Post C Section Quotes

Remember to write continuously the entire twenty minutes. And never forget that this writing is for you and you alone. At the conclusion of your twenty minutes of writing, read the section “Post-writing thoughts” and complete the post-writing questionnaire. Post-Writing Thoughts Following the Day One Writing Session Congratulations! You have completed the first day of writing. After each writing exercise, it can be helpful to make objective assessments about how the writing felt. In this way, you can go back and determine which writing methods are most effective for you. For this and for all future writing exercises, respond to each of the five following questions either at the end of your writing or in a separate place. Put a number between 0 and 10 by each question. 0 — Not at all 1 2 3 4 5— Somewhat 6 7 8 9 10— A great deal ____ A. To what degree did you express your deepest thoughts and feelings? ____ B. To what degree do you currently feel sad or upset? ____ C. To what degree do you currently feel happy? ____ D. To what degree was today’s writing valuable and meaningful for you? E. Briefly describe how your writing went today so you may refer to this later. For many people, the first day of writing is the most difficult. This kind of writing can bring up emotions and thoughts that you may not have known that you had. It may also have flowed much more easily than you expected — especially if you wrote about something that you have been keeping to yourself for a long time. If you don’t want anyone to see your writing, keep the pages in a secure place or destroy them. If keeping them is not a problem, you can go back and analyze the pages at the end of the four days of writing. Now, take some time for yourself. Until tomorrow.

The reality is that there is a huge section of this country that feels like D.C. is filled with a bunch of self-serving careerists who’ve never built anything in their lives, and that Wall Street is filled with people making ungodly amounts of money, and Silicon Valley is just totally disconnected from everyone, and all of them are trying to tell me how to live my life,” he says. “If you put aside all the stupid, offensive shit that Trump does and says, the fact is that he is posing some big, important questions about how we are thinking about our labor pool, our trade agreements, NATO, and our international relationships.

Beyond One-Way ANOVA The approach described in the preceding section is called one-way ANOVA. This scenario is easily generalized to accommodate more than one independent variable. These independent variables are either discrete (called factors) or continuous (called covariates). These approaches are called n-way ANOVA or ANCOVA (the “C” indicates the presence of covariates). Two way ANOVA, for example, allows for testing of the effect of two different independent variables on the dependent variable, as well as the interaction of these two independent variables. An interaction effect between two variables describes the way that variables “work together” to have an effect on the dependent variable. This is perhaps best illustrated by an example. Suppose that an analyst wants to know whether the number of health care information workshops attended, as well as a person’s education, are associated with healthy lifestyle behaviors. Although we can surely theorize how attending health care information workshops and a person’s education can each affect an individual’s healthy lifestyle behaviors, it is also easy to see that the level of education can affect a person’s propensity for attending health care information workshops, as well. Hence, an interaction effect could also exist between these two independent variables (factors). The effects of each independent variable on the dependent variable are called main effects (as distinct from interaction effects). To continue the earlier example, suppose that in addition to population, an analyst also wants to consider a measure of the watershed’s preexisting condition, such as the number of plant and animal species at risk in the watershed. Two-way ANOVA produces the results shown in Table 13.4, using the transformed variable mentioned earlier. The first row, labeled “model,” refers to the combined effects of all main and interaction effects in the model on the dependent variable. This is the global F-test. The “model” row shows that the two main effects and the single interaction effect, when considered together, are significantly associated with changes in the dependent variable (p < .000). However, the results also show a reduced significance level of “population” (now, p = .064), which seems related to the interaction effect (p = .076). Although neither effect is significant at conventional levels, the results do suggest that an interaction effect is present between population and watershed condition (of which the number of at-risk species is an indicator) on watershed wetland loss. Post-hoc tests are only provided separately for each of the independent variables (factors), and the results show the same homogeneous grouping for both of the independent variables. Table 13.4 Two-Way ANOVA Results As we noted earlier, ANOVA is a family of statistical techniques that allow for a broad range of rather complex experimental designs. Complete coverage of these techniques is well beyond the scope of this book, but in general, many of these techniques aim to discern the effect of variables in the presence of other (control) variables. ANOVA is but one approach for addressing control variables. A far more common approach in public policy, economics, political science, and public administration (as well as in many others fields) is multiple regression (see Chapter 15). Many analysts feel that ANOVA and regression are largely equivalent. Historically, the preference for ANOVA stems from its uses in medical and agricultural research, with applications in education and psychology. Finally, the ANOVA approach can be generalized to allow for testing on two or more dependent variables. This approach is called multiple analysis of variance, or MANOVA. Regression-based analysis can also be used for dealing with multiple dependent variables, as mentioned in Chapter 17.

In sum, in light of the breadth of Section 1512(c)(2) and the other obstruction statutes, an argument that the conduct at issue in this investigation falls outside the scope of the obstruction laws lacks merit.

My niece, Anna, told about a poignant moment with her eight-year-old daughter. I love myself but I hate my thighs. I do. I also hate my post-baby, three-times-C-sectioned tummy. No matter how many planks, sit-ups, or miles I run, it will never be like it was when I was in college. And that makes me sad, frustrated, and sometimes angry. When my sweet husband tells me I look beautiful, instead of just thanking him, I answer back with a caveat: “Thanks, but I look fat.” I do this in front of my kids sometimes without realizing it. My boys always come back with, “No way, Mom. You look awesome” or “We think you’re beautiful!” But my daughter is just quiet. Watching. Listening. Later she’ll come up to me, hug me, and whisper, “I love you so much, Mommy.” A couple of months ago, when she was all dressed up, I saw her looking at herself in the mirror. I stopped and said, “Lillian, you look absolutely stunning!” She turned around and said to me very matter of fact, “No I don’t. I look fat.” I gasped! Doesn’t she know how precious she is? Doesn’t she know how beautiful she is? What a blessing she is? Doesn’t she know what a miracle her very existence is? And then I remembered all the times I answered her dad with the very same words. I was sad, ashamed, and most of all heartbroken. Lillian was eight years old. She understood that “fat” was how I felt about myself, so she decided she should feel that way too. Lillian and I had a long talk that day. I told her what a blessing her life is, and how God made her special, unique, and beautiful. I also apologized to her, my two sons, and my husband for not loving myself like I should. Lately, I’ve been saying “thank you” when I get compliments—something new to me—and it’s made all the difference. Now when I tell Lillian how gorgeous she is (which is all the time), she looks at me with her bright hazel eyes and says, “Thanks, Mommy! I think you’re really beautiful too!

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