Low Key Relationship Quotes

Then when Matt had come along it hadn't been fireworks, passion and fights and drama. It had been low- key, sweet, lovely. But that didn't meant it wasn't the real thing. It never had done. Just because it wasn't suprising hadn't meant it wasn't right.

If women were as libidinous as men, we’re told, society itself would collapse. Lord Acton was only repeating what everyone knew in 1875 when he declared, “The majority of women, happily for them and for society, are not very much troubled with sexual feeling of any kind.” And yet, despite repeated assurances that women aren’t particularly sexual creatures, in cultures around the world men have gone to extraordinary lengths to control female libido: female genital mutilation, head-to-toe chadors, medieval witch burnings, chastity belts, suffocating corsets, muttered insults about “insatiable” whores, pathologizing, paternalistic medical diagnoses of nymphomania or hysteria, the debilitating scorn heaped on any female who chooses to be generous with her sexuality…all parts of a worldwide campaign to keep the supposedly low-key female libido under control. Why the electrified high-security razor-wire fence to contain a kitty-cat?

She dances, She dances around the burning flames with passion, Under the same dull stars, Under the same hell with crimson embers crashing, Under the same silver chains that wires, All her beauty and who she is inside, She's left with the loneliness of human existence, She's left questioning how she's survived, She's left with this awakening of brutal resilience, Her true beauty that she denies, As much she's like to deny it, As much as it continues to shine, That she doesn't even have to admit, Because we all know it's true, Her glory and success, After all she's been through, Her triumph and madness, AND YET, SHE STANDS. Broken legs- but she's still standing, Still dancing in this void, You must wonder how she's still dancing, You must wonder how she's not destroyed, She doesn't even begin to drown within the flames, But little do you realize, Within these chains, She weeps and she cries, But she still goes on, And just you thought you could stop her? You thought you'd be the one? Well, let me tell you, because you thought wrong. Nothing will ever silence her, Because I KNOW, I know that she is admiringly strong, Her undeniable beauty, The triumph of her song, She's shining bright like a ruby, Reflecting in the golden sand, She's shining brighter like no other, She's far more than human or man, AND YET, SHE STANDS. She continues to dance with free-spirit, Even though she's locked in these chains, Though she never desired to change it, Even throughout the agonizing pain, Throughout all the distress, Anxiety, depression, tears and sorrow, She still dances so beautify in her dress, She looks forward to tomorrow, Not because of a fresh start but a new page, A new day full of opportunities, Despite being trapped in her cage, She still smiles after being beaten so brutally, A smile that could brighten anyone's day, She's so much more than anyone could ask for, She's so much more than I could ever say, She's a girl absolutely everyone should adore, She never gets in the way, Even after her hearts been broken, Even after the way she has been treated, After all these severe emotions, After all all the blood she's bled, AND YET, SHE STANDS. Even if sometimes she wonders why she's still here, She wonders why she's not dead, But there's this one thing that had been here throughout every tear, Throughout the blazing fire leaving her cheeks cherry red, Everyday this thing has given her a place to exist, This thing, person, these people, Like warm sunlight it had so softly kissed, The apples of her cheeks, Even when she's feeling feeble, Always there at her worst and at her best Because of you and all the other people, She has this thing deep inside her chest, That she will cherish forever, Even once you're gone, Because today she smiles like no other, Even when the sun sets at dawn, Because today is the day, She just wants you to remember, In dark and stormy weather, It gets better. And after what she's been through she knows, Throughout the highs and the lows, Because of you and all others, After crossing the seas, She has come to understand, You have formed this key, This key to free her from this land, This endless gorge that swallowed her, Her and other men, She had never knew, nor had she planned, That because of you, She's free. AND YET, THIS VERY DAY, SHE DANCES. EVEN IN THE RAIN.

When I describe for my far-away friends the Northwest’s subtle shades of weather — from gloaming skies of ‘high-gray’ to ‘low-gray’ with violet streaks like the water’s delicate aura — they wonder if my brain and body have, indeed, become water-logged. Yet still, I find myself praising the solace and privacy of fine, silver drizzle, the comforting cloaks of salt, mold, moss, and fog, the secretive shelter of cedar and clouds. Whether it’s in the Florida Keys, along the rocky Maine coast, within the Gulf of Mexico’s warm curves, on the brave Outer Banks; or, for those who nestle near inland seas, such as the brine-steeped Great Salk Lake or the Midwest’s Great Lakes — water is alive and in relationship with those of us who are blessed with such a world-shaping, yet abiding, intimate ally. Every day I am moved by the double life of water — her power and her humility. But most of all, I am grateful for the partnership of this great body of inland sea. Living by water, I am never alone. Just as water has sculpted soil and canyon, it also molds my own living space, and every story I tell. …Living by water restores my sense of balance and natural rhythm — the ebb and flow of high tides and low tides, so like the rise and fall of everyday life. Wind, water, waves are not simply a backdrop to my life, they are steady companions. And that is the grace, the gift of inviting nature to live inside my home. Like a Chambered Nautilus I spin out my days, drifting and dreaming, nurtured by marine mists, like another bright shell on the beach, balancing on the back of a greater body.

Each of the eight scales represents one key area that managers must be aware of, showing how cultures vary along a spectrum from one extreme to its opposite. The eight scales are:        •  Communicating: low-context vs. high-context        •  Evaluating: direct negative feedback vs. indirect negative feedback        •  Persuading: principles-first vs. applications-first        •  Leading: egalitarian vs. hierarchical        •  Deciding: consensual vs. top-down        •  Trusting: task-based vs. relationship-based        •  Disagreeing: confrontational vs. avoids confrontation        •  Scheduling: linear-time vs. flexible-time

But in the Europe of 1903–14, the reality was even more complex than the ‘international’ model would suggest. The chaotic interventions of monarchs, ambiguous relationships between civil and military, adversarial competition among key politicians in systems characterized by low levels of ministerial or cabinet solidarity, compounded by the agitations of a critical mass press against a background of intermittent crisis and heightened tension over security issues made this a period of unprecedented uncertainty in international relations. The policy oscillations and mixed signalling that resulted made it difficult, not just for historians, but for the statesmen of the last pre-war years to read the international environment. It would be a mistake to push this

We have witnessed hundreds of clients and patients damage their metabolic and hormonal health through low-carb diets. It is becoming increasingly apparent that there is an epidemic of metabolic and hormonal dysfunction emerging in the hordes of people who have been following low-carb diets. This is particularly impactful for women—and especially physically active women—who commonly suffer side effects from their low-carb diets, including: A stopped or irregular menstrual cycle (amenorrhea)418 419 420 421 422 Decreased fertility423 424 425 Hypoglycemic episodes and blood sugar swings426 Depression, anxiety, and irritability427 428 429 Poor libido430 431 432 Disrupted sleep/insomnia433 434 Dysfunctional relationship with food and fear about eating either fat or carbohydrate435 436 Cycles of restriction and binges437 438 Chronic fatigue 439 440 441 442 Poor thyroid function (and a slow metabolism)443 444 445 446 447 448

Back in bed I listen to every sound. The plastic tarp over the table on the balcony crunching in the cold wind. the two short clicks in the walls before the heat comes on with a low whoosh. I hear a constant base hum all around, the nervous system of the building, carrying electricity and gas and phone conversations to all our respective little boxes. I listen to it all, the constant, the rhythmic, and the random. It's hard to measure the night by sound, but it can be done. I know that when the traffic noise is quietest, it's about 4:30 in the morning. I know that when the 'Times' hits the door, it's around 5. Now the clock says it's morning, 5:45, but the November sky still says midnight. I hear the elevator ding twenty yards down the hall outside our door. Seven seconds later, I hear his keys in our lock, then his heavy backpack hitting the floor. I hear the refrigerator door open, the unsealing vacuum wheezing as the cold inside air meets the dry heat in the apartment. The cupboard door. A glass. The crescendoing fizz of a new two-liter Diet Coke bottle opening. It's a one-sided conversation with no one actually talking. I lie in the dark, close my eyes, and try not to listen to his movements around apartment. these are the sounds of our life together before it got so messy. I want to say something back. Anything, anything that sounds like things sounded last summer. Even just to myself. Just something out loud. The inside of my eyelids turn pink. My door has been opened and the light from the hallway shines through them. I won't open them. There is no noise. Like an eclipse, the world behind my closed eyes goes dark again. For just one second, before I feel a kiss on my right eye. I keep them closed. A kiss on the left one. I open them. Jack looks down at me and closes his eyes. He leans forward and puts his forehead on my chest and goes limp. ''Blues Clues' is on,' he says softly into my tee shirt. His muffled voice vibrating only a half inch away from my heart.

[A] central theme is why social, political, and economic institutions tend to coevolve in a manner that reinforces rather than undermines one another. The welfare state is not 'politics against markets,' as commonly assumed, but politics with markets. Although it is popular to think that markets, especially global ones, interfere with the welfare state, and vice versa, this notion is simply inconsistent with the postwar record of actual welfare state development. The United States, which has a comparatively small welfare state and flexible labor markets, has performed well in terms of jobs and growth during the past two decades; however, before then the countries with the largest welfare states and the most heavily regulated labor markets exceeded those in the United States on almost any gauge of economic competitiveness and performance. Despite the change in economic fortunes, the relationship between social protection and product market strategies continues to hold. Northern Europe and Japan still dominate high-quality markets for machine tools and consumer durables, whereas the United States dominates software, biotech, and other high-tech industries. There is every reason that firms and governments will try to preserve the institutions that give rise to these comparative advantages, and here the social protection system (broadly construed to include job security and protection through the industrial relations system) plays a key role. The reason is that social insurance shapes the incentives workers and firms have for investing in particular types of skills, and skills are critical for competitive advantage in human-capital-intensive economies. Firms do not develop competitive advantages in spite of systems of social protection, but because of it. Continuing this line of argument, the changing economic fortunes of different welfare production regimes probably has very little to do with growing competitive pressure from the international economy. To the contrary, it will be argued in Chapter 6 that the main problem for Europe is the growing reliance on services that have traditionally been closed to trade. In particular, labor-intensive, low-productivity jobs do not thrive in the context of high social protection and intensive labor-market regulation, and without international trade, countries cannot specialize in high value-added services. Lack of international trade and competition, therefore, not the growth of these, is the cause of current employment problems in high-protection countries.

values and coefficients are they key regression output. Collectively, these statistics indicate whether the variables are statistically significant and describe the relationships between the independent variables and the dependent variable. Low p-values (typically < 0.05) indicate that the independent variable is statistically significant. Regression analysis is a form of inferential statistics. Consequently, the p-values help determine whether the relationships that you observe in your sample also exist in the larger population. The coefficients for the independent variables represent the average change in the dependent variable given a one-unit change in the independent variable (IV) while controlling the other IVs.

In person, Mr. Desmond mixes low-key friendliness and on-message discipline.

Thus, multiple regression requires two important tasks: (1) specification of independent variables and (2) testing of the error term. An important difference between simple regression and multiple regression is the interpretation of the regression coefficients in multiple regression (b1, b2, b3, …) in the preceding multiple regression model. Although multiple regression produces the same basic statistics discussed in Chapter 14 (see Table 14.1), each of the regression coefficients is interpreted as its effect on the dependent variable, controlled for the effects of all of the other independent variables included in the regression. This phrase is used frequently when explaining multiple regression results. In our example, the regression coefficient b1 shows the effect of x1 on y, controlled for all other variables included in the model. Regression coefficient b2 shows the effect of x2 on y, also controlled for all other variables in the model, including x1. Multiple regression is indeed an important and relatively simple way of taking control variables into account (and much easier than the approach shown in Appendix 10.1). Key Point The regression coefficient is the effect on the dependent variable, controlled for all other independent variables in the model. Note also that the model given here is very different from estimating separate simple regression models for each of the independent variables. The regression coefficients in simple regression do not control for other independent variables, because they are not in the model. The word independent also means that each independent variable should be relatively unaffected by other independent variables in the model. To ensure that independent variables are indeed independent, it is useful to think of the distinctively different types (or categories) of factors that affect a dependent variable. This was the approach taken in the preceding example. There is also a statistical reason for ensuring that independent variables are as independent as possible. When two independent variables are highly correlated with each other (r2 > .60), it sometimes becomes statistically impossible to distinguish the effect of each independent variable on the dependent variable, controlled for the other. The variables are statistically too similar to discern disparate effects. This problem is called multicollinearity and is discussed later in this chapter. This problem is avoided by choosing independent variables that are not highly correlated with each other. A WORKING EXAMPLE Previously (see Chapter 14), the management analyst with the Department of Defense found a statistically significant relationship between teamwork and perceived facility productivity (p <.01). The analyst now wishes to examine whether the impact of teamwork on productivity is robust when controlled for other factors that also affect productivity. This interest is heightened by the low R-square (R2 = 0.074) in Table 14.1, suggesting a weak relationship between teamwork and perceived productivity. A multiple regression model is specified to include the effects of other factors that affect perceived productivity. Thinking about other categories of variables that could affect productivity, the analyst hypothesizes the following: (1) the extent to which employees have adequate technical knowledge to do their jobs, (2) perceptions of having adequate authority to do one’s job well (for example, decision-making flexibility), (3) perceptions that rewards and recognition are distributed fairly (always important for motivation), and (4) the number of sick days. Various items from the employee survey are used to measure these concepts (as discussed in the workbook documentation for the Productivity dataset). After including these factors as additional independent variables, the result shown in Table 15.1 is

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

The two women stepped back and looked at one another. “You look great!” they said simultaneously. Rachel tugged Ivy to the side of the concourse to avoid other passengers. “Sit, sit,” she said as she lowered herself back onto the bench. “Did you find a dress you want to wear?” “Yes, but I still don’t understand why you’re low-keying such a momentous occasion as your wedding.” “Luke and I love each other. Our relationship is so special that we don’t need all that hoo-haw. That’s why I told you just to find a nice gown.” “Speaking of Luke…” Ivy’s head swiveled from one side to the other. “Where is the man? I thought you two were inseparable.” Rachel

driven responses. It is the healthy development of the right orbitofrontal cortex and its links to the amygdala that enables us to have a wide window of tolerance for intense emotions and to respond flexibly and adaptively to our interpersonal world. Next, Sieff asked how the relationship between an infant and its caregiver shape the development of the emotional right brain. Schore answered that genes code for when the various components of the emotional brain come on-line, but how each area develops depends on the infant’s epigenetically shaped emotional experiences with his primary caregiver. Those experiences, as John Bowlby first described, are circumscribed by the infant’s innate drive to become emotionally bonded to his or her primary caregiver. The infant’s experiences with his caregiver are internalized through changes in his rapidly developing brain. Typically, an attuned caregiver will minimize the infant’s discomfort, fear and pain, and, as importantly, creates opportunities for the child to feel joy and excitement. The caregiver will also mediate the transition between these emotional states. Mirroring by the attuned caretaker amplifies the infant’s emotional state. In physics, when two systems match it creates what is called “resonance,” whereby the amplitude of each system is increased, comparable to face-to-face play between an infant and an attuned caretaker who creates emotional resonance and amplifies joy. Together, infant and mother move from low arousal to high positive arousal which helps the infant to extend his window of tolerance for intense positive emotions, a key developmental task. At other times the emotional intensity becomes more than the infant can tolerate, and he will avert his gaze. When this happens, an attuned mother intuitively disengages from the infant and reduces her stimulation. Then she waits for her baby to signal his readiness to re-engage. The more the mother tunes her activity level to the infant during periods of engagement and the more she allows him to recover quietly in periods of disengagement, and the

If I had to characterize the key difference between a high-quality and a low-quality preschool environment, it is this: in a high-quality program, adults are building relationships with children and paying a lot of attention to children’s thinking processes and, by extension, their communication.

romantic consumerism. ‘my needs aren’t being met,’ ‘this marriage is not working for me anymore,’ ’it’s not the deal i signed up for’ - these are laments i hear regularly in my sessions. as psychologist and author Bill Doherty observes, these kinds of statements apply the values of consumerism - ‘personal gain, low cost, entitlement, and hedging one’s bets - to our romantic connections’. (…) in our consumer society, novelty is key.

But her first instincts had been right. He was a good husband, a wonderful father and stepfather. He brought her a cup of tea in bed every morning and rubbed her feet at night when she was tired. And they’d made beautiful children together, she thought fondly, as she put Jacob’s breakfast on the high chair in front of him. Both their sons were a perfect blend of the two of them, with ruddy chestnut hair and hazel eyes. Only Emily looked like she didn’t belong. She was growing more like her biological father with every passing year. As she stirred the lumps out of Jacob’s cereal, Maddie felt an unexpected rush of tears. She blinked them back, cursing the pregnancy hormones that left her so vulnerable. Emily’s father, Benjamin, had been her first boyfriend, a veterinary student in his final year at the same college as she when they’d met. Quiet and painfully shy, Maddie had always found it hard to make friends, having been raised by a widowed mother too busy with her charitable causes to have time to show Maddie how to have fun. At twenty-one, she’d never even been on a date until Benjamin asked her to join him at a lecture about animal husbandry. Somehow, Benjamin had got under her skin. Theirs had been a gentle, low-key relationship, a slow burn born of shared interests and companionship. It wasn’t love, exactly, but it was warm and reassuring and safe. Eight months after they’d met, she’d lost her virginity to him in an encounter that, like the relationship itself, was unremarkable but quietly satisfying. The pregnancy a year later had been a complete accident. To her surprise, Benjamin had been thrilled. They’d both graduated college by then, and while she made next to nothing at the sanctuary, he was earning enough as a small animal vet to look after them both. He bought dozens of books on fatherhood and had picked out names – Emily for a girl, Charlie for a boy – before Maddie had been for her first scan. He was so excited about becoming a

Mechanism of Statin Drug Benefit Chapter Summary and Key Points. ·       I support the idea of statin use for high risk people, but at non-cholesterol lowering doses (low dose). · Any cardiovascular risk benefit from statins has no relationship to cholesterol reduction. ·       In addition to blockading cholesterol production, dolichols, CoQ10, selenoproteins and Rho are equally diminished by the effect of statins. · Like aspirin, statins reduce the production of the blood clotting agent thromboxane. ·       Blood levels of hs-CRP (high sensitivity C-reactive protein) — an inflammatory marker — are also reduced by statins. ·       Aspirin has shown benefit in both primary and secondary prevention of heart attacks and strokes. · Ora Shovman concluded that inflammation was the cause of atherosclerosis. · Statins show cardiovascular benefits for their anti-inflammatory effect. · Even at a very low dose of a statin, inflammation is suppressed substantially. ·       Studies are needed to see whether statin sensitive people can tolerate low dose statins without the often debilitating side effects from higher doses.