1 00:00:00,000 --> 00:00:05,860 Welcome to the Clinician Researcher podcast, where academic clinicians learn the skills 2 00:00:05,860 --> 00:00:11,260 to build their own research program, whether or not they have a mentor. 3 00:00:11,260 --> 00:00:17,340 As clinicians, we spend a decade or more as trainees learning to take care of patients. 4 00:00:17,340 --> 00:00:22,380 When we finally start our careers, we want to build research programs, but then we find 5 00:00:22,380 --> 00:00:27,780 that our years of clinical training did not adequately prepare us to lead our research 6 00:00:27,780 --> 00:00:29,200 program. 7 00:00:29,200 --> 00:00:35,480 Through no fault of our own, we struggle to find mentors, and when we can't, we quit. 8 00:00:35,480 --> 00:00:40,580 However, clinicians hold the keys to the greatest research breakthroughs. 9 00:00:40,580 --> 00:00:46,200 For this reason, the Clinician Researcher podcast exists to give academic clinicians 10 00:00:46,200 --> 00:00:51,800 the tools to build their own research program, whether or not they have a mentor. 11 00:00:51,800 --> 00:01:01,080 Now introducing your host, Toyosi Onwuemene. 12 00:01:01,080 --> 00:01:02,180 All right, everybody. 13 00:01:02,180 --> 00:01:04,520 Welcome to the Clinician Researcher podcast. 14 00:01:04,520 --> 00:01:06,240 I'm Toyosi Onwuemene, your host. 15 00:01:06,240 --> 00:01:07,720 I'm so excited to be here today. 16 00:01:07,720 --> 00:01:10,600 I have a really special guest, Beth Blockwood. 17 00:01:10,600 --> 00:01:12,280 Beth, welcome to the show. 18 00:01:12,280 --> 00:01:13,280 Yeah. 19 00:01:13,280 --> 00:01:15,080 Thank you so much for having me. 20 00:01:15,080 --> 00:01:20,240 Beth, so I want to call you a librarian, but I'm not sure that's the right technical term. 21 00:01:20,240 --> 00:01:24,960 Could you introduce yourself to our audience, what you do, and what makes you so special? 22 00:01:24,960 --> 00:01:26,360 Yeah, absolutely. 23 00:01:26,360 --> 00:01:32,640 So my name is Beth Blockwood, and I am technically the research and education librarian here 24 00:01:32,640 --> 00:01:35,720 at Duke Medical Center Library and Archives. 25 00:01:35,720 --> 00:01:44,200 So librarian is in my job title, but I specialize in kind of a new area of librarianship that 26 00:01:44,200 --> 00:01:49,400 Duke and a few other institutions have kind of invested a lot of time and effort into, 27 00:01:49,400 --> 00:01:50,840 but there's not very many of us yet. 28 00:01:50,840 --> 00:01:56,360 And I am specifically a librarian who works on research impact and bibliometrics. 29 00:01:56,360 --> 00:02:02,600 So I specialize in what some might call the science of science, measuring what that kind 30 00:02:02,600 --> 00:02:11,120 of meta space is for how we measure what has been studied, what hasn't been studied, who 31 00:02:11,120 --> 00:02:16,640 is researching and writing about specific things, and who might not be showing up in 32 00:02:16,640 --> 00:02:18,160 that literature. 33 00:02:18,160 --> 00:02:23,960 A lot of that kind of looks like doing reporting and measuring things for administrators, but 34 00:02:23,960 --> 00:02:29,760 a lot of it can also be more novel questions that have to do with who is in what publishing 35 00:02:29,760 --> 00:02:36,240 space, what kind of communities are actually reading and accessing the information that 36 00:02:36,240 --> 00:02:38,000 people are publishing. 37 00:02:38,000 --> 00:02:44,720 So it's a new kind of nebulous field in librarianship, but ultimately it is about how and who is 38 00:02:44,720 --> 00:02:49,360 accessing information, which I love and I think is true librarianship. 39 00:02:49,360 --> 00:02:52,600 It's just kind of that next meta level of it. 40 00:02:52,600 --> 00:02:53,600 Absolutely. 41 00:02:53,600 --> 00:02:59,040 And one of the things you don't add to your title, Beth, is that you're a life changer. 42 00:02:59,040 --> 00:03:04,160 So for the audience, I first met Beth a couple of, gosh, maybe a few months ago now when 43 00:03:04,160 --> 00:03:09,600 I was putting my materials together for a promotion and Beth, I asked Beth, well, someone 44 00:03:09,600 --> 00:03:14,500 actually referred to Beth and said, you just talked to Beth about how to measure your impact. 45 00:03:14,500 --> 00:03:18,920 And so I sat down with Beth and Beth really transformed my experience because after talking 46 00:03:18,920 --> 00:03:23,720 to Beth, I was like, oh, now I know what to write about and how to really represent my 47 00:03:23,720 --> 00:03:26,720 impact in a way that was just beyond just the H index. 48 00:03:26,720 --> 00:03:31,720 So that's what I want to talk about today because Beth, we're all trying to make an 49 00:03:31,720 --> 00:03:37,000 impact in our field and we would be making an impact anyway, but then all of a sudden 50 00:03:37,000 --> 00:03:41,440 we live in the background of people saying, well, let's measure your impact. 51 00:03:41,440 --> 00:03:42,560 What's your H index? 52 00:03:42,560 --> 00:03:46,480 And beyond the H index, many of us don't know how else to measure our impact. 53 00:03:46,480 --> 00:03:48,560 So I'd like to just start there. 54 00:03:48,560 --> 00:03:50,360 Tell me about the H index. 55 00:03:50,360 --> 00:03:54,080 Why it's so, I guess, powerful and important. 56 00:03:54,080 --> 00:03:57,840 What are the limitations and how else can we think about measuring impact? 57 00:03:57,840 --> 00:03:58,940 Absolutely. 58 00:03:58,940 --> 00:04:03,440 And this is one of my favorite topics to talk about because it is nuanced. 59 00:04:03,440 --> 00:04:09,340 The H index, journal impact factor, a lot of these metrics that we hear tossed around 60 00:04:09,340 --> 00:04:17,000 all the time are very specific measurements that measure extremely small aspects of a 61 00:04:17,000 --> 00:04:22,000 particular scholar, of a particular journal, and of the readership of a particular scholar 62 00:04:22,000 --> 00:04:23,000 or journal. 63 00:04:23,000 --> 00:04:28,800 For example, H index is a measure really of productivity, theoretically, productivity 64 00:04:28,800 --> 00:04:35,960 in terms of what we are told is productive by truly publishers and corporate America 65 00:04:35,960 --> 00:04:41,880 and the folks who are making a lot of money off of publications of materials. 66 00:04:41,880 --> 00:04:44,040 And they're usually making that money off of libraries. 67 00:04:44,040 --> 00:04:46,160 So I will put that plug in there. 68 00:04:46,160 --> 00:04:51,120 They're not our favorite folks in the library world. 69 00:04:51,120 --> 00:04:59,000 But an H index is supposed to measure a scholar's amount of publications by how many citations 70 00:04:59,000 --> 00:05:00,080 they get. 71 00:05:00,080 --> 00:05:07,040 So that formula more or less is the number of publications that they have and the highest 72 00:05:07,040 --> 00:05:10,280 cited paper that they've published. 73 00:05:10,280 --> 00:05:16,160 So if a person has 46 papers that they've published and their highest cited paper has 74 00:05:16,160 --> 00:05:22,360 been cited 13 times and they have 13 papers that have been cited 13 times, then their 75 00:05:22,360 --> 00:05:24,080 H index is 13. 76 00:05:24,080 --> 00:05:30,320 Even though they've published 36, 46, however many papers, unlimited number of papers, it's 77 00:05:30,320 --> 00:05:35,280 a way to show that they are both impactful, people are reading them, and they're also 78 00:05:35,280 --> 00:05:36,280 productive. 79 00:05:36,280 --> 00:05:41,520 But if I just gave you that number, you wouldn't know anything about that person. 80 00:05:41,520 --> 00:05:45,420 You wouldn't know whether they study a rare disease. 81 00:05:45,420 --> 00:05:46,420 Because guess what? 82 00:05:46,420 --> 00:05:51,640 People who study rare diseases do not get cited as often as people who study very, very 83 00:05:51,640 --> 00:05:56,800 popular or very well studied or very highly prominent diseases, things that lots of people 84 00:05:56,800 --> 00:06:00,600 have, lots of people talk about, and lots of people fund. 85 00:06:00,600 --> 00:06:07,680 So that already creates a very interesting problem for researchers who are helping and 86 00:06:07,680 --> 00:06:12,580 studying and working with communities that might not be as popularly funded or might 87 00:06:12,580 --> 00:06:14,940 not have a lot of people reading about it. 88 00:06:14,940 --> 00:06:19,720 So those are the types of things that an H index does not take into effect. 89 00:06:19,720 --> 00:06:24,280 It also doesn't tell you anything about where a researcher is in their career. 90 00:06:24,280 --> 00:06:29,000 If you have a new researcher, someone who's new to the field, someone who may be very, 91 00:06:29,000 --> 00:06:34,520 very prominent in their particular fellowship, someone who's going to be a star, whatever 92 00:06:34,520 --> 00:06:38,380 you want to say, they probably don't have a high H index because they have not been 93 00:06:38,380 --> 00:06:47,160 on the planet long enough to have accumulated tons and tons of citations and funding and 94 00:06:47,160 --> 00:06:51,800 things that really help increase those normal traditional metrics. 95 00:06:51,800 --> 00:06:54,920 So it's really important to look at the whole scholar. 96 00:06:54,920 --> 00:07:01,080 An H index means very little if someone is working in something outside of the traditional 97 00:07:01,080 --> 00:07:09,840 norm or working really hard to make sure that the people and the populations that they study 98 00:07:09,840 --> 00:07:12,560 can actually access that information. 99 00:07:12,560 --> 00:07:16,760 So those are some things I can get into if we talk about journal impact factor, but I 100 00:07:16,760 --> 00:07:23,040 often see the folks who have dedicated their lives to truly helping communities, truly 101 00:07:23,040 --> 00:07:29,680 helping the folks that their research, the actual populations that they study and their 102 00:07:29,680 --> 00:07:33,880 research is a part of often don't have the highest H indexes, but are making the biggest 103 00:07:33,880 --> 00:07:35,820 impact within those communities. 104 00:07:35,820 --> 00:07:39,160 And there are other ways to communicate that kind of information. 105 00:07:39,160 --> 00:07:41,280 Thank you, Beth. 106 00:07:41,280 --> 00:07:46,720 So I love how you talk about just the disparities really that exist in how people's work is 107 00:07:46,720 --> 00:07:49,040 showcased or how it's cited. 108 00:07:49,040 --> 00:07:52,120 And yeah, so I was thinking as you were talking, I was like, maybe if I'm a cardiologist studying 109 00:07:52,120 --> 00:07:58,040 coronary artery disease, surely you'll probably get a lot more citations as opposed to those 110 00:07:58,040 --> 00:08:01,680 of us who are in the rare disease space where, to be honest, not that many people are interested 111 00:08:01,680 --> 00:08:03,020 in reading our work. 112 00:08:03,020 --> 00:08:08,200 But then, okay, so if not the H index, what are other metrics to demonstrate our impact? 113 00:08:08,200 --> 00:08:14,640 Yeah, honestly, traditional metrics are never going to be my favorite way to present anything. 114 00:08:14,640 --> 00:08:22,000 But I think if you are in a space where traditional metrics are required, which a lot of us are, 115 00:08:22,000 --> 00:08:27,200 if you receive NIH funding, if you're trying to receive federal funding in any way, if 116 00:08:27,200 --> 00:08:33,680 you are in a very traditional tenure APT kind of process, sometimes you do have to include 117 00:08:33,680 --> 00:08:34,920 those metrics. 118 00:08:34,920 --> 00:08:38,800 But the important thing to do is include the narrative around it. 119 00:08:38,800 --> 00:08:44,480 Keep your narrative to reflect why you have a low or H index. 120 00:08:44,480 --> 00:08:50,040 And you can specifically point to the fact that, hey, the journals that I publish in 121 00:08:50,040 --> 00:08:51,720 are open access. 122 00:08:51,720 --> 00:08:58,600 They might not necessarily be in a mainline database like Scopus or Web of Science where 123 00:08:58,600 --> 00:09:01,560 people will find and cite those papers. 124 00:09:01,560 --> 00:09:05,440 And the reason that they may not be found there, and the reason that I try not to publish 125 00:09:05,440 --> 00:09:11,080 there would be because people have to pay to subscribe to those places. 126 00:09:11,080 --> 00:09:16,280 And if the research that I am working on is maybe for people who live in rural communities, 127 00:09:16,280 --> 00:09:20,720 the hospitals in those rural communities are not going to have access to those publications 128 00:09:20,720 --> 00:09:27,800 unless they are open access on PubMed Central or whatever other means that you have to provide. 129 00:09:27,800 --> 00:09:32,560 That's part of a narrative that you could say, hey, it's intentional that I did this. 130 00:09:32,560 --> 00:09:37,880 The important thing to note is that these are factors that folks actually look and care 131 00:09:37,880 --> 00:09:38,880 about. 132 00:09:38,880 --> 00:09:44,640 And I think that's kind of the secret that a lot of administrators don't necessarily 133 00:09:44,640 --> 00:09:51,760 want you to know because they want to see high numbers, numbers in these top journal 134 00:09:51,760 --> 00:09:59,200 impact journals, these top H indexes, these top kind of performing metrics that a lot 135 00:09:59,200 --> 00:10:01,920 of folks translate. 136 00:10:01,920 --> 00:10:06,120 These metrics that can translate across a lot of different communities, a lot of different 137 00:10:06,120 --> 00:10:08,040 academic spheres. 138 00:10:08,040 --> 00:10:13,040 But they know these things as well, and they work, and they will get you to where you need 139 00:10:13,040 --> 00:10:14,040 to go. 140 00:10:14,040 --> 00:10:17,440 It's just making sure that the researchers are able to communicate that. 141 00:10:17,440 --> 00:10:22,320 And I think that's one of the biggest challenges that we face in scholarly communication and 142 00:10:22,320 --> 00:10:28,080 scientific communication is recognizing all the ways that our information is disseminated 143 00:10:28,080 --> 00:10:30,680 in a way that actually does help the population. 144 00:10:30,680 --> 00:10:33,120 Because ultimately, why are we here? 145 00:10:33,120 --> 00:10:36,240 Except to help the populations that we're there for. 146 00:10:36,240 --> 00:10:37,240 I love it, Beth. 147 00:10:37,240 --> 00:10:38,240 Thank you so much. 148 00:10:38,240 --> 00:10:39,240 You bring hope. 149 00:10:39,240 --> 00:10:40,240 I try. 150 00:10:40,240 --> 00:10:41,240 Okay. 151 00:10:41,240 --> 00:10:47,540 So one of the things that I hear you talking about is owning your narrative. 152 00:10:47,540 --> 00:10:50,400 And so it's like, what story, actually, it's funny. 153 00:10:50,400 --> 00:10:52,720 You said, this is what I intentionally did. 154 00:10:52,720 --> 00:10:54,360 Some of us didn't intentionally do anything. 155 00:10:54,360 --> 00:10:57,420 We just ended up here and we're like, oh, now I have to tell the story. 156 00:10:57,420 --> 00:11:02,320 But it's how do you shape the narrative in a way that highlights your work in its best 157 00:11:02,320 --> 00:11:03,320 light? 158 00:11:03,320 --> 00:11:07,640 And if you have an age index, that's great, but it's not... 159 00:11:07,640 --> 00:11:11,120 You can't just rely on that and say, well, I have a high age index, therefore my work 160 00:11:11,120 --> 00:11:12,240 speaks for itself. 161 00:11:12,240 --> 00:11:14,800 But how do you even shape the narrative around that high age index? 162 00:11:14,800 --> 00:11:18,860 And if you don't have a high age index, how do you shape the narrative around what you 163 00:11:18,860 --> 00:11:20,080 do not have? 164 00:11:20,080 --> 00:11:24,240 But not with a focus on what you don't have, but with a focus on the impact of your work 165 00:11:24,240 --> 00:11:26,800 and the communities that it reaches out to. 166 00:11:26,800 --> 00:11:31,880 And so one of the things I want to speak to, so when I sat down with you, you talked about 167 00:11:31,880 --> 00:11:34,880 my collaborations with international collaborators. 168 00:11:34,880 --> 00:11:40,440 You talked about some of my work being cited in the top 25% of journals by site score. 169 00:11:40,440 --> 00:11:41,840 That was all news to me. 170 00:11:41,840 --> 00:11:47,160 Can you talk to me about how we can find some of these non-traditional metrics in a way 171 00:11:47,160 --> 00:11:49,760 that helps us spin the narrative about our work? 172 00:11:49,760 --> 00:11:50,760 Absolutely. 173 00:11:50,760 --> 00:11:54,640 And my favorite metric, if we were going to talk about a concrete metric, my favorite 174 00:11:54,640 --> 00:12:00,120 one and the one that I encourage authors to utilize as much as possible is the journal 175 00:12:00,120 --> 00:12:06,360 quartile, which is really where your journal that you published in falls within a normalized 176 00:12:06,360 --> 00:12:08,760 category that you publish in. 177 00:12:08,760 --> 00:12:14,640 So if you publish in rare diseases, your journal that you publish in is going to be grouped 178 00:12:14,640 --> 00:12:18,280 in a category with other rare diseases that it is similar to. 179 00:12:18,280 --> 00:12:22,200 So it is what we call a field normalized category. 180 00:12:22,200 --> 00:12:29,200 And that can often really show you where you are truly in a way that will communicate better 181 00:12:29,200 --> 00:12:32,000 to the folks who need to hear it. 182 00:12:32,000 --> 00:12:36,000 So this is talking specifically about journal impact factor now. 183 00:12:36,000 --> 00:12:42,960 So this is a metric that a lot of people don't love because we're comparing apples and oranges 184 00:12:42,960 --> 00:12:44,200 a lot of times with this. 185 00:12:44,200 --> 00:12:48,200 When we're looking at an impact factor of a journal, it's comparing review articles 186 00:12:48,200 --> 00:12:51,160 with RCTs, with editorials. 187 00:12:51,160 --> 00:12:55,240 These are all things that are citable material within a journal, but we're kind of comparing 188 00:12:55,240 --> 00:13:00,840 them all, which as a person interested in data, I think that is a questionable way to 189 00:13:00,840 --> 00:13:03,920 go about things, but it is where we are. 190 00:13:03,920 --> 00:13:10,560 But the quartile is the way that a lot of journals try and solve for this issue by comparing 191 00:13:10,560 --> 00:13:12,280 things, apples and apples. 192 00:13:12,280 --> 00:13:18,560 So like we mentioned earlier, you would never compare a cardiologist's publishing history 193 00:13:18,560 --> 00:13:21,400 to someone who studies rural health. 194 00:13:21,400 --> 00:13:24,400 And just specifically though, there may be overlap there. 195 00:13:24,400 --> 00:13:29,360 Like a community health journal would not be in the same category as someone who studies 196 00:13:29,360 --> 00:13:34,720 like thoracic surgery or anything like that, because the populations who are reading those 197 00:13:34,720 --> 00:13:36,840 journals are very different. 198 00:13:36,840 --> 00:13:40,300 Their publication, the people who cite them are very different. 199 00:13:40,300 --> 00:13:46,280 So what I would recommend for someone who looks and sees, oh, I don't publish in high 200 00:13:46,280 --> 00:13:53,360 impact journals and I don't publish enough to have a high H index in the same like traditional 201 00:13:53,360 --> 00:13:54,360 way. 202 00:13:54,360 --> 00:13:59,200 I would really recommend that person look at their publishing history and look for patterns. 203 00:13:59,200 --> 00:14:03,320 Am I publishing in journals that reach a certain population? 204 00:14:03,320 --> 00:14:06,240 Am I publishing in open access journals? 205 00:14:06,240 --> 00:14:10,520 Am I publishing in journals that are around a particular theme? 206 00:14:10,520 --> 00:14:11,520 What is that theme? 207 00:14:11,520 --> 00:14:18,600 And how can I communicate that theme to my reviewers, to anyone who is trying to judge 208 00:14:18,600 --> 00:14:22,080 me by these metrics or whatever it is. 209 00:14:22,080 --> 00:14:25,100 And there are arguments that you can make about those journals. 210 00:14:25,100 --> 00:14:31,160 One of the best things that I like to show for this is if you're publishing about a marginalized 211 00:14:31,160 --> 00:14:39,020 population and you don't have high citations on your articles, it's probably because the 212 00:14:39,020 --> 00:14:45,460 journals that are citing you are not necessarily indexed in a database like Scopus or a database 213 00:14:45,460 --> 00:14:47,440 like Web of Science. 214 00:14:47,440 --> 00:14:49,920 And the free databases do not show you your citation. 215 00:14:49,920 --> 00:14:51,080 There's a reason for that. 216 00:14:51,080 --> 00:14:54,760 So if you look at PubMed, PubMed is what we utilize for everything. 217 00:14:54,760 --> 00:14:59,880 PubMed is how we find the majority of information and it's how the world finds the majority 218 00:14:59,880 --> 00:15:00,880 of information. 219 00:15:00,880 --> 00:15:10,000 It's a huge, huge, openly accessible database, which is why ChatGPT trains the majority of 220 00:15:10,000 --> 00:15:16,840 their algorithm, of their large language model off of PubMed because it's freely available. 221 00:15:16,840 --> 00:15:22,680 And a big point to make from that is it doesn't have citations because it doesn't know who 222 00:15:22,680 --> 00:15:23,680 cites anyone. 223 00:15:23,680 --> 00:15:24,680 It doesn't track that. 224 00:15:24,680 --> 00:15:25,680 It doesn't index. 225 00:15:25,680 --> 00:15:26,680 It doesn't read. 226 00:15:26,680 --> 00:15:30,060 It doesn't care about those types of things for a reason. 227 00:15:30,060 --> 00:15:32,800 It's impossible to track all of those things. 228 00:15:32,800 --> 00:15:39,440 So it's important to look back and say, okay, if I am publishing in a rural health journal, 229 00:15:39,440 --> 00:15:41,440 who is citing me? 230 00:15:41,440 --> 00:15:46,660 Probably not someone who's indexing and getting a big name journal to publish in one of these 231 00:15:46,660 --> 00:15:48,360 major databases. 232 00:15:48,360 --> 00:15:49,360 So who are they? 233 00:15:49,360 --> 00:15:50,360 Go find them. 234 00:15:50,360 --> 00:15:52,760 You can use Google Scholar for that type of metric. 235 00:15:52,760 --> 00:15:56,240 You can also provide presentations. 236 00:15:56,240 --> 00:15:59,920 You can provide your additional outside kind of content. 237 00:15:59,920 --> 00:16:03,280 Your presentations that you give at the rural hospital. 238 00:16:03,280 --> 00:16:09,280 The conference proceedings that you give or teaching the teaching that you do to train 239 00:16:09,280 --> 00:16:11,240 doctors in these rural places. 240 00:16:11,240 --> 00:16:15,640 Whatever the example is, there are narratives that you can pull in to say like, yeah, I'm 241 00:16:15,640 --> 00:16:20,160 not getting citations because the folks who read my papers don't publish. 242 00:16:20,160 --> 00:16:21,640 They're doctors. 243 00:16:21,640 --> 00:16:25,540 Those are some of the ways that I think are really interesting to start to provide a more 244 00:16:25,540 --> 00:16:27,900 nuanced picture of yourself. 245 00:16:27,900 --> 00:16:28,900 Another great example. 246 00:16:28,900 --> 00:16:30,760 I love this group. 247 00:16:30,760 --> 00:16:34,440 I can't talk about, I'm not going to name what group they are. 248 00:16:34,440 --> 00:16:35,440 They ever listen to this podcast. 249 00:16:35,440 --> 00:16:36,440 We'll know who they are. 250 00:16:36,440 --> 00:16:41,880 So y'all are my favorite, but I have a rogue group of physicians who are very against using 251 00:16:41,880 --> 00:16:44,860 any type of metrics to describe their work. 252 00:16:44,860 --> 00:16:49,600 And some of the ways that they've been really interested to show true impact is to find 253 00:16:49,600 --> 00:16:55,080 their citations in up to date and actually go and see, okay, am I actually being used? 254 00:16:55,080 --> 00:17:00,200 Are the publications that I write actually making it to physicians who are treating patients? 255 00:17:00,200 --> 00:17:02,440 Cause that's where you would look. 256 00:17:02,440 --> 00:17:07,440 I did almost, well, I did, it's not an almost, I did violate my terms and conditions on my 257 00:17:07,440 --> 00:17:12,320 up to date license to try and scrape it and find those, find those citations, but that's 258 00:17:12,320 --> 00:17:13,320 for a different story. 259 00:17:13,320 --> 00:17:14,840 I still work here, so it's fine. 260 00:17:14,840 --> 00:17:18,280 No one was fired in the making of that story. 261 00:17:18,280 --> 00:17:25,240 Another way that this group is working to find ways to show other impact outside of 262 00:17:25,240 --> 00:17:30,640 citations outside of H index, outside of journal impact factor is to see their citations and 263 00:17:30,640 --> 00:17:36,840 consensus papers and actually go and see are people working with the research that I do? 264 00:17:36,840 --> 00:17:40,120 Is the research that I do impacting the field? 265 00:17:40,120 --> 00:17:45,280 And those are some measures that to me, if I saw that cited, if I saw that communicated 266 00:17:45,280 --> 00:17:51,120 in a narrative, it would mean more to me than just a random publication in a random journal 267 00:17:51,120 --> 00:17:54,920 that may or may not have been deeply well done. 268 00:17:54,920 --> 00:17:58,360 It speaks nothing to the quality of a paper. 269 00:17:58,360 --> 00:18:03,160 If it's included in a journal, it speaks a lot to the quality of the paper. 270 00:18:03,160 --> 00:18:08,600 If it's included in a consensus paper or something along those lines. 271 00:18:08,600 --> 00:18:09,600 Thank you, Beth. 272 00:18:09,600 --> 00:18:14,580 And I remember one of the things we did was look at some of my articles and look to see 273 00:18:14,580 --> 00:18:21,800 how many of these guidelines papers had actually cited my papers, which then allowed me to 274 00:18:21,800 --> 00:18:27,240 make the narrative of, you know, or to create a narrative of, well, my work is foundational 275 00:18:27,240 --> 00:18:30,720 such that these guidelines are citing my work. 276 00:18:30,720 --> 00:18:32,840 I mean, it's foundational. 277 00:18:32,840 --> 00:18:35,720 That's what I want to hear every time with the folks that I work with. 278 00:18:35,720 --> 00:18:37,440 And that's how you prove it. 279 00:18:37,440 --> 00:18:38,960 I mean, and it's beautiful. 280 00:18:38,960 --> 00:18:41,480 It's really, really great to think outside of that box. 281 00:18:41,480 --> 00:18:45,040 Now, there's one thing you mentioned that I want to go back and kind of try to address, 282 00:18:45,040 --> 00:18:49,360 because when you look at your work, saying Google scholar, you find a certain age index 283 00:18:49,360 --> 00:18:53,640 or certain number of citations as opposed to when you go to a place like Scopus. 284 00:18:53,640 --> 00:18:58,080 And then actually looking at my work, I have fewer citations than Scopus compared to Google 285 00:18:58,080 --> 00:18:59,080 scholar. 286 00:18:59,080 --> 00:19:01,280 What's the difference between the two? 287 00:19:01,280 --> 00:19:02,280 Great question. 288 00:19:02,280 --> 00:19:09,680 So Google scholar, Google versus Elsevier, it's big evil company versus big evil company. 289 00:19:09,680 --> 00:19:16,640 It's, you know, elitist, one elitist institution, you know, like counting citations and other 290 00:19:16,640 --> 00:19:22,320 elitist things versus a what I would refer to as a very opaque system. 291 00:19:22,320 --> 00:19:28,800 So in something like Scopus or Web of Science, we know exactly what is being counted. 292 00:19:28,800 --> 00:19:34,200 They have specific journals that they will actively tell you these are what we've indexed. 293 00:19:34,200 --> 00:19:38,760 So if you're cited in anywhere in these journals that we look at, we're going to count it and 294 00:19:38,760 --> 00:19:41,360 it'll count toward our numbers. 295 00:19:41,360 --> 00:19:44,400 Google scholar opaque. 296 00:19:44,400 --> 00:19:45,840 We don't know what it's counting. 297 00:19:45,840 --> 00:19:50,240 We know that it's probably counting the same things and then some. 298 00:19:50,240 --> 00:19:56,100 One of the biggest kind of inflators of Google scholar numbers, Google scholar numbers tend 299 00:19:56,100 --> 00:19:58,560 to be higher, which is why people love them. 300 00:19:58,560 --> 00:19:59,880 I don't I don't blame them. 301 00:19:59,880 --> 00:20:02,160 We want to make it look as high as possible. 302 00:20:02,160 --> 00:20:07,600 But it does tend to be more inflated than other locations because it often will double 303 00:20:07,600 --> 00:20:14,120 count your open access papers and it will often count an index of something that's in 304 00:20:14,120 --> 00:20:17,800 PubMed Central with an index of something that's in Scopus. 305 00:20:17,800 --> 00:20:22,960 So sometimes you'll get, you know, four or five points higher if it says that you have 306 00:20:22,960 --> 00:20:23,960 higher papers. 307 00:20:23,960 --> 00:20:27,920 So if it said if it counts that you have, you know, that same paper that's living in 308 00:20:27,920 --> 00:20:33,000 two locations, that same paper that's living in research gate, that's also in PubMed Central, 309 00:20:33,000 --> 00:20:37,800 that's also on the journals website that will sometimes inflate your numbers a little bit, 310 00:20:37,800 --> 00:20:42,760 which is often why people put their papers in these locations because they know that 311 00:20:42,760 --> 00:20:47,080 and that's the other kind of area that I like to discuss with Google is that folks who have 312 00:20:47,080 --> 00:20:49,960 the time to game it can't. 313 00:20:49,960 --> 00:20:54,800 That's the big thing to know is that folks who have the time to spend, you know, a lot 314 00:20:54,800 --> 00:21:00,400 of effort making sure that their papers link out to specific places, making sure that their 315 00:21:00,400 --> 00:21:05,480 citations are perhaps double counting, they succeed in that environment. 316 00:21:05,480 --> 00:21:09,080 It's a little more gameable than something like Scopus or Web of Science. 317 00:21:09,080 --> 00:21:15,840 So those are the kind of how you weigh that situation of one evil company versus another 318 00:21:15,840 --> 00:21:22,160 evil company versus one that is a little bit more elitist and kind of locked down of who 319 00:21:22,160 --> 00:21:27,960 can count what, what counts and what doesn't versus one that is gameable by folks who have 320 00:21:27,960 --> 00:21:33,120 the capacity, the time, the energy to do something and the knowledge, truly the knowledge to 321 00:21:33,120 --> 00:21:35,080 do that kind of work. 322 00:21:35,080 --> 00:21:36,400 Wow. 323 00:21:36,400 --> 00:21:39,560 This is how you know you're talking to the expert when she can tell you how to game the 324 00:21:39,560 --> 00:21:44,460 system and I hope, you know, but I, you know, it's interesting. 325 00:21:44,460 --> 00:21:45,460 People do it, right? 326 00:21:45,460 --> 00:21:49,280 So it's kind of like, I don't know that it's an open secret, but it's, it's, people do 327 00:21:49,280 --> 00:21:53,920 it and if you want to look up how to do it, you can, but I think that the real issue is 328 00:21:53,920 --> 00:21:58,680 how do you, how do you present your work in a way that honors the work you've done, honors 329 00:21:58,680 --> 00:22:03,200 the communities you served without trying to play a game because at the end of the day, 330 00:22:03,200 --> 00:22:04,840 it's not, it's not worth it. 331 00:22:04,840 --> 00:22:05,840 At least I think so. 332 00:22:05,840 --> 00:22:06,840 Totally agree. 333 00:22:06,840 --> 00:22:07,840 Totally agree. 334 00:22:07,840 --> 00:22:11,200 It's a capitalist system, so it's always going to be a game. 335 00:22:11,200 --> 00:22:15,560 It just depends on, you know, how much time, energy and funding do you have to play that 336 00:22:15,560 --> 00:22:16,560 game? 337 00:22:16,560 --> 00:22:17,560 Sure. 338 00:22:17,560 --> 00:22:18,560 Sure. 339 00:22:18,560 --> 00:22:19,560 No really good points, really good points. 340 00:22:19,560 --> 00:22:20,560 Okay. 341 00:22:20,560 --> 00:22:25,720 So we've been talking about from the perspective of the investigator demonstrating their impact. 342 00:22:25,720 --> 00:22:30,160 One of the things you also do is you help institutions understand the impact of their 343 00:22:30,160 --> 00:22:31,560 investigators. 344 00:22:31,560 --> 00:22:32,960 Tell me a little bit about that. 345 00:22:32,960 --> 00:22:33,960 Yeah. 346 00:22:33,960 --> 00:22:41,200 So my August through October is absolutely slammed with end of fiscal year reports providing 347 00:22:41,200 --> 00:22:47,440 large data sets of publication data that I'll either add information to, to make a whole 348 00:22:47,440 --> 00:22:52,640 piece, a whole presentable data set about a particular department. 349 00:22:52,640 --> 00:22:59,120 So I will again, not say any department names or Institute names, but usually it's a particular 350 00:22:59,120 --> 00:23:04,000 division, a particular department or an Institute at our, at Duke, where they would request 351 00:23:04,000 --> 00:23:11,600 in, you know, July, August, we're going to have X meeting or do X report in October and 352 00:23:11,600 --> 00:23:16,800 we'll need to know every publication that our department has done in the last year, 353 00:23:16,800 --> 00:23:22,680 how it's been cited and what journal, what journal and what impact the journal was. 354 00:23:22,680 --> 00:23:29,840 So, and I would say that, you know, I wish that the whole journal impact kind of that, 355 00:23:29,840 --> 00:23:36,520 that factor of it was starting to like lose its, its sting and lose its popularity, but 356 00:23:36,520 --> 00:23:37,520 it really hasn't. 357 00:23:37,520 --> 00:23:44,160 I would say that almost every, every department that I work with does act, ask for me to add 358 00:23:44,160 --> 00:23:47,060 impact factor into the data sets that I provide. 359 00:23:47,060 --> 00:23:51,920 So every year, every single year they get a lecture from me where I tell them, recognize 360 00:23:51,920 --> 00:23:57,600 that if you are, if you have any researchers who are working in rare disease spaces, this 361 00:23:57,600 --> 00:24:00,440 is not going to be an accurate metric for them. 362 00:24:00,440 --> 00:24:06,360 Also recognize that if you have any new journals or folks who are publishing in novel fields 363 00:24:06,360 --> 00:24:12,520 or doing novel research, this is not going to be an, an accurate rating or an accurate 364 00:24:12,520 --> 00:24:14,040 measurement for them. 365 00:24:14,040 --> 00:24:18,960 And so whether they ask for it or not, I always include the core tile, which will tell them 366 00:24:18,960 --> 00:24:22,900 where they fall within that, their specific field. 367 00:24:22,900 --> 00:24:29,080 And I personally try to provide data visualizations or ways that I can communicate what a core 368 00:24:29,080 --> 00:24:33,200 tile is about their department kind of automatically. 369 00:24:33,200 --> 00:24:36,640 Most of them don't ask for that, but I provide it anyway. 370 00:24:36,640 --> 00:24:41,600 And it does tend to make its way into their reports, does tend to make it into their kind 371 00:24:41,600 --> 00:24:45,120 of like larger meetings where they're presenting and they're like, Oh, we have a visualization 372 00:24:45,120 --> 00:24:46,120 that's already made. 373 00:24:46,120 --> 00:24:47,920 Thank you, librarian for doing that. 374 00:24:47,920 --> 00:24:52,880 And that's how I kind of sneak in the value of more normalized fields. 375 00:24:52,880 --> 00:24:59,240 Granted, I do have some departments that will actually normalize for fields. 376 00:24:59,240 --> 00:25:03,040 So I have folks who, if you're familiar with the population health department at Duke, 377 00:25:03,040 --> 00:25:04,040 it's fairly new. 378 00:25:04,040 --> 00:25:11,260 It's a fairly young department and a lot of the journals that they work in are very interdisciplinary. 379 00:25:11,260 --> 00:25:16,040 So those tend to have much lower journal impact factors because they're newer. 380 00:25:16,040 --> 00:25:17,800 They're not, they haven't been as round as long. 381 00:25:17,800 --> 00:25:20,000 They haven't built up the following. 382 00:25:20,000 --> 00:25:24,920 And honestly, libraries haven't purchased as many of their subscriptions just because 383 00:25:24,920 --> 00:25:29,200 they're so new and people don't request them quite as much as guess what? 384 00:25:29,200 --> 00:25:31,640 Community health doesn't have as much money as others. 385 00:25:31,640 --> 00:25:32,640 Shock. 386 00:25:32,640 --> 00:25:34,240 We're all surprised by that. 387 00:25:34,240 --> 00:25:38,760 So I've worked with a couple of departments that now are institutes here that have interdisciplinary 388 00:25:38,760 --> 00:25:45,000 groups to actually lower what they consider a high impact journal for particular fields, 389 00:25:45,000 --> 00:25:54,080 which does go a long way to making that impact actually more normalized where we have journals 390 00:25:54,080 --> 00:26:00,640 like science, nature that have impact factors in the nineties, over a hundred points, things 391 00:26:00,640 --> 00:26:01,800 like that. 392 00:26:01,800 --> 00:26:04,240 And then we have folks in population health. 393 00:26:04,240 --> 00:26:11,360 That'll be the top Q1 journal in all of population health that has a one or a two. 394 00:26:11,360 --> 00:26:13,800 And that's the highest, that's the highest journal. 395 00:26:13,800 --> 00:26:16,800 So I apologize. 396 00:26:16,800 --> 00:26:20,720 All right. 397 00:26:20,720 --> 00:26:21,720 Thank you so much. 398 00:26:21,720 --> 00:26:24,300 Gosh, you know, Beth, I almost feel as if so. 399 00:26:24,300 --> 00:26:28,600 So from what you're telling me, you're like the, the, the undercover crusader working 400 00:26:28,600 --> 00:26:34,200 so hard to, to make sure that people are valuing the work of investigators well, whether that 401 00:26:34,200 --> 00:26:38,040 is investigators valuing their own work, but also departments valuing the work of their 402 00:26:38,040 --> 00:26:39,760 investigators, their faculty. 403 00:26:39,760 --> 00:26:42,240 So thank you for the work that you do. 404 00:26:42,240 --> 00:26:44,480 I'm curious about the visualization. 405 00:26:44,480 --> 00:26:50,320 How can faculty for themselves create their own visual representation of the kind of work 406 00:26:50,320 --> 00:26:52,240 that they've done and their impact? 407 00:26:52,240 --> 00:26:53,240 Absolutely. 408 00:26:53,240 --> 00:26:57,880 First, I'll shout out our library resources, both here at the medical center library and 409 00:26:57,880 --> 00:26:59,480 at our main campus library. 410 00:26:59,480 --> 00:27:03,920 And if you're a researcher listening anywhere that has access to a medical or university 411 00:27:03,920 --> 00:27:09,440 library, I guarantee that they have workshops that they're teaching to show researchers, 412 00:27:09,440 --> 00:27:15,720 faculty, including sending your, your researchers, your postdocs there to go learn it for you, 413 00:27:15,720 --> 00:27:20,560 how to use a variety of different tools that are available to actually communicate that 414 00:27:20,560 --> 00:27:21,560 data. 415 00:27:21,560 --> 00:27:25,000 Of course, some of the easiest tools that you have, I'm sure anyone would have access 416 00:27:25,000 --> 00:27:27,040 to it in Google sheets. 417 00:27:27,040 --> 00:27:32,980 In Excel, you can make a graph, you can make a table, but the benefit of actually providing 418 00:27:32,980 --> 00:27:40,440 an image for someone who's trying to communicate a point is it's easy. 419 00:27:40,440 --> 00:27:41,440 It's easy. 420 00:27:41,440 --> 00:27:42,440 Someone can read it. 421 00:27:42,440 --> 00:27:44,720 Someone doesn't have to spend a lot of time interpreting it. 422 00:27:44,720 --> 00:27:51,000 They can look quickly at a bar chart and say, all right, Q4, that's the lowest, Q1, that's 423 00:27:51,000 --> 00:27:54,440 the highest, Q1 is gray, Q1, Q4 is this. 424 00:27:54,440 --> 00:27:59,160 And I can see that we have a lot of Q1 journals that just might not have super high impact 425 00:27:59,160 --> 00:28:00,640 factors. 426 00:28:00,640 --> 00:28:06,720 It's so easy to, for me to make those in like 30 seconds over data that someone from a particular 427 00:28:06,720 --> 00:28:10,800 department has provided that will end up somewhere. 428 00:28:10,800 --> 00:28:15,600 It's just taking a little time, you know, a minute and a half of my time that will take 429 00:28:15,600 --> 00:28:20,280 a minute and a half off of that poor administrator or that poor coordinator who's making those 430 00:28:20,280 --> 00:28:24,600 slides who's already slammed and be like, it'll sneak in there. 431 00:28:24,600 --> 00:28:30,600 But for a researcher, we all know the value of data visualization in the way that we publish 432 00:28:30,600 --> 00:28:36,840 and how we communicate things, how, you know, color can make someone feel a certain way 433 00:28:36,840 --> 00:28:43,240 or a bar or a pie chart can be sometimes pretty racist if we use it badly. 434 00:28:43,240 --> 00:28:48,080 There are all kinds of ways that we can learn how to use data visualizations in an ethical 435 00:28:48,080 --> 00:28:50,640 way and to share our own narrative. 436 00:28:50,640 --> 00:28:56,840 One example of this might be if you're demonstrating your own research is making a simple bar chart 437 00:28:56,840 --> 00:28:59,480 of how you publish and what journals you publish in. 438 00:28:59,480 --> 00:29:00,760 How many are open access? 439 00:29:00,760 --> 00:29:06,120 If you have a pie chart of everything that you've published and 90% of that is open access, 440 00:29:06,120 --> 00:29:07,880 that communicates a lot. 441 00:29:07,880 --> 00:29:12,160 Just to say like, oh, pretty much everything I do is openly accessible to all of the folks 442 00:29:12,160 --> 00:29:13,660 that I work with. 443 00:29:13,660 --> 00:29:17,440 Or you want to say that all of everything that I publish is a Q1 journal. 444 00:29:17,440 --> 00:29:19,240 It's just not a high impact factor. 445 00:29:19,240 --> 00:29:25,280 Those are really easy ways to show something that someone will look at lightly and immediately 446 00:29:25,280 --> 00:29:30,720 understand without having to read deeply through, oh, I published here and here and here and 447 00:29:30,720 --> 00:29:33,480 here and this is what this is and this is and this is. 448 00:29:33,480 --> 00:29:35,600 It's a quick, you immediately know. 449 00:29:35,600 --> 00:29:40,800 And we all know that people who are reviewing us, whether they're, you know, program officers 450 00:29:40,800 --> 00:29:44,760 at the NIH or they're administrative, like faculty that, you know, are administrators 451 00:29:44,760 --> 00:29:50,080 and faculty members that are granting us tenure, they're the folks who have the least amount 452 00:29:50,080 --> 00:29:53,480 of time to look at these things and delve deeply into them. 453 00:29:53,480 --> 00:29:55,480 So let's make it easy on them. 454 00:29:55,480 --> 00:29:56,840 Oh, it's really good. 455 00:29:56,840 --> 00:29:57,840 It's really good. 456 00:29:57,840 --> 00:30:01,400 Let's just take a little bit of effort and make something that makes it easy for someone 457 00:30:01,400 --> 00:30:02,760 to understand your impact. 458 00:30:02,760 --> 00:30:04,000 I love it. 459 00:30:04,000 --> 00:30:05,000 Okay. 460 00:30:05,000 --> 00:30:12,640 If you could speculate on the perfect score, how to create the perfect score, or maybe 461 00:30:12,640 --> 00:30:18,200 not so much score as metric or maybe it's not a score. 462 00:30:18,200 --> 00:30:20,160 What would you recommend? 463 00:30:20,160 --> 00:30:22,100 Kind of looking at the whole landscape. 464 00:30:22,100 --> 00:30:23,900 How would you recommend we do this? 465 00:30:23,900 --> 00:30:28,280 Because the whole purpose, right, is to compare one investigator to another. 466 00:30:28,280 --> 00:30:32,720 But what we're really doing as you, as you highlighted, is comparing apples to oranges 467 00:30:32,720 --> 00:30:36,960 and then feeling good about ourselves, but not really doing a good job. 468 00:30:36,960 --> 00:30:42,640 How should institutions be thinking about evaluating kind of the impact of the work 469 00:30:42,640 --> 00:30:44,200 their investigators are doing? 470 00:30:44,200 --> 00:30:45,200 Yeah. 471 00:30:45,200 --> 00:30:48,500 From the institutional level, it's look for that narrative. 472 00:30:48,500 --> 00:30:54,480 Look and see who the person is and look at who the population they work with, who can 473 00:30:54,480 --> 00:30:56,240 access their work. 474 00:30:56,240 --> 00:31:02,000 It's awesome if, you know, they're published in Nature, but if nobody reading Nature gets 475 00:31:02,000 --> 00:31:08,480 anything out of it, if nobody reading Nature actually cares about this particular rare 476 00:31:08,480 --> 00:31:12,520 disease and is going to use it, is it used? 477 00:31:12,520 --> 00:31:18,800 So I think the real clutch part for any person who is going up for review, who's trying to 478 00:31:18,800 --> 00:31:24,680 make their narrative, who's trying to actually communicate what they're doing is to look 479 00:31:24,680 --> 00:31:33,440 at where they're being cited at the population level, whether that is rural hospitals newsletter 480 00:31:33,440 --> 00:31:38,160 and just citing that, whether it's on ABC and you're actually getting written up in 481 00:31:38,160 --> 00:31:43,400 a news story that's communicated in the morning news, whether it is in somebody's podcast 482 00:31:43,400 --> 00:31:47,480 that is actually being listened to, you know, like these are the things where you actually 483 00:31:47,480 --> 00:31:49,960 are communicating that research. 484 00:31:49,960 --> 00:31:54,360 Those are some more like altmetrics that we always talk about altmetrics, these additional 485 00:31:54,360 --> 00:31:55,360 kind of things. 486 00:31:55,360 --> 00:31:59,920 Like it used to be very popular to say that your altmetrics were on Twitter, but now I 487 00:31:59,920 --> 00:32:04,280 have to like look for other things because our library no longer supports Twitter slash 488 00:32:04,280 --> 00:32:08,680 formerly known as Twitter X now formerly known as Twitter and whatever that is. 489 00:32:08,680 --> 00:32:14,080 There are lots of ways that you can measure how things have been seen outside of these 490 00:32:14,080 --> 00:32:20,360 traditional narratives and it doesn't have to be something fancy like a documentary or 491 00:32:20,360 --> 00:32:24,400 you know, you were seen on, you got an NPR story about you like awesome. 492 00:32:24,400 --> 00:32:26,440 That would be awesome if you had an NPR story about you. 493 00:32:26,440 --> 00:32:31,940 I'm not going to say it's not awesome, but like getting written up in like a local journal 494 00:32:31,940 --> 00:32:37,400 that actually reaches folks who, who need it, I think is the most important. 495 00:32:37,400 --> 00:32:39,240 I have a good colleague. 496 00:32:39,240 --> 00:32:43,840 I used to be an environmental science librarian and I have a colleague who studies beavers 497 00:32:43,840 --> 00:32:49,760 and fire prevention, which is so random, but you know, she never dedicated her time to 498 00:32:49,760 --> 00:32:54,520 actually publishing in these major major journals because she was actually trying to make an 499 00:32:54,520 --> 00:33:00,260 impact on like California policy, which has like all these regulations about where a beaver 500 00:33:00,260 --> 00:33:02,800 can be and not be and it's right. 501 00:33:02,800 --> 00:33:08,320 Like anyway, it doesn't matter, but that was where she focused her actual goals and her 502 00:33:08,320 --> 00:33:09,320 communication. 503 00:33:09,320 --> 00:33:10,620 So she published in local journals. 504 00:33:10,620 --> 00:33:14,640 She published and wrote at major conferences that were just statewide. 505 00:33:14,640 --> 00:33:20,300 It didn't matter to her so much about these bigger, like, you know, bigger journals that 506 00:33:20,300 --> 00:33:24,200 might matter to someone who's trying to like climb a ladder, which is all fine. 507 00:33:24,200 --> 00:33:26,120 I'm not saying there's anything wrong climbing the ladder. 508 00:33:26,120 --> 00:33:27,120 It's important. 509 00:33:27,120 --> 00:33:29,480 We need good people at the top of the ladder too. 510 00:33:29,480 --> 00:33:32,600 But that was kind of her goal. 511 00:33:32,600 --> 00:33:37,880 And so her major representation in her tenure package was speaking on the state floor, the 512 00:33:37,880 --> 00:33:42,560 house floor at like the California, one of the state Senate meetings, because she had 513 00:33:42,560 --> 00:33:47,040 worked her way up to being able to provide her testimony and give expert testimony in 514 00:33:47,040 --> 00:33:48,040 that level. 515 00:33:48,040 --> 00:33:49,580 And she did get tenure off of that. 516 00:33:49,580 --> 00:33:53,400 And she did get a lot of praise and kind of accolade for that. 517 00:33:53,400 --> 00:33:58,480 But that's what I'm talking about with a narrative is like, it would be awesome if we all publish 518 00:33:58,480 --> 00:34:03,000 in nature, if we all publish in these big journals, we all are in JAMA. 519 00:34:03,000 --> 00:34:04,360 Everybody's so proud of us. 520 00:34:04,360 --> 00:34:11,960 But that narrative of I did X, Y, and Z to scaffold to this goal, which forwards my research, 521 00:34:11,960 --> 00:34:15,800 that is a narrative that you would give someone tenure for, in my opinion. 522 00:34:15,800 --> 00:34:17,080 I love it. 523 00:34:17,080 --> 00:34:18,080 I love it. 524 00:34:18,080 --> 00:34:19,680 It's individualizing the process. 525 00:34:19,680 --> 00:34:21,340 It's easier. 526 00:34:21,340 --> 00:34:24,920 It's easier for us to just pick a number and not have to do any work. 527 00:34:24,920 --> 00:34:27,540 But really it's saying it's doing the work. 528 00:34:27,540 --> 00:34:30,320 It's the investigators doing the work of representing their work well. 529 00:34:30,320 --> 00:34:35,480 And this institution is not trying to put everybody in a one size fits all box. 530 00:34:35,480 --> 00:34:40,400 And just make it easy for that reader, for the person who's judging you to easily follow 531 00:34:40,400 --> 00:34:41,400 that narrative. 532 00:34:41,400 --> 00:34:45,680 Dare I say it might be writing skills, which is scary to have to say, but good writing 533 00:34:45,680 --> 00:34:51,120 skills, good communication in that sense, but also just paying attention and looking 534 00:34:51,120 --> 00:34:53,280 for patterns in where you've published. 535 00:34:53,280 --> 00:34:55,800 Even if you are like, I have no idea how I got here. 536 00:34:55,800 --> 00:34:57,360 I don't really know who I talked to. 537 00:34:57,360 --> 00:34:58,360 But it's a pattern. 538 00:34:58,360 --> 00:35:01,000 There'll be some type of pattern that you can pull. 539 00:35:01,000 --> 00:35:04,860 And it helps to just talk to someone else, bring in another person. 540 00:35:04,860 --> 00:35:09,520 That's what we did is we just like looked at your record, try and see, have someone 541 00:35:09,520 --> 00:35:11,920 else tell you what they see. 542 00:35:11,920 --> 00:35:16,040 And be like, oh, that is actually what I do, but I've never said it. 543 00:35:16,040 --> 00:35:17,040 You know? 544 00:35:17,040 --> 00:35:18,040 Right. 545 00:35:18,040 --> 00:35:19,040 Never thought about it that way. 546 00:35:19,040 --> 00:35:20,040 Yeah, it's right. 547 00:35:20,040 --> 00:35:21,040 It's true. 548 00:35:21,040 --> 00:35:24,920 It's so helpful to talk to someone else like you, the expert about how to do that. 549 00:35:24,920 --> 00:35:26,840 You touched a little bit on social media. 550 00:35:26,840 --> 00:35:31,280 What should people be thinking about in terms of representing their work that's highlighted 551 00:35:31,280 --> 00:35:32,280 on social media? 552 00:35:32,280 --> 00:35:35,680 Yeah, for me, I would say don't focus on it. 553 00:35:35,680 --> 00:35:38,180 Don't waste a lot of time on social media. 554 00:35:38,180 --> 00:35:43,800 But do have a presence in terms of like a website that if someone Googles you, that's 555 00:35:43,800 --> 00:35:47,880 coming up early enough if that's something that matters to you. 556 00:35:47,880 --> 00:35:54,800 But honestly, social media, I find it even now to still be very transitory of what is 557 00:35:54,800 --> 00:35:55,800 findable. 558 00:35:55,800 --> 00:35:58,360 And for me as a librarian, it's hard to search. 559 00:35:58,360 --> 00:35:59,720 It's hard for people to find you. 560 00:35:59,720 --> 00:36:03,480 It's hard to find things that are like stable places. 561 00:36:03,480 --> 00:36:06,720 So focus your energy on stable things. 562 00:36:06,720 --> 00:36:11,800 Stable, a stable website that you can then, you know, post in your stories as much as 563 00:36:11,800 --> 00:36:14,640 you want, but it has a stable page that it links to. 564 00:36:14,640 --> 00:36:19,320 So that's kind of the strategy that I recommend for folks who want to use social media or 565 00:36:19,320 --> 00:36:24,040 want to use a more, you know, ephemeral is typically the word that I would use to describe 566 00:36:24,040 --> 00:36:30,080 ephemeral form of media to communicate their research is to focus on a stable backbone, 567 00:36:30,080 --> 00:36:35,560 something that you can actually take a screenshot of and find to provide to, you know, as proof 568 00:36:35,560 --> 00:36:41,640 of something versus a TikTok video that you lost in your past somewhere, which is fine. 569 00:36:41,640 --> 00:36:44,600 If you become TikTok famous and get tenure off of that, I support it. 570 00:36:44,600 --> 00:36:48,320 So that is a good way to communicate information if it's good information. 571 00:36:48,320 --> 00:36:50,960 But that's what you're battling with. 572 00:36:50,960 --> 00:36:52,280 No, that's really good. 573 00:36:52,280 --> 00:36:53,280 That's really good. 574 00:36:53,280 --> 00:36:58,640 And when you create your narrative, that people can find the evidence that supports the narrative 575 00:36:58,640 --> 00:36:59,640 as well. 576 00:36:59,640 --> 00:37:00,640 I love it. 577 00:37:00,640 --> 00:37:01,640 Okay. 578 00:37:01,640 --> 00:37:03,360 So we are coming to the end of our podcast episode. 579 00:37:03,360 --> 00:37:05,920 We've talked about so many golden nuggets. 580 00:37:05,920 --> 00:37:11,760 I wonder, is there anything that's left unsaid that you want to share with our audience? 581 00:37:11,760 --> 00:37:15,480 Really just do your research and keep track of it. 582 00:37:15,480 --> 00:37:16,600 Do your research. 583 00:37:16,600 --> 00:37:22,560 Don't, don't be swayed by what, you know, the journal wants you to do. 584 00:37:22,560 --> 00:37:27,080 Don't be swayed by what your institution says is the most important. 585 00:37:27,080 --> 00:37:30,360 Obviously those, those voices are important, but serve your community. 586 00:37:30,360 --> 00:37:32,280 Serve that, do your research. 587 00:37:32,280 --> 00:37:36,280 And there is a narrative and there is a metric and there is a way to communicate it. 588 00:37:36,280 --> 00:37:41,440 You just might need to talk to an additional person to find it, but don't, don't be swayed 589 00:37:41,440 --> 00:37:44,640 by low H index by low journal impact factor. 590 00:37:44,640 --> 00:37:49,640 It's just an arbitrary number that a white man made up like 30 years ago. 591 00:37:49,640 --> 00:37:53,120 It does not matter ultimately, and think of it that way. 592 00:37:53,120 --> 00:37:55,760 Like do your research. 593 00:37:55,760 --> 00:37:56,760 Thank you, Beth. 594 00:37:56,760 --> 00:38:00,320 It's music to my ears because it's one of the things I talk about where it's like, you 595 00:38:00,320 --> 00:38:03,000 could spend your time worrying about what everybody thinks about you. 596 00:38:03,000 --> 00:38:06,680 And you will always still find the people who are not impressed, or you could just focus 597 00:38:06,680 --> 00:38:11,360 on work that creates impact, knowing that you are serving communities that care about 598 00:38:11,360 --> 00:38:12,960 the work you do. 599 00:38:12,960 --> 00:38:18,160 And, and then find a way to tell the story in a way that, that makes sense to you and 600 00:38:18,160 --> 00:38:19,720 that people can understand. 601 00:38:19,720 --> 00:38:20,840 So I appreciate that. 602 00:38:20,840 --> 00:38:21,840 Thank you. 603 00:38:21,840 --> 00:38:22,840 Yeah. 604 00:38:22,840 --> 00:38:23,840 Thanks so much for letting me share. 605 00:38:23,840 --> 00:38:28,080 Cause I feel like we speak on deaf ears a lot of time when we're talking to admins, but 606 00:38:28,080 --> 00:38:30,360 you know, I'll just keep yelling at them. 607 00:38:30,360 --> 00:38:31,360 It's fine. 608 00:38:31,360 --> 00:38:32,360 No, no, no, it's great. 609 00:38:32,360 --> 00:38:37,080 I think you are part of the revolution and it's an important revolution because what 610 00:38:37,080 --> 00:38:38,080 are we about? 611 00:38:38,080 --> 00:38:41,920 Are we about creating good work that, that changes people's lives? 612 00:38:41,920 --> 00:38:46,160 Or are we about just pretending to do that? 613 00:38:46,160 --> 00:38:52,640 And wouldn't it be great to be able to change lives and also be able to demonstrate how 614 00:38:52,640 --> 00:38:56,760 it's impactful by the numbers, but just because you can't do that, doesn't mean you cannot 615 00:38:56,760 --> 00:39:00,000 create a narrative that shows the work you've done. 616 00:39:00,000 --> 00:39:01,000 Exactly. 617 00:39:01,000 --> 00:39:04,160 Well, Beth, it's been such a pleasure having you on the show. 618 00:39:04,160 --> 00:39:06,240 Thank you so much for being here. 619 00:39:06,240 --> 00:39:07,600 Thank you so much for inviting me. 620 00:39:07,600 --> 00:39:10,640 It's always a pleasure to hang out with you. 621 00:39:10,640 --> 00:39:13,240 Well, everyone you've heard Beth, somebody needs to hear this. 622 00:39:13,240 --> 00:39:18,160 There's someone you know, who is working right now on their promotion packet and they're 623 00:39:18,160 --> 00:39:21,960 pulling out their hairs because they can't get their H index above the five. 624 00:39:21,960 --> 00:39:25,680 You need to share this episode with them so that their lives can be transformed forever. 625 00:39:25,680 --> 00:39:26,680 All right. 626 00:39:26,680 --> 00:39:27,680 Thank you for listening. 627 00:39:27,680 --> 00:39:39,400 And we look forward to listen to talking with you again on the next episode of the clinician 628 00:39:39,400 --> 00:39:40,400 researcher podcast. 629 00:39:40,400 --> 00:39:44,600 We're going to be listening to this episode of the clinician researcher podcast where 630 00:39:44,600 --> 00:39:50,080 academic clinicians learn the skills to build their own research program, whether or not 631 00:39:50,080 --> 00:39:52,040 they have a mentor. 632 00:39:52,040 --> 00:39:58,140 If you found the information in this episode to be helpful, don't keep it all to yourself. 633 00:39:58,140 --> 00:39:59,880 Someone else needs to hear it. 634 00:39:59,880 --> 00:40:03,920 So take a minute right now and share it. 635 00:40:03,920 --> 00:40:09,400 As you share this episode, you become part of our mission to help launch a new generation 636 00:40:09,400 --> 00:40:15,360 of clinician researchers who make transformative discoveries that change the way we do healthcare.