked. He glanced down at the groaning man. “Sir Templeton!” “Ow, she kicked me,” said Sir Templeton. “Kneed him, I kneed him,” Jane said. “I don’t kick. Not even when I’m a ninja.” Mr. Nobley stood a moment in silence, looking over the scene. “I hope you remembered to shout ‘Ya’ when taking him down. I hear that is very effective.” “I’m afraid I neglected that bit, but I’ll certainly ‘ya’ from here to London if he ever touches me again.” “Miss Erstwhile, were you perhaps employed by your president’s armed forces in America?” “What? Don’t British women know how to use their knees?” “Happily, I have never put myself in a position to find out.” He stared at the prostrate Sir Templeton. “Did he hurt you?” “Frankly, your arm-yanking earlier was worse.” “I see. Perhaps you should retire to your chambers, Miss Erstwhile. Would you like me to escort you?” “I’m fine,” she said, “as long as there aren’t any other Sir Templetons lurking upstairs.” “Well, I cannot give Colonel Andrews a glowing reference, but I believe the way is safe.” She stepped closer to Mr. Nobley and whispered, “Are you going to out me to Mrs. Wattlesbrook for the servants’ quarters lurking?” “I think,” he said, nudging the prostrate Sir Templeton with his foot, “that you have suffered enough tonight.” Mr. Nobley smiled at her, the first time she had seen his real smile. She wouldn’t go so far as to call it a grin. His lips were closed, but his eyes brightened and the corners of his mouth definitely turned up, creating pleasing little cheek wrinkles on either side as though the smile were in parentheses. It bothered her in a way she couldn’t explain, like feeling itchy but not knowing exactly where to scratch. He was not particularly amused, she saw, but smiled to reassure her. Wait, who wanted to reassure her? Mr. Nobley or the actual man, Actor X? “Thanks. Good night, Mr. Nobley.” “Good night, Miss Erstwhile.” She hesitated, then left, Sir Templeton’s groans following her up the stairs. On the second floor, Aunt Saffronia was emerging from her room, clutching a white shawl over her nightgown. “What was that noise? Is everything all right?” “Yes. It was…your husband. He was being inappropriate.” Aunt Saffronia blinked. “Inebriated?” “Yes.” She nodded slowly. “I’m sorry, Jane.” Jane wasn’t sure if Aunt Saffronia was speaking to Jane the niece or Jane the client. For the first time it didn’t matter; both Janes felt exactly the same. She acknowledged the apology with a nod, went to her room, and locked the door behind her. She thought she was angry but instead she plopped herself down on her bed, put her face in her pillow, and laughed. “What a joke,” she said, sounding to herself like the movie incarnation of Lydia Bennet. “I come for Mr. Darcy, fall for the gardener, and get propositioned by the drunk husband.” Tomorrow would be different. Tomorrow she would play for real. She was going to drive full force into the game, have a staggering good time, and kick the nasty Darcy habit for good. She fell asleep with the ticklish thought of Mr. Nobley’s smile.
Shannon Hale (Austenland (Austenland, #1))