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[Assistant] And the reality is that antibiotics have been responsible for saving millions of lives since penicillin, one of the earliest antibiotics, was first used on a clinical basis 70 years ago.


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[Assistant] However, today is a new era in which taking antibiotics can cause some very dangerous and potentially life threatening situations.


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[Assistant] In fact, you may have heard about the new superbugs, which are antibiotic resistant bacteria


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[Assistant] Health experts warned us that the day would come in which it would become very difficult to provide medical care for even common problems, such as lung infection or severe sore throat.


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[Assistant] And apparently that day has come because seemingly routine operations such as knee replacements are now much more hazardous due to the looming threat of these infections.


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[Assistant] From the funds necessary for a problem of such magnitude.


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[Assistant] Directions In this section you will hear three recordings of lectures or talks followed by three or four questions. The recordings will be played only once.


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[Assistant] After you hear a question, you must choose the best answer from the four choices marked A, B, C and D.


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[Assistant] Then mark the corresponding letter on answer sheet 1 with a single line through the center.


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[Assistant] Question 16 to 18 are based on the recording you have just heard. Question 16.


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[Assistant] Psychological research shows we consistently underestimate our mental powers. If you think this does not apply to you


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[Assistant] Write down the names of all the American states you can remember.


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[Assistant] Provided you have not cheated by consulting an Atlas, you will notice something rather surprising.


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[Assistant] The two lists will contain roughly the same number of states, but they will not be identical.


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[Assistant] Some names will have slipped away, but others will have replaced them.


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[Assistant] This suggests that somewhere in your mind, you may well have a record of virtually every state.


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[Assistant] We would remember a lot more if we had more confidence in our memories and knew how to use them properly.


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[Assistant] One useful tip is that things are more likely to be remembered if you are in exactly the same state and place as you were when you learned them.


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[Assistant] So if you are a student who always reviews over black coffee,


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[Assistant] Perhaps it would be sensible to prime yourself with a cup before the exam. If possible,


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[Assistant] You should also try to learn information in the room where it is going to be tested. When you learn is also important.


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[Assistant] Lots of people swear they can absorb new information more efficiently at some times of the day than at others. Research shows this is not just imagination. There is a biological rhythm for learning.


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[Assistant] Though it affects different people in different ways, for most of us, the best plan is to take in new information in the morning.


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[Assistant] You can do this by learning a set number of lines of poetry at different times of the day and seeing when most lines stick.


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[Assistant] When you have done this, try to organize your life, so that the time set aside for learning coincides with the time when your memory is at its best. Avoid learning marathons. They do not make the best use of your mind.


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[Assistant] Take plenty of breaks, because they offer a double bonus.


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[Assistant] The time off gives your mind a chance to do some preliminary consolidation, and it also gives a memory boost to the learning.


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[Assistant] Questions 23 to 25 are based on the recording you have just heard. Question 23. What does this speaker


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[Assistant] Where does the speaker say we can find extreme poverty?


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[Assistant] What do we learn about American people living in relative poverty?


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[Assistant] The wind stopped howling and a brilliant blue sky stretched over the moor.


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[Assistant] The moor itself looked soft blue instead of gloomy purple black or awful dreary grey.


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[Assistant] When Mary awoke, she sat up in bed and called to Martha.


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[Assistant] Martha was in high spirits that morning because it was her day off.


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[Assistant] She gave Mary her breakfast, and then she was going home to the cottage. She wouldn't be back until the next morning.


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[Assistant] After Martha left, Mary felt lonelier than ever.


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[Assistant] She went outside, and the first thing she did was run around the fountain ten times.


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[Assistant] Then she ran into the kitchen gardens and found Ben Weatherstaff at work. The change in the weather seemed to have done him good.


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[Assistant] Springtime's comin', he said cheerfully. Can you smell it? Mary sniffed the air.


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[Assistant] Mary heard the soft rustling of wings, and there was the robin looking right at her.


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[Assistant] 10 years was a long time. She was 10 years old herself. Mary slowly walked away, lost in thought.


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[Assistant] She had begun to like the garden just as she had begun to like Dickon and Martha and their mother too.


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[Assistant] That seemed a lot of people to like when you weren't used to liking people. She also counted the Robin as a person.


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[Assistant] She spotted him again as she was strolling along her favorite path outside the kitchen gardens.


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[Assistant] He was pecking in the earth and pretending that he hadn't followed her, but Mary knew he had.


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[Assistant] She chirped and talked and coaxed, while he hopped and twittered.


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[Assistant] The robin allowed her to move closer and closer to him.


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[Assistant] Then Mary saw him stop to look for a worm near a pile of freshly turned up dirt. An animal must have been digging in the garden.


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[Assistant] As she watched the robin, she spotted something half buried in the little pile of soil.


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[Assistant] It looked like a ring of brass or rusty iron.


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[Assistant] When the robin flew up into a nearby tree, Mary picked up the ring.


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[Assistant] But it wasn't a ring. It was an old key. Mary stared in amazement at the key in her hand.


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[Assistant] Yes ma'am, I understand. You want more than just the math answer. You want me to explain how I got the answer. I copied it from the kid behind me. Actually ma'am, I don't understand this problem. Of course, I don't understand math at all. Let's face it, I don't even understand school.


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[Assistant] On this test ma'am, do you want our last name first or our first name first? How about a middle initial? Should we put down a middle initial? Okay, I gotcha. Not used to dealing with a perfectionist, huh ma'am?


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[Assistant] You look, Marcy. I hate seeing what my grade is. Explain World War II.


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[Assistant] In 1066, Napoleon crossed the Mississippi River. I'll bet the teacher has fun correcting your test papers, sir. She probably has friends over and makes it into a big party.


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[Assistant] Mother will be pleased when I tell her what skipping rope has done for you.


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[Assistant] Those are bulbs. Lots of spring flowers grow from them. Snowdrops, crocuses, daffodils, lilies. Dickens got a whole lot of them planted in our bit of a garden.


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[Assistant] That's just what Mother suggested. At Thwait Village, there's a shop where they sell little garden sets. And they sell packages of flower seeds.


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[Assistant] He walks to Thwait almost every day, and he knows all about growing things. Oh, you are so nice.


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[Assistant] Maybe me and my buddy will do a little routine. We call it Sad Valentine.


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[Assistant] In this last module I want to give you a few last tips for your very final draft. Before you send something off to your editor or to a journal, there's a checklist that you should go through.


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[Assistant] Once the prose is sounding good, there are a few other things that I want to make sure you check.


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[Assistant] Before you submit your final draft, you should check for consistency. And in particular, for numerical consistency.


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[Assistant] You also want to make sure that your references are not what I call references to nowhere. I'll talk more about this in a minute.


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[Assistant] Checking for consistency means making sure that you don't have things that are contradictory in different places in the manuscript. This happens often.


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[Assistant] I was editing somebody's work and in the methods section they said, we followed participants for a minimum of two years.


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[Assistant] But in the results section, they said that the follow-up time, the average follow-up time was one and a half years.


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[Assistant] Clearly the average follow-up can't be one and a half years if the minimum follow-up is two years. So this was an inconsistency.


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[Assistant] Maybe they meant to say that they had a maximum follow-up of two years or that they aimed to follow participants for two years.


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[Assistant] But if a reviewer or editor sees this kind of inconsistency, it raises a lot of red flags.


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[Assistant] I see numerical inconsistencies a lot when I'm reviewing papers.


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[Assistant] For example, I've seen a lot of papers where the abstract reports different numbers than the body of the paper.


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[Assistant] This may result from sloppy cutting and pasting or because authors redo an analysis, but maybe they forget to update the entire manuscript.


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[Assistant] I was reviewing one paper where the numbers in a table and figure should have been identical, but they didn't match. Uh, so I suspected that the authors had more than one version of their dataset running around.


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[Assistant] If you can't keep track of your data set, that makes me worry about the whole analysis. So you want to make sure that your basic numbers match throughout your paper. Otherwise it raises all sorts of red flags.


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[Assistant] You want to make sure that you don't have what I call references to nowhere.


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[Assistant] This is when the authors cite a reference, but when you look up that paper, it does not contain the information that the authors indicated was available there.


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[Assistant] I am often checking references for various reasons, such as to track down original sources, and I have found that the majority, the majority of the time,


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[Assistant] Oftentimes, uh, authors will misinterpret or exaggerate the findings from the original source. If you go back to the original reference, turns out that the citing authors were selective in the information that they chose to mention in their paper.


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[Assistant] Or authors cite a paper to support a particular statement.


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[Assistant] But that statement is not in fact supported by the original reference. It might be supported in some roundabout way, but not directly.


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[Assistant] Another common problem is that citing authors often cite secondary sources rather than original sources. I call this citation propagation.


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[Assistant] Maybe Jones and Al does the original study. They come up with a statistic.


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[Assistant] Then Smith et al. wants to cite that statistic, so they cite Jones et al.


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[Assistant] But then, Barry and Al gives the statistic in their paper


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[Assistant] And instead of citing Jones et al., they cite Smith. They read the statistic in Smith's paper so they don't bother to go back to get the original reference. Then James et al. cites Beery et al. for this statistic and so on.


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[Assistant] It reminds me of the game of telephone that children play.


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[Assistant] If you're not familiar with that game, that's where children sit in a circle.


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[Assistant] The first child comes up with a sentence and they whisper that sentence into the ear of the next child.


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[Assistant] And then that child whispers it into the ear of the next child and so forth.


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[Assistant] The last child says out loud what they heard and it's always something that's garbled and funny and that has little resemblance to the original sentence.


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[Assistant] This is exactly what happens in the scientific literature when you cite secondary rather than original sources.


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[Assistant] You lose important pieces of information down the citation chain and often things get completely jarable.


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[Assistant] Using a reference manager program like EndNote can help avoid that kind of problem.


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[Assistant] But here's an example. I was writing about UVC light a few years back and I was reading a paper. I got to this sentence.


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[Assistant] I was writing for a lay audience and I thought, great, this is a very easy comparison that anybody can understand. Ambient light on a mountain.


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[Assistant] I wanted to use this comparison in my story, so I needed to go back to the original references to verify its accuracy.


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[Assistant] I also had a question because when they said it's larger than ambient sunlight on a mountain, they didn't give any time frame. Is it larger than the amount that you get in one minute on the mountain? Is it larger than the amount that you get in an hour?


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[Assistant] Well, first I went to reference 13, it was a URL, uh, but the link was broken. It brought me to a website, but I got an error message. I searched all over that website and I could find no relevant information about UBC emissions on a mountain.


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[Assistant] Fortunately, they had given two references, so I still had hope. So I went to reference 14, uh, which was a paper.


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[Assistant] I scanned through the paper, I did a word search on the paper, it did not contain the words ambient, sunlight, mountain, or UVC.


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[Assistant] It was a reference to nowhere because the paper contained nothing to support the author's statement. I was out of luck. So always double check your references.


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[Assistant] And here is finally an example of citation propagation, where citations get garbled through the literature like a game of telephone because authors fail to cite original sources.


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[Assistant] When I was a graduate student, I worked on something called Female Athlete Triad.


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[Assistant] One of the components of the triad is disordered eating.


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[Assistant] People would always want to know how common is disordered eating in female athletes.


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[Assistant] At the time that I was a graduate student in the late 1990s, there was a hallmark statistic that everybody cited.


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[Assistant] The statistic was that 15 to 62% of female athletes have disordered eating.


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[Assistant] This statistic appeared in every paper on female athlete triad or eating disorders in athletes. Everybody used this statistic.


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[Assistant] But everybody cited different sources for this statistic. At one point I was trying to trace back to where this statistic came from and I found about 50 different attributions for the statistic.


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[Assistant] Well obviously that statistic came from somewhere, so everybody was just citing secondary sources. And I'll just give you some examples. Uhm, I found


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[Assistant] Neither of those is the original source. The original source is actually from the 1980s. I'll show you in a minute.


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[Assistant] Just another example. I found in a fact sheet on eating disorders among female athletes, the prevalence of eating disorders is reported to be between 15% and 62%. They cite a book. So again, a secondary source.


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[Assistant] In a 2000 review paper in the American Family Physician,


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[Assistant] They say, although the exact prevalence of the female athlete triad is unknown, studies have reported disordered eating behavior in 15-62% of female college athletes. No citation was given there.


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[Assistant] Uh, and then in a 2004 paper in the Sport Journal, studies report between 15% and 62% of college women engage in problematic weight control behaviors. They cite a 2000 paper, Barry and Howe,


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[Assistant] Well, I actually went and pulled that 2000 paper, Barry and Howe.


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[Assistant] And guess what? It doesn't contain any mention of the statistic whatsoever. So it's a reference to nowhere. Not only is it not the original source, but it doesn't even talk about the statistic in that paper.


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[Assistant] Interestingly, I found the following statement in a 1999 New York Times article, and actually they got the closest to getting this right.


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[Assistant] They say, but informal surveys suggest that 15% to 62% of female athletes are affected by disordered behavior that ranges from a preoccupation with losing weight to anorexia or bulimia. Informal surveys is actually right on the money.


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[Assistant] So I know that some fact checker at the New York Times actually went back and found the original source for this statistic.


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[Assistant] A publication like the New York Times has a superb fact checking department.


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[Assistant] Unfortunately, few scientific journals have fact-checking departments to double-check sources like this.


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[Assistant] Out of curiosity, at some point as a graduate student, I got interested in where this statistic actually came from. And I tracked down the original sources, which took some sleuthing on my part.


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[Assistant] The statistic comes from three papers that were published in the 1980s. The 15% value comes from a 1987 paper.


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[Assistant] All three studies shared an author, Rosen, but notice that all three studies were from the 1980s and this statistic was being secade, uh, cited decades later.


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[Assistant] These were cross-sectional surveys, self-report with no non-athlete control groups.


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[Assistant] And they weren't random samples of athletes. They were just convenience samples.


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[Assistant] The 1986 study surveyed varsity athletes from some midwestern universities in a whole bunch of sports.


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[Assistant] The 1987 study was on 9 to 18 year old swimmers at a particular swim camp. These weren't even college athletes, though sometimes when the statistic is cited people say college athletes.


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[Assistant] And the final study looked at just 42 college gymnasts.


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[Assistant] So these are totally non-representative samples across a wide range of athletic groups with no controls.


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[Assistant] And uhm, what the studies considered disordered eating was also poorly conceived and poorly measured. I don't want to go into a lot of detail, but if you're curious, there was a wide range in what they were defining as disordered eating and the definition differed for those three different surveys.


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[Assistant] Uh, here are a few more details about the findings if you're curious, but the bottom line is this statistic was widely used as if it was the gold standard. It was used everywhere in the literature.


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[Assistant] But it basically had no meaning because it came from studies that were old and that were inherently limited by their low quality design.


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[Assistant] So my take home message is you always want to cite the primary source. Take the time to go back to the primary source.


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[Assistant] Don't just cut and paste other authors' citations and assume they are correct. Because more often than not, those authors have made errors in their citing.


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[Assistant] Dig back to the original source and get it right.


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[Assistant] And you must not expect that there will be people to talk to you.


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[Assistant] You'll be told what rooms you can go into and what rooms you're to keep out of.


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[Assistant] Open your eyes. We're at the wait station and we have a long drive ahead of us.


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[Assistant] If you look out the window in about ten minutes, you'll see one.


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[Assistant] You won't see much because it's a dark night, but you can see something.


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[Assistant] The moor is a dreary place, though there are plenty of people who like it, especially when the heather is in bloom.


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[Assistant] This room and the next are where you'll live, and you must not wander from them. Don't forget that.


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[Assistant] They put on quite a lot of weight, they'll eat loads and loads of fish, um, and put on about half of their body weight, uh, and then they will molt all of their feathers at once.


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[Assistant] Barbara, I don't have the hoppity-scoppity-bop-bop or whatever your weird uncle had.


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[Assistant] Dear Santa Claus, I know you are a busy man.


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[Assistant] The Secret Garden Chapter 14 Who is Crying?


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[Assistant] Mary knew that Dickon had meant the picture of the nesting bird to be a message. It was a promise that he would keep her secret. She was the bird and the garden was her nest. Mary hoped that Dickon would come back the next day. She fell asleep that night looking forward to the morning.


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[Assistant] But she was awakened in the night by the sound of rain beating against her window and wind howling.


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[Assistant] Mary sat up in bed and felt miserable and angry.


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[Assistant] Though she tried to go back to sleep, the wind kept her awake.


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[Assistant] There was a candle by her bed, so she took that and stepped out of her room.


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[Assistant] She walked slowly along the corridors, letting the crying lead her on.


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[Assistant] Finally, she came to the door covered with tapestry, the one she had found that day she was lost. She pushed it open and stood in the corridor. The crying was quite nearby now. Mary could see light coming from beneath the door. Whoever was crying was in that room. Mary took a deep breath and opened the door. She found herself in a big room.


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[Assistant] A fire glowed faintly on the hearth, and a light burned by the side of a bed.


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[Assistant] A boy was lying in the bed. He had a pale face with large dark eyes.


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[Assistant] Are you a ghost? cried the boy in surprise.


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[Assistant] Mary said quietly, What garden?


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[Assistant] Mary said cautiously. She tried to change the subject.


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[Assistant] Colin told her he used to be taken to the seaside, but he didn't like it when people stared at him.


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[Assistant] A doctor from London recommended that he go out in the fresh air, but he didn't like that either.


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[Assistant] He was allowed to have whatever he asked for, yet he still wasn't happy.


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[Assistant] He said this as if he were so used to the idea that it didn't bother him anymore.


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[Assistant] He was more interested in asking Mary lots of questions about herself.


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[Assistant] As she talked about her life in India and the long voyage to England, he seemed to grow sleepy. But then he asked how old she was.


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[Assistant] Said Mary, forgetting to be careful for a moment.


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[Assistant] Excuse me? What? You two. You know you don't need to break in through the fence. You could just fly over with your wings. Oh yeah. Good point.


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[Assistant] Mark. Mark, have you heard about Pete's Monsters?


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[Assistant] Hmm, you are one dirty tortoise. But over on Gorilla Island, Jogan is- Hold on, where is he?


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[Assistant] Meanwhile, Pete continues his search. Found anything yet, Pete? No, I can't see them at the minute. Ah, funny that.


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[Assistant] And it seems that gas isn't the only convert to Pete's monster theory. Sam, you've actually seen some down here just along the water's edge.


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[Assistant] So, can you show me where you've seen them? This is unexpected. I thought Pete was making this up.


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[Assistant] Anyway, it seems that maybe the rumored Monsters of the Lagoon might well exist.


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[Assistant] No Pete, no you don't. But if there's no monster, then what happened to-


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[Assistant] It was a very big hamster. You better not be laughing Dave.


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[Assistant] In this next module, we're going to talk about writing the results section.


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[Assistant] Once you've got a nice, complete set of tables and figures that tell a good story, then it's time to write the results section.


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[Assistant] Your results section just falls right out of those tables and figures.


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[Assistant] The biggest mistake that people make with the results section is that because it falls right out of the tables and figures, there's a temptation to just repeat to readers line by line


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[Assistant] Statistic by statistic, what's already in the tables. It becomes a reading out of numbers that are already in the tables. But that's not the point of the results section.


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[Assistant] The results section is supposed to summarize at a higher level what's in the tables and figures.


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[Assistant] You want to point out simple relationships, describe big picture trends, and just refer the reader to the tables or figures that provide the supporting data.


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[Assistant] Over the course of treatment, Topiramate was significantly more effective than placebo at improving drinking outcomes on drinks per day, drinks per drinking day, percentage of heavy drinking days, percentage of days abstinent, and log plasma glutamyl transferase ratio.


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[Assistant] This study measured a whole bunch of outcomes and you can imagine that if you go to table three, it's this big table with all these different outcomes and lots and lots of numbers.


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[Assistant] But the authors here give a high level summary on all these different outcomes about drinking. The treatment, the drug beat the placebo. If you want more details, you can go to the table and see more details.


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[Assistant] The second example says the total suicide rates for Australian men and women did not change between 1991 and 2000 because marked decreases in older men and women were offset by increases in younger adults, especially younger men.


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[Assistant] This is referring you to table one and you can imagine that what's in table one is just a list of the suicide rates from 1991 to 2000 broken down by gender and age.


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[Assistant] But the author is summarizing the trends in the data set. There are no changes overall during this period, but if you look at certain subsets, there's a decrease in one group and an increase in another.


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[Assistant] They point out these trends without giving any specific numbers. The reader can go to the table to see the specific numbers.


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[Assistant] This is what a results section should look like. Notice it's very succinct. Each table is summarized in just a sentence.


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[Assistant] I'm gonna go back to the hypothetical example that I had on bad witches and good witches.


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[Assistant] The bad witches, remember, were older, less healthy, they exercised less, and so on.


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[Assistant] The characteristics of the bad witches and the good witches are shown in table one. And I want to just point out here that they are shown, that's in the passive voice.


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[Assistant] And then the writer launches into a reading out of the table. The mean age of the bad witches was 45 plus or minus 5 and the mean age of the good witches was 36 plus or minus 6.


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[Assistant] Then, uh, the author tells us that gender was similar between the groups with 85% female in the bad witches and 83% female in the good witches. And then the writer moves on to present the exact numbers for BMI, blood pressure and so on.


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[Assistant] You can see that the author is literally just reading the table for the reader, line by line, number by number.


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[Assistant] You have to give your reader more credit than this. The reader can go to the table and get all those details themselves.


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[Assistant] Your job in the results section is to give a higher level summary. What's the take home message of the table? What do you want your readers to pay attention to?


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[Assistant] My edited version starts, the witches were on average lean and predominantly female. Table 1 in parentheses.


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[Assistant] Notice that I didn't waste a sentence explicitly telling the reader that table one shows the descriptive characteristics of the groups.


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[Assistant] I just launched right into the take home messages from table one and cited the table in parentheses. You have to trust your reader.


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[Assistant] It's obvious to the reader that it's a table of descriptive characteristics, so don't waste a sentence stating the obvious. It just slows your reader down.


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[Assistant] Then I just go through the high level comparison of the two groups. Bad witches were significantly older, had higher blood pressure, exercised less, and were more likely to smoke than good witches.


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[Assistant] More bad witches were unemployed, but this difference did not reach statistical significance. Notice that I didn't present any numbers.


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[Assistant] The key here is to point out how the two groups differ at a high level. The reader can refer to the table for specific numbers.


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[Assistant] Okay, so notice the edited version here, it's much easier to read, it's less tedious, and it's more useful to the reader because it gives only the key points. Here are some tips for writing your results section.


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[Assistant] If the results are long or complex, consider breaking the results into subsections with informative headaches.


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[Assistant] This is not always needed, but it can provide a helpful roadmap for the reader, particularly if there are a lot of results to weed through.


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[Assistant] As I've already talked about, the information in the results section should complement rather than repeat what's in the tables and figures.


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[Assistant] For example, if you're presenting a figure like a bar graph that doesn't have precise numbers, you could give some of the precise numbers in the text.


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[Assistant] Or, if you presented the means of two groups in the table, you could in the text report the percent difference in those two groups. So a slightly different take on those numbers.


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[Assistant] Uh, for example, rather than repeating that good witches exercise 60 minutes a day and bad witches 30 minutes a day, you could say that good witches exercise twice as long as bad witches. That would complement the information in the table.


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[Assistant] You can repeat or highlight the most important numbers from the table, for example,


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[Assistant] If your study is a randomized, placebo controlled trial of a new drug to reduce blood pressure,


[User] Please transcribe this text

[Assistant] Then the main point of the study is to estimate the difference in blood pressure reduction between the drug and placebo groups. So that number probably belongs in the text. You want to highlight it.


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[Assistant] Don't forget that negative results are just as important as positive results. And if you have a control group, the most important comparison is the active treatment versus the control. So make sure you are highlighting that comparison in the results.


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[Assistant] Another tip, reserve the term significant to mean statistically significant just to avoid any confusion. Also try not to mix results with methods.


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[Assistant] One thing I commonly see is that authors spend a lot of time justifying and explaining their statistical approach within the results section. They feel like they need to give the rationale for which models they ended up using. They feel like they need to give that within the results section. But this is confusing for the reader.


[User] Please transcribe this text

[Assistant] The results section is about what you found, not what you did. So justify and explain the statistical approach within the method section. Then in the results section, just tell the reader what those statistical models reveal.


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[Assistant] Similarly, you don't want to mix up the results section with the discussion section. The results section is about what your data show.


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[Assistant] The discussion section is about what your data mean.


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[Assistant] So concentrate on the basic findings in the results section and leave the interpretation of those findings for the discussion.


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[Assistant] The rule is that if you're talking about completed actions, things that are already finished, such as the experiments and analysis, use the past tense.


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[Assistant] So you would say, we found that because you found it in the past. Or the average reaction time was because the experiment that measured reaction times has already been completed in the past.


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[Assistant] Or, women were more likely to, or men smoked more cigarettes then, because again, these experiments were completed in the past.


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[Assistant] But if you're talking about assertions that continue to be true, such as what the tables show or what the data suggest, these statements belong in the present tense because it's still true when your reader reads the paper that figure one shows the means of the groups. This continues to be true.


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[Assistant] So if you say, figure one shows, you should put that in the present tense because the figure is still showing that when the reader reads the paper.


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[Assistant] Or you would say the findings confirm. That's still true. Uh, the data suggest.


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[Assistant] Or we believe that this shows because those things are still true at the time the reader reads the paper. Those belong in the present tense. Just to give you a few examples on verb tense. Here's a result section.


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[Assistant] But then we get table one gives. So we start with the past tense, all the experiments that were completed. But then when we talk about the table, we put it in the present tense. Table one gives because state table one is still giving those characteristics presently.


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[Assistant] Because it's talking about things that were already measured in the completed study.


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[Assistant] Finally, I strongly recommend using the active voice in the results section. As we've talked about, it's more lively and easier to read than the passive voice.


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[Assistant] And people worry about using the active voice in results because they feel like they'll end up starting every sentence with we, we found, we observed.


[User] Please transcribe this text

[Assistant] But that's not the case in the results section. You can talk about the study participants, the experimental outputs, the data models, and so on. So there's lots of other options for the subject of the sentence besides we. So it's fairly easy to put the results section in the active voice.


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[Assistant] Just to give you an example, uh, notice that this study broke the results section into subsections with headings which I've mentioned before can be helpful.


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[Assistant] This subsection is comparing attitudes and beliefs in smokers with low versus high dependence as well as in hardcore smokers versus non-hardcore smokers.


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[Assistant] But notice the paragraph is in the active voice as well as the past tense. So we compared, beliefs were, smokers agreed, differentiation emerged.


[User] Please transcribe this text

[Assistant] It's nice and lively and easy to read, and the authors only used we once as the subject of the sentence. They were able to find other subjects. They talked about the smokers or the differentiation. So for the results section, use the active voice.


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[Assistant] I've only read one page since this morning. Boss, you're a gorilla. You can't read. Ah, shut up, Jeffrey. Look, I need to take this library book back by the end of the week. Otherwise I'll get a five cabbage fine.


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[Assistant] We built new communities in the ruins of the old. We adapted. We survived. Established a new normal. But there are also those who build nothing. Create nothing.


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[Assistant] Nah, here it is guys, I was looking for this button. Pretty important. The save button, you want to click on it pretty often when you're working inside Premiere. So I'm gonna lay this close with me. Anyways, in this lesson we're gonna take a look at some more advanced text techniques.


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[Assistant] What I have here in my timeline is just a very simple text which says Lord of the Rings. And what I'd like to explore here with the Essential Graphics panel is the Mask with Text option. What we can do is actually use this text as a mask for another layer. So, for instance, we want to see a video through the text.


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[Assistant] Well, that can be simply done by just taking a normal clip, like this one right here.


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[Assistant] And then make sure to select mask with text. And there we go. Now we can see the video clip that lays underneath through that text, which is pretty cool. We can also choose to invert that mask, which is basically gonna reveal the video and not the text, but you know, this is not so exciting. So in this case don't invert it and just have it like this.


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[Assistant] So what I'm gonna do here on the end position, just take the rectangle mask tool from my toolbox and just draw a rectangle over it. Just like that. And what we can say now is with that shape selected here, make sure to say mask with shape.


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[Assistant] And what it's gonna do now is only reveal the text when it sits within that shape. So before that animation you will see that the text will go behind that mask.


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[Assistant] Alrighty, on to the next technique and that is right here where I have some credits. Now, what I want to do is make sure that these credits roll up. And to do that simply select your graphics essential layer and without having any layer within selected we can just say here on the bottom roll.


[User] Please transcribe this text

[Assistant] That enabled the animation already sits in place and the text will roll up. They're pretty cool is that we also get this scroll bar, so that means that we can work further on this text for however long that we want it to be. So we can now just double click in here and add a line, for example actor, and the actor is...


[User] Please transcribe this text

[Assistant] Janik, there you go, now it's also animated within that rolling up text. We also have some more options here, for example pre-roll, that means how long should we wait before the animation starts, the same thing goes with post-roll. But also some easing options, for example we can say like in the first couple of seconds we want the text to ease in. So now you'll see that the text will start coming up


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[Assistant] Slowly and then accelerate faster. Alright, and then finally is a pinning option. So what I have right here is a new graphics essential layer and within there I have some simple text and also a background shape, just a simple rectangle. Now what I can do here with the text is pin it to, for example, that background shape.


[User] Please transcribe this text

[Assistant] I can choose to which side that I would like to pin this to, we can say for example only to the left side, but we can also click in the middle and say it has to be pinned to everything. So if I'm going to click here on the background shape now and move that to a different spot, you'll see that the text will always come with it.


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[Assistant] Even when I'm going to stretch out the background shape, you'll also see that it will also stretch out the text.


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[Assistant] But this also has the advantage that you can stretch it out as well and everything will stretch with it. Something that a group will not do. So this means that I can make a complex design, just pin it all together and just do my animations on one layer.


[User] Please transcribe this text

[Assistant] So that's it pretty much for the more advanced text techniques. I think all the rest speaks for itself like the size, the fill, the stroke, the shadow and all sorts of those other styling options we have in the Essential Graphics panel.


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[Assistant] And now let's save this project, there we go, and let's continue to the next lesson. Thank you so much for watching.


[User] Please transcribe this text

[Assistant] The Secret Garden Chapter 21 Visitors


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[Assistant] That afternoon, Dr. Craven came to see Colin. He always visited after a temper tantrum.


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[Assistant] Mrs. Medlock explained as she led the doctor upstairs.


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[Assistant] But as soon as they noticed the adults, the two children grew silent.


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[Assistant] I'm sorry to hear you're ill, my boy," said Dr. Craven.


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[Assistant] If Colin got well, then the doctor would lose all chance of inheriting Mistletwaite Manor. But Dr. Craven was not a bad man. He wouldn't let Colin run into danger.


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[Assistant] This boy who's pushing you must be strong, said Dr. Craven. And I must know something about him. Who is he? It's Dickon, said Mary.


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[Assistant] She was sure that everyone knew Dickon and she was right. Oh, you'll be safe with him, said Dr. Craven. He's as strong as a moor pony.


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[Assistant] That afternoon, Dr. Craven did not give any medicine or leave instructions for the nurse.


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[Assistant] This certainly is a new state of things, he said to Mrs. Methlock as they went downstairs.


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[Assistant] That night, Colin slept peacefully for the first time.


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[Assistant] He lay still and breathed in the fresh air while Mary described everything she had seen in the garden that morning.


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[Assistant] She also told him how Dickon had rescued a newborn lamb whose mother had died.


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[Assistant] After a while the nurse brought breakfast for Colin and Mary.


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[Assistant] When do you think Dickon will come? Ask Colin.


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[Assistant] replied Mary. And in a few minutes they heard a crow cawing.


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[Assistant] Dickon entered the room, wearing his nicest smile.


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[Assistant] The newborn lamb was in his arms, and the fox trotted by his side.


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[Assistant] But Colin's behavior did not make Dickon feel shy or awkward. Wild creatures always stared at him until they knew him.


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[Assistant] Dickon knelt by the sofa and took a bottle out of his pocket.


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[Assistant] Colin watched in amazement while Dickon fed the lamb and told them how he'd discovered it on the moor. I heard a weak cry, but couldn't find it. At last I spotted a bit of white near a rock.


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[Assistant] Nut and Shell made trips to the big trees outside and ran up and down the branches.


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[Assistant] Captain curled up near Dickon after the lamb fell asleep.


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[Assistant] The children looked at some of Colin's books, which were full of pictures of flowers.


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[Assistant] We call that one Columbine, said Dickon, pointing to a flower that had a long Latin name in the book. There are big clumps of Columbine in the garden.


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[Assistant] Colin said firmly, Mary nodded solemnly.


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[Assistant] You know, sometimes I dream about being on my own. I'd love to have this place all to myself.


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[Assistant] Well now I'm a bit lonely. I've got no one to chase. I'm almost starting to miss her. And it looks like that gorilla's on his way. Oh, he's almost packed.


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[Assistant] When you're working with higher resolution source files, such as 5K, we can bring them into an Ultra HD sequence and scale them down. But in Premiere we've got two options for that. We've got scale to frame size and fit to frame size. But what is the difference?


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[Assistant] So we can either like scale it down, like so, so that it fits to the frame size. Or we can also right click on that clip and choose scale to or set to frame size.


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[Assistant] When choosing set to frame size Premiere will actually do that action that I've just done, just set it to 80% scale.


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[Assistant] But when choosing the other option, scale to frame size, you'll see that it will do the exact same thing here in the program monitor, but it will retain the scale at 100%.


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[Assistant] The difference between these two is that with set to frame size it will actually just


[User] Please transcribe this text

[Assistant] Decrease the scale of that clip while retaining its full resolution, 5K in this case.


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[Assistant] When choosing scale to frame size, it will resample that and your playback in Premiere will actually go smoother.


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[Assistant] Now let's talk about workflow. Because we are working here with 5K resolution source clips in an Ultra HD.


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[Assistant] Sequence. And it's gonna take a lot of time if we have to right click every clip and scale or set it to the frame size. Well, for starters we can go to the menu here, edit, go to keyboard shortcuts. Let's just search for frame size. Here are those two options. So we can already set a short key for that if we like so.


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[Assistant] However, there are some better ways to do it. First of all, we can select all the clips in here, go over to the menu here, clip,


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[Assistant] Then go to video options and from there select scale to frame size. On the source clips we only have the option to scale it to the frame size and not set it to the frame size.


[User] Please transcribe this text

[Assistant] So when we do that, all these clips are now scaled to the frame size, so when we're going to drag any of these files here to the timeline, select that clip, head over to the motion property, you'll notice that the scale is set to 100,


[User] Please transcribe this text

[Assistant] However, the clip is scaled or better said resampled to the correct frame size. Okay, but what if I want to actually scale down each clip to 80% to retain that quality? Well, no worries, I can help you out. Let me just delete that clip right here, head over to the menu, select edit,


[User] Please transcribe this text

[Assistant] Preferences and then choose media. From here you can see that we have an option called default media scaling. And you want to set that to set to frame size. Yea, now this could be like very confusing. Scale to frame size should actually be like actually scaling it to 80%.


[User] Please transcribe this text

[Assistant] Instead of the set to frame size. It takes some time, but remember, in the Adobe Universe, nothing makes sense. Alright, let's just press OK.


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[Assistant] You'll notice that it has automatically now been scaled to 80%. And from there we can upscale that if we like so to 90 or whatever we want. There we go, and that's the difference between set two


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[Assistant] You mean you want me to go outside and find out what his purpose was in pushing him down and ask him not to do it again?


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[Assistant] I went out there and faced that big kid who pushed you down. At least I know I tried. He may have been bigger than I, but I faced up to him.


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[Assistant] I can't believe I'm going over to the mall to meet a girl I don't remember. But-


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[Assistant] Yes ma'am, I'd like to buy a box of valentine chocolates for a girl who doesn't know I exist. No ma'am, nothing too expensive. I'll never have the nerve to give it to her anyway.


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[Assistant] Isn't this a beautiful valentine? It says, I love you. I love you.


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[Assistant] No, no, I can't open it now. It's a gift for someone. I think I'll give it to the little red-haired girl.


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[Assistant] It's a Valentine's Day card to go with a box of chocolates. Uh-uh.


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[Assistant] I'll go outside and ring the doorbell and you pretend you're the little red-haired girl. Okay?


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[Assistant] I'd really appreciate it if you could find somewhere else to sit, Snoopy.


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[Assistant] In this next module, we're going to do an active practice exercise about what you just learned about introduction sections.


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[Assistant] This is the introduction section from an article in the BMJ Christmas issue, which is a humor issue. But it makes a good example.


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[Assistant] I want you to read the introduction and identify which sentences give the what's known or background, which sentences give the what's unknown, and which sentences refer to this specific study.


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[Assistant] So go through and figure that out and when you are done, restart the video and I'll walk


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[Assistant] In the very first two paragraphs and just the beginning of the third paragraph, we get a lot of background information. We get the what's known.


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[Assistant] So we're told a lot about popular medical talk shows, uh, the background there. Hopefully you identified all of those as what's known.


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[Assistant] There are two places, two sentences where we get the what's unknown.


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[Assistant] The third paragraph, however, no research has systematically examined the content of the medical information provided on these talk shows. Nobody has done a study like this before, systematically evaluating those talk shows.


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[Assistant] Alright, finally the last sentence gives us the aims of this study. They say our objective was to...


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[Assistant] Review the most popular medical talk shows on television to 1. Determine the type of recommendations and claims given and the details provided and 2. Search for and evaluate the evidence behind these recommendations.


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[Assistant] It's clear that this study is filling in a gap because nobody has ever looked at this research question before. So hopefully that one was fairly straightforward. Now we're going to do a second exercise.


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[Assistant] This was a study on self citation. The authors wanted to know if men cite their own papers self cite more than women.


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[Assistant] And I want you to do the same thing as we did in the last exercise. I want you to identify the sentences that give the known, the unknown, and then those that are pertinent to this study.


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[Assistant] So now pause the video and complete the exercise and then restart the video.


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[Assistant] You got that uhm, most of the, uh, the first three paragraphs are giving a lot of background.


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[Assistant] We learn that self citation is an important question. They tell us why this matters. We need some background on that to explain that citation counts are an important part of promotion in an academic career.


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[Assistant] And so if men are self promoting more effectively than women, perhaps that contributes to the gender disparity we see in faculty hiring and promotion.


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[Assistant] Then in that third paragraph, we get the previous literature. So we're told that there was a 2013 paper that looked just at citations in general, not at self-citations, and that one did find a gender difference. Men's papers in general are cited more than women's.


[User] Please transcribe this text

[Assistant] And then there was one previous paper from 2013 that looked specifically at self citation and they did find a gender difference. They found that men self cited 1.5 times more than women. But,


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[Assistant] The, here let's move to the what's unknown. There's just a one sentence, uh, statement of what's unknown here. The problem is, there have been few studies on this, right? We only have one that specifically looked at self citation and gender.


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[Assistant] And that one study that looked at self citation and gender had looked at only a few disciplines and a relatively small number of papers. So this hasn't been looked at broadly.


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[Assistant] And then finally, hopefully you were able to identify the last two sentences as those pertinent to what this specific study is going to do.


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[Assistant] Here we examine gender differences in self-citations across 24 broad academic fields with hundreds of sub-fields and several million scholarly papers with over a million self-citations. So they're going to fill in the gap of the


[User] Please transcribe this text

[Assistant] Previous literature by doing a much larger, much broader study.


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[Assistant] And they're also going to look at one other thing, which is how the gender gap has changed over time.


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[Assistant] I'm going to follow the pig. I want to make sure he really searches the mountain.


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[Assistant] You know, that is simply not true. I love vegetarians. They're wonderful, delightful.


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[Assistant] Oh no. You know what this means, don't you? The bananas?


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[Assistant] Uh, no. All the visitors love a cute little baby. We won't stand a chance against them cubs.


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[Assistant] When it comes to the cutometer, those little furballs are off the scale. Everybody who is anybody would want to take a look. We won't see any visitors for weeks. What? Rubbish!


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[Assistant] Cute beats rubbish catching skills any day of the week. Nonsense! Check out my incredible parkour skills!


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[Assistant] Where is everybody? Oh well, what a surprise. They've all gone to try and get a look at those super cute lion cubs. What? Come on boys, we need to make su-


[User] Please transcribe this text

[Assistant] Then we need to get something small, fluffy and adorable. Hmm, what about this? Uh? No, not really. Well, what about the puppies then? Yeah, that would do it, but we don't have any puppies.


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[Assistant] Dave, how many times? That's a piece of poo.


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[Assistant] It's his new pet goldfish. He keeps losing it. Shut up, Jeffrey. I got a pet.


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[Assistant] No! Will you give her a rest, boss? Look!


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[Assistant] I think you have to accept that, as a massive western lowland gorilla,


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[Assistant] You're probably never gonna be considered that cute. But Fate, look! The people, they're coming back!


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[Assistant] See, I am super cutie. They are coming back, but that's not because you're cute, boss. It's because they like seeing a big airy eat.


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[Assistant] Journey to the West. Chapter 35. A Visit to the King.


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[Assistant] Said the monster. He stamped his foot. Then he sighed.


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[Assistant] The monster thought for a minute. Finally he had a plan. He went to the princess's room.


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[Assistant] Before the princess could say another word, the monster left the room.


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[Assistant] He said to himself, he recited a quick spell. Light sparkled. Now the monster looked like a handsome young man.


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[Assistant] He told the king that he and Wu Jing couldn't save Princess Hundred Flowers. The pig hung his head.


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[Assistant] Said the messenger. The king was confused.


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[Assistant] What? Cried the Tang Monk. The King frowned.


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[Assistant] Said the young man. He pointed at the monk again and recited a spell. Light sparkled.


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[Assistant] Now a tiger sat in the Tang monk's spot.


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[Assistant] That night, Bajay was sitting alone outside when he heard a voice. Sss, said the voice.


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[Assistant] Cried Bajay. Shh, said the horse.


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[Assistant] Yes, Starlight is student of the year, isn't she? She has so much potential. So, what are we going to do with her? And by we, I definitely mean you, being her mentor and all that. Her destiny falls squarely on your haunches.


[User] Please transcribe this text

[Assistant] Oh good. I'm sure she can't wait to hear all about it.


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[Assistant] Yes, I'd say we were both fairly interested.


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[Assistant] I may have let it slip that you'd be unveiling your big plan for Starlight tonight. Silly me. But we're all very excited to hear what you've cooked up.


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[Assistant] You weren't coming up with a plan just now, were you? Oh dear. This could be pretty embarrassing for you.


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[Assistant] Anytime. I really do love being helpful.


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[Assistant] Darn it. I was hoping you'd send her to my realm. We could've been roomies. Way to not pick up what I was putting down.


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[Assistant] Or we could go cause a little mischief. I know a trick that'll turn Celestia's castle into cheese. Do you think it's a gouda idea? That's just the first of many cheese jokes if we go down this path.


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[Assistant] Templates. You can use someone else's work or you can also create your own templates so that someone else can use your work or just make it yourself easy and use your own custom design for multiple videos, like maybe you're working on a show or something.


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[Assistant] Anyways, let's have a look at how we can do that. What I've got right here is just a simple


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[Assistant] Graphic and I've added this animation to it where we can see this text with a background shape pop open. In the previous lesson we have seen that we can pin different layers together and what I've done right now is actually the opposite of what we did last lesson and that is linking the background shape


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[Assistant] To the text, so truly pin to option. So this means that whenever I'm going to change the text, the size of the background shape will also change. Let me just show that to you. It currently says Lord of the Rings, but let's change the text to something else. So just say text. And as you can see here, the background


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[Assistant] So that is something perfect for templates, as you always want to make sure that whenever you're going to change the text from within, that your design also


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[Assistant] Alright, let me just reset that back to Lord of the Rings because that is pretty cool. Now what we can do is actually save this as a template so that we can use that in other projects as well. And the templates can be found back here under the Browse tab on top. And by default you will already see a bunch of templates in here.


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[Assistant] Whenever you're going to install Premiere Pro, these come with the installation by default.


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[Assistant] They are not the greatest templates, but hey, they're there. If you don't like them you can also just right click any of these and just say...


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[Assistant] Yes, I'm sure. Now this is a local templates folder, some kind of a folder that is stored on your computer, so that means whenever I'm going to import a template in here, that doesn't mean that it will also appear.


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[Assistant] On another computer. But we also have an Adobe Stock templates location. Now Adobe Stock is essentially an additional subscription from Adobe where you can purchase stock clips but also templates. And the cool thing is that you can browse through their stock from within Adobe Premiere.


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[Assistant] You can search for something specific or you can also select to only show the free templates or...


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[Assistant] Now, I personally don't have an Adobe Stock subscription and that is because there are a dozen of others, uh, stock libraries out there. For instance, we use Storyblocks for such things. But we can make use of the free template, so let's just have a look at what that is. Let's just take the first one here, for example, let's just drag that into.


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[Assistant] Our composition like that and Premiere will load it in. We've got the template right here and it's pretty heavy it seems and that's because we see a bunch of effects on it, so my PC has some trouble playing this back.


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[Assistant] Anyways, when we select that layer, we can then go to the edit tab here on top and from there we've got a bunch of controls to change the template. Of course, we've got some text controls from which we can change the text in there.


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[Assistant] Alright, let me just go back to my template right here and let's save this as well because what we can actually do is import this


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[Assistant] And then we can choose where we would like to save this, for example into the local templates folder, and that will automatically import it into the essential graphics right here.


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[Assistant] But we can also choose to store this onto the local drive. Let's do that. I'm going to hit browse to make sure that it's safe to my desktop. Say select folder and press okay.


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[Assistant] The great thing about exporting it onto your local drive is that now you can also share that template with your friends or colleagues so that they can use the same design. And let's have a look now. Minimize Premiere. There it is, the yellow pop-up text.


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[Assistant] That's right. Alright, so how can we start using that now? Let's go back into Premiere Pro and here on the bottom of the Essential Graphics, when you're inside the Browse tab, you'll find a button that says Install Motion Graphics Template. So just click on that and let's locate...


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[Assistant] The yellow pop-up text template that I've just created onto my desktop and hit open. So whenever you're going to send that file to a friend or something, they can do the exact same steps to also import it into their templates folder. And let me just look, it should be somewhere in here. It's usually on the bottom, there we go, here it is, Lord of the Rings.


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[Assistant] So I can now just go ahead and delete this here. There we go. Because it's in my templates folder from which I can always drag it out from into my edit and it will just load it in. Look how cool that is. And from there I can now go ahead and change the text... ...painting.


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[Assistant] And the cool thing about the templates folder is that whenever you're going to start a new project inside Premiere, you will every time see your templates in here.


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[Assistant] So you don't need to install them every time again. It's basically like a collection of video assets that you can use throughout your entire video editing career. Look at that. That was it for the...


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[Assistant] Templates, how you can create your own, how to use someone else's templates. That's pretty much it. Thank you so much for watching and I hope that you've learned something new.


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[Assistant] See? Leave it to you three to come up with more ideas than I've had in a year. Now that's talent.


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[Assistant] I think talking to Cheese Sandwich is a great idea. But the only pony who can really find your life's purpose is you.


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[Assistant] Maybe we need to start even smaller. You can't run before you can walk.


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[Assistant] And Cheese Sandwich just left his own factory?


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[Assistant] I'm glad you came. I ache all over because I'm so tired.


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[Assistant] Do you think Jump really understands everything Dickon says?


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[Assistant] I never had anything to be friends with, and I can't stand people. Can you stand me?


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[Assistant] Yes, I can. It's funny, but I even like you.


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[Assistant] Mary, I wish I hadn't said what I did about sending Dick in a way. I wouldn't mind him looking at me. I want to see him.


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[Assistant] Ugh, well it ain't gonna be easy. But I think we can whip up these new cookies Twilight wants before sunrise. If anypony can handle some last minute bacon, Braeburn. It's y'all.


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[Assistant] Juergen. Juergen, this episode is not about you. It's about the jobs the humans do. You do know what the humans do, don't you?


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[Assistant] Right, well, okay, that didn't go exactly to plan. Right, Jurgen, you'll have to do. Tell us about the job the keepers do.


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[Assistant] Well, come on then. You've had some suggestions. Now tell us in your own words what else the keepers do. No. Fine. Then I'll ask the actual keepers. They'll give me a sensible answer.


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[Assistant] What? I mean that's not really helpful, Jim. Yeah.


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[Assistant] What do the keepers do? You know, on a normal day.


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[Assistant] Yeah, well that's rich coming from you. So far, you, the supposed expert, have told us zookeepers have gangly arms, say hello a lot, and can count.


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[Assistant] I guess they're more like, um, poo keepers than zoo keepers, eh? Poo keeper. Ha ha. Do you get it?


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[Assistant] Right, well, moving on from keepers then, let's talk about the vets.


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[Assistant] Ah, hold on. Jeffrey, have you been teaching him stuff? Obviously. Great. Well, what else did he teach you?


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[Assistant] Right, so uhm, in reality you know absolutely nothing about the Vets, Jürgen.


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[Assistant] Well, you've taught me today that gorillas called Jergen are really annoying. No.


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[Assistant] So hi, my name is Crystal Botham and I'm the Director of the Grant Writing Academy at Stanford. And I'm going to discuss tips and strategies for writing your specific aims.


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[Assistant] Well, it's perfect for listening feedback because it's the executive summary of your entire proposal.


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[Assistant] As you're developing your proposal, your colleagues and mentors will be happy to provide feedback on your specific aims document because it's not a big time investment like reading the entire proposal.


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[Assistant] So the specific aims document is critical to developing a first class proposal because it's perfect for eliciting feedback.


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[Assistant] You want a lot of feedback so you can ensure the conceptual framework of your proposal is good.


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[Assistant] As I mentioned, the specific aim should provide that conceptual framework of your proposal, so it's perfect roadmap as you write the rest of your proposal.


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[Assistant] Equally important, your specific aims document must empower the reviewers with all the necessary information to fund your project after reading only the specific aims document.


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[Assistant] Let's use NIH, the National Institute of Health, instructions as an example.


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[Assistant] There, a specific aims document is one page, and here are the specific directions.


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[Assistant] State concisely the goals of the proposed research and summarize expected outcomes, including the impact the results of the proposed research will exert on the research fields involved.


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[Assistant] List succinctly the specific objectives of the research proposed. And for example, to test a stated hypothesis, create a novel design, solve a specific problem, challenge an existing paradigm or clinical practice, address a critical barrier to progress in the field, or develop new technology.


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[Assistant] So, goals, expected outcomes, impact, specific objectives. So there are really some key questions and ideas that should be conveyed on the specific aims document. I've come up with four key questions that you need to answer in writing a compelling specific aims page.


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[Assistant] This is really getting at the idea that there may be a particular gap in the knowledge base or a need that's holding your field back. So if you were able to


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[Assistant] Fill in that gap or address the need then you can move your field significantly forward and more than just incremental steps. What is the overall goal?


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[Assistant] This must fill in the gap or need delineated by addressing the first question. What specifically will be done?


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[Assistant] What are your specific research questions or aims? What is your hypothesis?


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[Assistant] What are the expected outcomes and impact? What is the return and investment of funding this research?


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[Assistant] Just like a machine or these gears uhm, if one of the answers to these questions isn't perfectly aligned,


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[Assistant] Then you won't be able to have a really compelling specific aims page. So when answering these questions, you really need to take a big picture look to make sure each of your answers to these questions are perfectly aligned with the other answers.


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[Assistant] And your responses to these four questions could become four really important parts to your specific aims page and could be used to organize your specific aims document.


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[Assistant] And so we'll go into more detail in the next couple of slides about how you can use these four questions to organize your specific aims page into four sections or paragraphs.


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[Assistant] So first, the introductory section of your specific aims co- should answer, uhm, is the research question important?


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[Assistant] So the first sentence of course needs to grab the attention of your reviewers. You want to hook them immediately and highlight that your proposal will support the mission of the funding agency.


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[Assistant] Then after you have the attention of your reviewers, bring them all up to speed by summarizing the relevant current knowledge.


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[Assistant] This is important because your reviewers may not be familiar with all the complexities of your specific field.


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[Assistant] In your field or the need that your proposal will address.


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[Assistant] This statement is really important and will drive your proposal.


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[Assistant] The knowledge gap or need statement should identify this critical bottleneck that's slowing or stopping progress in your field.


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[Assistant] So at the conclusion of this first section or paragraph, you should have the attention of your reviewers, they should understand the proposed research area is relevant, and the knowledge gap or unmet need is important.


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[Assistant] The second paragraph needs to connect to that first section, which answers a really big question, is the research important? And funnel down to the specifics that are proposed.


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[Assistant] So it's going from this idea of this big knowledge gap to actually the specifics that you're proposing.


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[Assistant] So one approach to do this in this section is to start still pretty big with your big picture goal. This could be a long-term goal for your research program or a goal that relates directly to the funding agency's mission.


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[Assistant] Next, narrow the focus and describe the objective of the proposed research. Remember that your objective must directly address the knowledge gap or the need statement described in the first section.


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[Assistant] Also, your objective must be obtainable regardless of how the hypothesis tests.


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[Assistant] Most funding agencies fund hypothesis driven research. So it's best to explicitly state your hypothesis. This overall or central hypothesis must be objectively testable and should be your prediction or best bet.


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[Assistant] It's nice to bold or italicize your hypothesis because it's the climax of this section.


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[Assistant] Lastly, describe your preliminary data or other data that helped you formulate your hypothesis. Now, what specifically will be done?


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[Assistant] It's nice to have broad aims that are achievable regardless of how your hypothesis tests. Uhm, then briefly describe the methods that you'll use to test your hypotheses.


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[Assistant] This is really getting at the return of investment of funding your project. This needs to relate to the goals of the funding agency's mission. That's really important.


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[Assistant] So for example, if uhm, you're applying to a fellowship or career development award, and there, the goal of the funding agency is to advance your career towards an independent scientist, then that may be appropriate to include that information in the expected payoff on your specific aims page.


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[Assistant] So here, you can see how these four questions can be formulated into four key sections or paragraphs of your specific aims page. So let's look at an example.


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[Assistant] Here's an example from a faculty member at Stanford. And notice that the specific aims is divided into several different sections. This faculty member is answering


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[Assistant] Is the question important in this first paragraph? You can see she's ending that first paragraph with a clear statement of the knowledge gap.


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[Assistant] Thus, there's a critical need to standardize how donor hearts are evaluated and accepted for transplantation. There's a clear, uhm, statement of the knowledge gap or need that is going to drive this proposal.


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[Assistant] Next, she's funneling down by stating her long-term goal, stating her central hypothesis, which she's italicized and underlying.


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[Assistant] To get to the specifics of her proposal. She's using a broad aim.


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[Assistant] And then several working hypotheses to describe, uh, what exactly she'll be, the different approaches that she will take.


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[Assistant] It's actually really nice to end this specific aims section with this statement because it leaves the positive impact


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[Assistant] Uhm, as the reviewer is ending the specific aims page.


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[Assistant] So you can see how she's answered these four questions in a very logical approach.


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[Assistant] And it provided a nice organization, uh, structure to her specific aims page.


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[Assistant] Now answering the questions in this specific order isn't the only approach to writing effective specific aims page. So let's look at another example.


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[Assistant] Here they're using the first part of this first paragraph to answer the question, is it the question important?


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[Assistant] They have the knowledge gap statement, uhm, in the middle of that pair, that section. Then they have the overall goal.


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[Assistant] Uhm, delineated, uhm, in the second part of that first paragraph. And they have the hypothesis broken out a little bit.


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[Assistant] It's nice to have the hypothesis clearly identified.


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[Assistant] Uhm, uh, which provides that focus for your proposal. And then the specifics are here. They're using nice broad, uhm, uhm, bolded aims. They have, uhm, the specific approaches that they'll be taking, uhm, as well highlighted. And then the expected payoff is here.


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[Assistant] So here's another example of a funded application.


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[Assistant] That is answering these four critical questions, but it is taking a different approach in the order.


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[Assistant] So in summary, the specific AIMS document must concisely answer the following questions. So is the research question important?


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[Assistant] Compelling projects and proposals often tackle particular gaps in the knowledge base or need that when addressed significantly advance the field. What is the overall goal?


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[Assistant] So the overall goal defines the purpose of the proposal and must be obtainable regardless of how the hypothesis tests.


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[Assistant] What specifically will be done? Attract the reviewers' interest using attention-getting headlines. Describe your working hypothesis and your approach to objectively test the hypothesis.


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[Assistant] Then what are the expected outcomes and impact? Describe what the reviewers can expect after the proposal is completed in terms of advancement, uhm, to the field.


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[Assistant] So to write effective specific aims, feedback is critical. You need a wide audience providing feedback too, because your reviewers are likely to come from a wide background as well. So get feedback throughout the process.


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[Assistant] Uhm, and in the beginning, in the middle, in the end, really writing your specific aim should be an iterative process.


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[Assistant] Here's a couple of outstanding resources to learn more about how to write effective, specific aims.


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[Assistant] I expect you to do things by the book.


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[Assistant] Classes won't start at all. The EEA has spoken, and none shall pass!


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[Assistant] This is for the greater good.


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[Assistant] The school was disorganized, the teachers unqualified, and those dangerous and unpredictable students put ponies' lives in danger.


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[Assistant] In the last module for this week, I want to make you aware of the problem of predatory journals.


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[Assistant] If you're publishing in the scientific literature, you need to be aware of the problem of predatory open access journals.


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[Assistant] Creditory open access journals are bogus journals that are exploiting the open access model to make money. Open access journals are a great idea.


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[Assistant] The idea is that authors pay publishing fees so that journals can make the full text of articles freely available to everyone.


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[Assistant] The PLOS journals, Public Library of Science journals, are shining examples of this open access publishing model.


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[Assistant] When it's done with integrity, open access publishing is fantastic.


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[Assistant] But, because money is exchanging hands, this has opened the floodgates for the creation of bogus journals which exist solely to collect money from authors, not to publish high quality research.


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[Assistant] Jeffrey Beale, a librarian at the University of Colorado Denver, has been a leader in calling out this practice and keeping lists of bad publishers and bad journals.


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[Assistant] Another leader in exposing this whole problem is the journalist John Bohannon.


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[Assistant] He ran a sort of sting operation that he wrote about in Science in 2013.


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[Assistant] What he did was he submitted an obviously flawed bogus cancer paper. He describes it as he did a scientific version of Mad Libs so that he could come up with 255 slightly different versions of the same paper.


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[Assistant] Where he took molecule X from lichen species Y inhibits the growth of cancer cell Z.


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[Assistant] He created a whole bunch of different papers just substituting different molecules and species and cancer cells.


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[Assistant] And the papers had obvious flaws. Any scientist, no matter how schooled, should have been able to look at figure one and know that this paper was problematic.


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[Assistant] He submitted this to open access journals, many of which he suspected to be predatory journals.


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[Assistant] I'll note that PLOS One was one of the journals that correctly rejected the paper.


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[Assistant] In fact, 82% of the publishers on Jeffrey Beal's list, uh, actually accepted that paper. So, John Bohannon was able to show that there is this huge suite out there of predatory journals, and they are willing to accept anything for money.


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[Assistant] All evidence shows us that these predatory journals are greatly on the rise.


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[Assistant] There was a 2015 paper in BMC Medicine that tracked predatory journals from 2010 to 2014. You can see it's growing exponentially.


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[Assistant] Pay attention to that red line on top. That's the total number of predatory journals.


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[Assistant] They estimated that in 2014, there were about 8,000 active predatory journals.


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[Assistant] That was up to 420,000 articles published in these predatory journals in 2014.


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[Assistant] These are probably all or most of poor or garbage quality.


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[Assistant] Authors paid an average article processing charge of 178 US dollars per article. So it's a money making scam.


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[Assistant] That same paper, they also show that this affects all scientific disciplines. You can see in this graph here that no scientific discipline was safe from this practice.


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[Assistant] I like this checklist that Declan Butler published in 2013 in Nature.


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[Assistant] Provides full verifiable contact information.


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[Assistant] You want the full address of the publisher to be available.


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[Assistant] You also want to check that the journal's editorial board lists actual experts with full affiliations, not just made up people.


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[Assistant] You might even want to contact them and ask them about their experience with the publisher.


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[Assistant] Because there are known instances when people's names have been borrowed and just stuck on these websites without the person's permission.


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[Assistant] You want to check that the journal prominently displays its policy for author fees. Open access journals do charge fees, but you want to make sure that these policies are clearly described on their website. If they're not, that's a suspicious sign.


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[Assistant] Be wary of spam email invitations. We talked in an earlier module about academic spam.


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[Assistant] You will get a lot of these emails that ask you to submit to journals or to become an editorial board member or to speak at a conference.


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[Assistant] You can tell that these are spam if you look carefully. They have lots of grammatical errors and lots of exclamation points. Be careful of those.


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[Assistant] Always go to the journal's website and make sure that the articles that they are publishing are high quality articles, not just junk.


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[Assistant] Check that a journal's peer review process is clearly described. Make sure that they are actually doing peer review.


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[Assistant] There is a trend now where these predatory journals are making up bogus metrics. They have names like the Universal Impact Factor, UIF, or the Global Impact Factor, GIF, or the Journal Impact Factor, JIF.


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[Assistant] These are all popular, but bogus metrics made up by predatory journals. They sound a lot like the real thing. So be careful not to get sucked into that.


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[Assistant] There are lists people publish of supposedly legitimate open access journals. The lists are not perfect, but at least the journals listed there have gone through some vetting. So you might want to check before submitting. You can check with the directory of open access journals.


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[Assistant] Uh, or the Open Access Scholarly Publishers Association. You can check there and make sure that the journal you're submitting to is listed there.


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[Assistant] Finally, use common sense. If something looks fishy, if it looks like spam, it probably is. So just be careful and be aware of these predatory journals.


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[Assistant] Finally changing topics here, I want to keep talking about writing throughout this course, even though we're now on to talking about publishing.


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[Assistant] So just to end this week, I want to present an example of good writing.


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[Assistant] This is from an article by Carl Dezeroth, in Scientific American. He wrote,


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[Assistant] The lesson of optogenetics is that the old, the fragile, and the rare even cells from pond scum or from harsh Saharan salt lakes. Notice the use of dashes there.


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[Assistant] Can be crucial to comprehension of ourselves and our modern world.


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[Assistant] The story behind this technology underscores the value of protecting rare environmental niches and the importance of supporting true basic science.


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[Assistant] We should never forget that we do not know where the long march of science is taking us or what will be needed to illuminate our path.


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[Assistant] And illuminate is a bit of a play on words here because of course optogenetics involves illumination.


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[Assistant] Anyway, I just wanted to end here with an example of good writing.


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[Assistant] That's made her well and saved Colin. Standing on his feet.


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[Assistant] The cook is afraid Mr. Craven will blame her if they starve themselves to death.


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[Assistant] And so is that girl. Mary is even beginning to look pretty.


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[Assistant] She used to be so unhappy, but now she and Colin laugh together all the time. Maybe they're growing fat on laughter.


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[Assistant] Why can't you be granny? You're her size and this is all your fault in the first place.


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[Assistant] I couldn't free you right away. I had to get rid of the demon first.


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[Assistant] But some corporate raiders have been unkind to employees.


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[Assistant] Wukong can't charge into the palace and attack the Daoist.


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[Assistant] People will think the monkey is evil, attacking a king for no reason.


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[Assistant] I don't know where it is now though. It was just a dream.


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[Assistant] adversary, adversary, someone who offers opposition