Welcome to the Clinician Researcher podcast, where academic clinicians learn the skills
to build their own research program, whether or not they have a mentor.
As clinicians, we spend a decade or more as trainees learning to take care of patients.
When we finally start our careers, we want to build research programs, but then we find
that our years of clinical training did not adequately prepare us to lead our research
program.
Through no fault of our own, we struggle to find mentors, and when we can't, we quit.
However, clinicians hold the keys to the greatest research breakthroughs.
For this reason, the Clinician Researcher podcast exists to give academic clinicians
the tools to build their own research program, whether or not they have a mentor.
Now introducing your host, Toyosi Onwuemene.
All right, everybody.
Welcome to the Clinician Researcher podcast.
I'm Toyosi Onwuemene, your host.
I'm so excited to be here today.
I have a really special guest, Beth Blockwood.
Beth, welcome to the show.
Yeah.
Thank you so much for having me.
Beth, so I want to call you a librarian, but I'm not sure that's the right technical term.
Could you introduce yourself to our audience, what you do, and what makes you so special?
Yeah, absolutely.
So my name is Beth Blockwood, and I am technically the research and education librarian here
at Duke Medical Center Library and Archives.
So librarian is in my job title, but I specialize in kind of a new area of librarianship that
Duke and a few other institutions have kind of invested a lot of time and effort into,
but there's not very many of us yet.
And I am specifically a librarian who works on research impact and bibliometrics.
So I specialize in what some might call the science of science, measuring what that kind
of meta space is for how we measure what has been studied, what hasn't been studied, who
is researching and writing about specific things, and who might not be showing up in
that literature.
A lot of that kind of looks like doing reporting and measuring things for administrators, but
a lot of it can also be more novel questions that have to do with who is in what publishing
space, what kind of communities are actually reading and accessing the information that
people are publishing.
So it's a new kind of nebulous field in librarianship, but ultimately it is about how and who is
accessing information, which I love and I think is true librarianship.
It's just kind of that next meta level of it.
Absolutely.
And one of the things you don't add to your title, Beth, is that you're a life changer.
So for the audience, I first met Beth a couple of, gosh, maybe a few months ago now when
I was putting my materials together for a promotion and Beth, I asked Beth, well, someone
actually referred to Beth and said, you just talked to Beth about how to measure your impact.
And so I sat down with Beth and Beth really transformed my experience because after talking
to Beth, I was like, oh, now I know what to write about and how to really represent my
impact in a way that was just beyond just the H index.
So that's what I want to talk about today because Beth, we're all trying to make an
impact in our field and we would be making an impact anyway, but then all of a sudden
we live in the background of people saying, well, let's measure your impact.
What's your H index?
And beyond the H index, many of us don't know how else to measure our impact.
So I'd like to just start there.
Tell me about the H index.
Why it's so, I guess, powerful and important.
What are the limitations and how else can we think about measuring impact?
Absolutely.
And this is one of my favorite topics to talk about because it is nuanced.
The H index, journal impact factor, a lot of these metrics that we hear tossed around
all the time are very specific measurements that measure extremely small aspects of a
particular scholar, of a particular journal, and of the readership of a particular scholar
or journal.
For example, H index is a measure really of productivity, theoretically, productivity
in terms of what we are told is productive by truly publishers and corporate America
and the folks who are making a lot of money off of publications of materials.
And they're usually making that money off of libraries.
So I will put that plug in there.
They're not our favorite folks in the library world.
But an H index is supposed to measure a scholar's amount of publications by how many citations
they get.
So that formula more or less is the number of publications that they have and the highest
cited paper that they've published.
So if a person has 46 papers that they've published and their highest cited paper has
been cited 13 times and they have 13 papers that have been cited 13 times, then their
H index is 13.
Even though they've published 36, 46, however many papers, unlimited number of papers, it's
a way to show that they are both impactful, people are reading them, and they're also
productive.
But if I just gave you that number, you wouldn't know anything about that person.
You wouldn't know whether they study a rare disease.
Because guess what?
People who study rare diseases do not get cited as often as people who study very, very
popular or very well studied or very highly prominent diseases, things that lots of people
have, lots of people talk about, and lots of people fund.
So that already creates a very interesting problem for researchers who are helping and
studying and working with communities that might not be as popularly funded or might
not have a lot of people reading about it.
So those are the types of things that an H index does not take into effect.
It also doesn't tell you anything about where a researcher is in their career.
If you have a new researcher, someone who's new to the field, someone who may be very,
very prominent in their particular fellowship, someone who's going to be a star, whatever
you want to say, they probably don't have a high H index because they have not been
on the planet long enough to have accumulated tons and tons of citations and funding and
things that really help increase those normal traditional metrics.
So it's really important to look at the whole scholar.
An H index means very little if someone is working in something outside of the traditional
norm or working really hard to make sure that the people and the populations that they study
can actually access that information.
So those are some things I can get into if we talk about journal impact factor, but I
often see the folks who have dedicated their lives to truly helping communities, truly
helping the folks that their research, the actual populations that they study and their
research is a part of often don't have the highest H indexes, but are making the biggest
impact within those communities.
And there are other ways to communicate that kind of information.
Thank you, Beth.
So I love how you talk about just the disparities really that exist in how people's work is
showcased or how it's cited.
And yeah, so I was thinking as you were talking, I was like, maybe if I'm a cardiologist studying
coronary artery disease, surely you'll probably get a lot more citations as opposed to those
of us who are in the rare disease space where, to be honest, not that many people are interested
in reading our work.
But then, okay, so if not the H index, what are other metrics to demonstrate our impact?
Yeah, honestly, traditional metrics are never going to be my favorite way to present anything.
But I think if you are in a space where traditional metrics are required, which a lot of us are,
if you receive NIH funding, if you're trying to receive federal funding in any way, if
you are in a very traditional tenure APT kind of process, sometimes you do have to include
those metrics.
But the important thing to do is include the narrative around it.
Keep your narrative to reflect why you have a low or H index.
And you can specifically point to the fact that, hey, the journals that I publish in
are open access.
They might not necessarily be in a mainline database like Scopus or Web of Science where
people will find and cite those papers.
And the reason that they may not be found there, and the reason that I try not to publish
there would be because people have to pay to subscribe to those places.
And if the research that I am working on is maybe for people who live in rural communities,
the hospitals in those rural communities are not going to have access to those publications
unless they are open access on PubMed Central or whatever other means that you have to provide.
That's part of a narrative that you could say, hey, it's intentional that I did this.
The important thing to note is that these are factors that folks actually look and care
about.
And I think that's kind of the secret that a lot of administrators don't necessarily
want you to know because they want to see high numbers, numbers in these top journal
impact journals, these top H indexes, these top kind of performing metrics that a lot
of folks translate.
These metrics that can translate across a lot of different communities, a lot of different
academic spheres.
But they know these things as well, and they work, and they will get you to where you need
to go.
It's just making sure that the researchers are able to communicate that.
And I think that's one of the biggest challenges that we face in scholarly communication and
scientific communication is recognizing all the ways that our information is disseminated
in a way that actually does help the population.
Because ultimately, why are we here?
Except to help the populations that we're there for.
I love it, Beth.
Thank you so much.
You bring hope.
I try.
Okay.
So one of the things that I hear you talking about is owning your narrative.
And so it's like, what story, actually, it's funny.
You said, this is what I intentionally did.
Some of us didn't intentionally do anything.
We just ended up here and we're like, oh, now I have to tell the story.
But it's how do you shape the narrative in a way that highlights your work in its best
light?
And if you have an age index, that's great, but it's not...
You can't just rely on that and say, well, I have a high age index, therefore my work
speaks for itself.
But how do you even shape the narrative around that high age index?
And if you don't have a high age index, how do you shape the narrative around what you
do not have?
But not with a focus on what you don't have, but with a focus on the impact of your work
and the communities that it reaches out to.
And so one of the things I want to speak to, so when I sat down with you, you talked about
my collaborations with international collaborators.
You talked about some of my work being cited in the top 25% of journals by site score.
That was all news to me.
Can you talk to me about how we can find some of these non-traditional metrics in a way
that helps us spin the narrative about our work?
Absolutely.
And my favorite metric, if we were going to talk about a concrete metric, my favorite
one and the one that I encourage authors to utilize as much as possible is the journal
quartile, which is really where your journal that you published in falls within a normalized
category that you publish in.
So if you publish in rare diseases, your journal that you publish in is going to be grouped
in a category with other rare diseases that it is similar to.
So it is what we call a field normalized category.
And that can often really show you where you are truly in a way that will communicate better
to the folks who need to hear it.
So this is talking specifically about journal impact factor now.
So this is a metric that a lot of people don't love because we're comparing apples and oranges
a lot of times with this.
When we're looking at an impact factor of a journal, it's comparing review articles
with RCTs, with editorials.
These are all things that are citable material within a journal, but we're kind of comparing
them all, which as a person interested in data, I think that is a questionable way to
go about things, but it is where we are.
But the quartile is the way that a lot of journals try and solve for this issue by comparing
things, apples and apples.
So like we mentioned earlier, you would never compare a cardiologist's publishing history
to someone who studies rural health.
And just specifically though, there may be overlap there.
Like a community health journal would not be in the same category as someone who studies
like thoracic surgery or anything like that, because the populations who are reading those
journals are very different.
Their publication, the people who cite them are very different.
So what I would recommend for someone who looks and sees, oh, I don't publish in high
impact journals and I don't publish enough to have a high H index in the same like traditional
way.
I would really recommend that person look at their publishing history and look for patterns.
Am I publishing in journals that reach a certain population?
Am I publishing in open access journals?
Am I publishing in journals that are around a particular theme?
What is that theme?
And how can I communicate that theme to my reviewers, to anyone who is trying to judge
me by these metrics or whatever it is.
And there are arguments that you can make about those journals.
One of the best things that I like to show for this is if you're publishing about a marginalized
population and you don't have high citations on your articles, it's probably because the
journals that are citing you are not necessarily indexed in a database like Scopus or a database
like Web of Science.
And the free databases do not show you your citation.
There's a reason for that.
So if you look at PubMed, PubMed is what we utilize for everything.
PubMed is how we find the majority of information and it's how the world finds the majority
of information.
It's a huge, huge, openly accessible database, which is why ChatGPT trains the majority of
their algorithm, of their large language model off of PubMed because it's freely available.
And a big point to make from that is it doesn't have citations because it doesn't know who
cites anyone.
It doesn't track that.
It doesn't index.
It doesn't read.
It doesn't care about those types of things for a reason.
It's impossible to track all of those things.
So it's important to look back and say, okay, if I am publishing in a rural health journal,
who is citing me?
Probably not someone who's indexing and getting a big name journal to publish in one of these
major databases.
So who are they?
Go find them.
You can use Google Scholar for that type of metric.
You can also provide presentations.
You can provide your additional outside kind of content.
Your presentations that you give at the rural hospital.
The conference proceedings that you give or teaching the teaching that you do to train
doctors in these rural places.
Whatever the example is, there are narratives that you can pull in to say like, yeah, I'm
not getting citations because the folks who read my papers don't publish.
They're doctors.
Those are some of the ways that I think are really interesting to start to provide a more
nuanced picture of yourself.
Another great example.
I love this group.
I can't talk about, I'm not going to name what group they are.
They ever listen to this podcast.
We'll know who they are.
So y'all are my favorite, but I have a rogue group of physicians who are very against using
any type of metrics to describe their work.
And some of the ways that they've been really interested to show true impact is to find
their citations in up to date and actually go and see, okay, am I actually being used?
Are the publications that I write actually making it to physicians who are treating patients?
Cause that's where you would look.
I did almost, well, I did, it's not an almost, I did violate my terms and conditions on my
up to date license to try and scrape it and find those, find those citations, but that's
for a different story.
I still work here, so it's fine.
No one was fired in the making of that story.
Another way that this group is working to find ways to show other impact outside of
citations outside of H index, outside of journal impact factor is to see their citations and
consensus papers and actually go and see are people working with the research that I do?
Is the research that I do impacting the field?
And those are some measures that to me, if I saw that cited, if I saw that communicated
in a narrative, it would mean more to me than just a random publication in a random journal
that may or may not have been deeply well done.
It speaks nothing to the quality of a paper.
If it's included in a journal, it speaks a lot to the quality of the paper.
If it's included in a consensus paper or something along those lines.
Thank you, Beth.
And I remember one of the things we did was look at some of my articles and look to see
how many of these guidelines papers had actually cited my papers, which then allowed me to
make the narrative of, you know, or to create a narrative of, well, my work is foundational
such that these guidelines are citing my work.
I mean, it's foundational.
That's what I want to hear every time with the folks that I work with.
And that's how you prove it.
I mean, and it's beautiful.
It's really, really great to think outside of that box.
Now, there's one thing you mentioned that I want to go back and kind of try to address,
because when you look at your work, saying Google scholar, you find a certain age index
or certain number of citations as opposed to when you go to a place like Scopus.
And then actually looking at my work, I have fewer citations than Scopus compared to Google
scholar.
What's the difference between the two?
Great question.
So Google scholar, Google versus Elsevier, it's big evil company versus big evil company.
It's, you know, elitist, one elitist institution, you know, like counting citations and other
elitist things versus a what I would refer to as a very opaque system.
So in something like Scopus or Web of Science, we know exactly what is being counted.
They have specific journals that they will actively tell you these are what we've indexed.
So if you're cited in anywhere in these journals that we look at, we're going to count it and
it'll count toward our numbers.
Google scholar opaque.
We don't know what it's counting.
We know that it's probably counting the same things and then some.
One of the biggest kind of inflators of Google scholar numbers, Google scholar numbers tend
to be higher, which is why people love them.
I don't I don't blame them.
We want to make it look as high as possible.
But it does tend to be more inflated than other locations because it often will double
count your open access papers and it will often count an index of something that's in
PubMed Central with an index of something that's in Scopus.
So sometimes you'll get, you know, four or five points higher if it says that you have
higher papers.
So if it said if it counts that you have, you know, that same paper that's living in
two locations, that same paper that's living in research gate, that's also in PubMed Central,
that's also on the journals website that will sometimes inflate your numbers a little bit,
which is often why people put their papers in these locations because they know that
and that's the other kind of area that I like to discuss with Google is that folks who have
the time to game it can't.
That's the big thing to know is that folks who have the time to spend, you know, a lot
of effort making sure that their papers link out to specific places, making sure that their
citations are perhaps double counting, they succeed in that environment.
It's a little more gameable than something like Scopus or Web of Science.
So those are the kind of how you weigh that situation of one evil company versus another
evil company versus one that is a little bit more elitist and kind of locked down of who
can count what, what counts and what doesn't versus one that is gameable by folks who have
the capacity, the time, the energy to do something and the knowledge, truly the knowledge to
do that kind of work.
Wow.
This is how you know you're talking to the expert when she can tell you how to game the
system and I hope, you know, but I, you know, it's interesting.
People do it, right?
So it's kind of like, I don't know that it's an open secret, but it's, it's, people do
it and if you want to look up how to do it, you can, but I think that the real issue is
how do you, how do you present your work in a way that honors the work you've done, honors
the communities you served without trying to play a game because at the end of the day,
it's not, it's not worth it.
At least I think so.
Totally agree.
It's a capitalist system, so it's always going to be a game.
It just depends on, you know, how much time, energy and funding do you have to play that
game?
Sure.
No really good points, really good points.
Okay.
So we've been talking about from the perspective of the investigator demonstrating their impact.
One of the things you also do is you help institutions understand the impact of their
investigators.
Tell me a little bit about that.
Yeah.
So my August through October is absolutely slammed with end of fiscal year reports providing
large data sets of publication data that I'll either add information to, to make a whole
piece, a whole presentable data set about a particular department.
So I will again, not say any department names or Institute names, but usually it's a particular
division, a particular department or an Institute at our, at Duke, where they would request
in, you know, July, August, we're going to have X meeting or do X report in October and
we'll need to know every publication that our department has done in the last year,
how it's been cited and what journal, what journal and what impact the journal was.
So, and I would say that, you know, I wish that the whole journal impact kind of that,
that factor of it was starting to like lose its, its sting and lose its popularity, but
it really hasn't.
I would say that almost every, every department that I work with does act, ask for me to add
impact factor into the data sets that I provide.
So every year, every single year they get a lecture from me where I tell them, recognize
that if you are, if you have any researchers who are working in rare disease spaces, this
is not going to be an accurate metric for them.
Also recognize that if you have any new journals or folks who are publishing in novel fields
or doing novel research, this is not going to be an, an accurate rating or an accurate
measurement for them.
And so whether they ask for it or not, I always include the core tile, which will tell them
where they fall within that, their specific field.
And I personally try to provide data visualizations or ways that I can communicate what a core
tile is about their department kind of automatically.
Most of them don't ask for that, but I provide it anyway.
And it does tend to make its way into their reports, does tend to make it into their kind
of like larger meetings where they're presenting and they're like, Oh, we have a visualization
that's already made.
Thank you, librarian for doing that.
And that's how I kind of sneak in the value of more normalized fields.
Granted, I do have some departments that will actually normalize for fields.
So I have folks who, if you're familiar with the population health department at Duke,
it's fairly new.
It's a fairly young department and a lot of the journals that they work in are very interdisciplinary.
So those tend to have much lower journal impact factors because they're newer.
They're not, they haven't been as round as long.
They haven't built up the following.
And honestly, libraries haven't purchased as many of their subscriptions just because
they're so new and people don't request them quite as much as guess what?
Community health doesn't have as much money as others.
Shock.
We're all surprised by that.
So I've worked with a couple of departments that now are institutes here that have interdisciplinary
groups to actually lower what they consider a high impact journal for particular fields,
which does go a long way to making that impact actually more normalized where we have journals
like science, nature that have impact factors in the nineties, over a hundred points, things
like that.
And then we have folks in population health.
That'll be the top Q1 journal in all of population health that has a one or a two.
And that's the highest, that's the highest journal.
So I apologize.
All right.
Thank you so much.
Gosh, you know, Beth, I almost feel as if so.
So from what you're telling me, you're like the, the, the undercover crusader working
so hard to, to make sure that people are valuing the work of investigators well, whether that
is investigators valuing their own work, but also departments valuing the work of their
investigators, their faculty.
So thank you for the work that you do.
I'm curious about the visualization.
How can faculty for themselves create their own visual representation of the kind of work
that they've done and their impact?
Absolutely.
First, I'll shout out our library resources, both here at the medical center library and
at our main campus library.
And if you're a researcher listening anywhere that has access to a medical or university
library, I guarantee that they have workshops that they're teaching to show researchers,
faculty, including sending your, your researchers, your postdocs there to go learn it for you,
how to use a variety of different tools that are available to actually communicate that
data.
Of course, some of the easiest tools that you have, I'm sure anyone would have access
to it in Google sheets.
In Excel, you can make a graph, you can make a table, but the benefit of actually providing
an image for someone who's trying to communicate a point is it's easy.
It's easy.
Someone can read it.
Someone doesn't have to spend a lot of time interpreting it.
They can look quickly at a bar chart and say, all right, Q4, that's the lowest, Q1, that's
the highest, Q1 is gray, Q1, Q4 is this.
And I can see that we have a lot of Q1 journals that just might not have super high impact
factors.
It's so easy to, for me to make those in like 30 seconds over data that someone from a particular
department has provided that will end up somewhere.
It's just taking a little time, you know, a minute and a half of my time that will take
a minute and a half off of that poor administrator or that poor coordinator who's making those
slides who's already slammed and be like, it'll sneak in there.
But for a researcher, we all know the value of data visualization in the way that we publish
and how we communicate things, how, you know, color can make someone feel a certain way
or a bar or a pie chart can be sometimes pretty racist if we use it badly.
There are all kinds of ways that we can learn how to use data visualizations in an ethical
way and to share our own narrative.
One example of this might be if you're demonstrating your own research is making a simple bar chart
of how you publish and what journals you publish in.
How many are open access?
If you have a pie chart of everything that you've published and 90% of that is open access,
that communicates a lot.
Just to say like, oh, pretty much everything I do is openly accessible to all of the folks
that I work with.
Or you want to say that all of everything that I publish is a Q1 journal.
It's just not a high impact factor.
Those are really easy ways to show something that someone will look at lightly and immediately
understand without having to read deeply through, oh, I published here and here and here and
here and this is what this is and this is and this is.
It's a quick, you immediately know.
And we all know that people who are reviewing us, whether they're, you know, program officers
at the NIH or they're administrative, like faculty that, you know, are administrators
and faculty members that are granting us tenure, they're the folks who have the least amount
of time to look at these things and delve deeply into them.
So let's make it easy on them.
Oh, it's really good.
It's really good.
Let's just take a little bit of effort and make something that makes it easy for someone
to understand your impact.
I love it.
Okay.
If you could speculate on the perfect score, how to create the perfect score, or maybe
not so much score as metric or maybe it's not a score.
What would you recommend?
Kind of looking at the whole landscape.
How would you recommend we do this?
Because the whole purpose, right, is to compare one investigator to another.
But what we're really doing as you, as you highlighted, is comparing apples to oranges
and then feeling good about ourselves, but not really doing a good job.
How should institutions be thinking about evaluating kind of the impact of the work
their investigators are doing?
Yeah.
From the institutional level, it's look for that narrative.
Look and see who the person is and look at who the population they work with, who can
access their work.
It's awesome if, you know, they're published in Nature, but if nobody reading Nature gets
anything out of it, if nobody reading Nature actually cares about this particular rare
disease and is going to use it, is it used?
So I think the real clutch part for any person who is going up for review, who's trying to
make their narrative, who's trying to actually communicate what they're doing is to look
at where they're being cited at the population level, whether that is rural hospitals newsletter
and just citing that, whether it's on ABC and you're actually getting written up in
a news story that's communicated in the morning news, whether it is in somebody's podcast
that is actually being listened to, you know, like these are the things where you actually
are communicating that research.
Those are some more like altmetrics that we always talk about altmetrics, these additional
kind of things.
Like it used to be very popular to say that your altmetrics were on Twitter, but now I
have to like look for other things because our library no longer supports Twitter slash
formerly known as Twitter X now formerly known as Twitter and whatever that is.
There are lots of ways that you can measure how things have been seen outside of these
traditional narratives and it doesn't have to be something fancy like a documentary or
you know, you were seen on, you got an NPR story about you like awesome.
That would be awesome if you had an NPR story about you.
I'm not going to say it's not awesome, but like getting written up in like a local journal
that actually reaches folks who, who need it, I think is the most important.
I have a good colleague.
I used to be an environmental science librarian and I have a colleague who studies beavers
and fire prevention, which is so random, but you know, she never dedicated her time to
actually publishing in these major major journals because she was actually trying to make an
impact on like California policy, which has like all these regulations about where a beaver
can be and not be and it's right.
Like anyway, it doesn't matter, but that was where she focused her actual goals and her
communication.
So she published in local journals.
She published and wrote at major conferences that were just statewide.
It didn't matter to her so much about these bigger, like, you know, bigger journals that
might matter to someone who's trying to like climb a ladder, which is all fine.
I'm not saying there's anything wrong climbing the ladder.
It's important.
We need good people at the top of the ladder too.
But that was kind of her goal.
And so her major representation in her tenure package was speaking on the state floor, the
house floor at like the California, one of the state Senate meetings, because she had
worked her way up to being able to provide her testimony and give expert testimony in
that level.
And she did get tenure off of that.
And she did get a lot of praise and kind of accolade for that.
But that's what I'm talking about with a narrative is like, it would be awesome if we all publish
in nature, if we all publish in these big journals, we all are in JAMA.
Everybody's so proud of us.
But that narrative of I did X, Y, and Z to scaffold to this goal, which forwards my research,
that is a narrative that you would give someone tenure for, in my opinion.
I love it.
It's individualizing the process.
It's easier.
It's easier for us to just pick a number and not have to do any work.
But really it's saying it's doing the work.
It's the investigators doing the work of representing their work well.
And this institution is not trying to put everybody in a one size fits all box.
And just make it easy for that reader, for the person who's judging you to easily follow
that narrative.
Dare I say it might be writing skills, which is scary to have to say, but good writing
skills, good communication in that sense, but also just paying attention and looking
for patterns in where you've published.
Even if you are like, I have no idea how I got here.
I don't really know who I talked to.
But it's a pattern.
There'll be some type of pattern that you can pull.
And it helps to just talk to someone else, bring in another person.
That's what we did is we just like looked at your record, try and see, have someone
else tell you what they see.
And be like, oh, that is actually what I do, but I've never said it.
You know?
Right.
Never thought about it that way.
Yeah, it's right.
It's true.
It's so helpful to talk to someone else like you, the expert about how to do that.
You touched a little bit on social media.
What should people be thinking about in terms of representing their work that's highlighted
on social media?
Yeah, for me, I would say don't focus on it.
Don't waste a lot of time on social media.
But do have a presence in terms of like a website that if someone Googles you, that's
coming up early enough if that's something that matters to you.
But honestly, social media, I find it even now to still be very transitory of what is
findable.
And for me as a librarian, it's hard to search.
It's hard for people to find you.
It's hard to find things that are like stable places.
So focus your energy on stable things.
Stable, a stable website that you can then, you know, post in your stories as much as
you want, but it has a stable page that it links to.
So that's kind of the strategy that I recommend for folks who want to use social media or
want to use a more, you know, ephemeral is typically the word that I would use to describe
ephemeral form of media to communicate their research is to focus on a stable backbone,
something that you can actually take a screenshot of and find to provide to, you know, as proof
of something versus a TikTok video that you lost in your past somewhere, which is fine.
If you become TikTok famous and get tenure off of that, I support it.
So that is a good way to communicate information if it's good information.
But that's what you're battling with.
No, that's really good.
That's really good.
And when you create your narrative, that people can find the evidence that supports the narrative
as well.
I love it.
Okay.
So we are coming to the end of our podcast episode.
We've talked about so many golden nuggets.
I wonder, is there anything that's left unsaid that you want to share with our audience?
Really just do your research and keep track of it.
Do your research.
Don't, don't be swayed by what, you know, the journal wants you to do.
Don't be swayed by what your institution says is the most important.
Obviously those, those voices are important, but serve your community.
Serve that, do your research.
And there is a narrative and there is a metric and there is a way to communicate it.
You just might need to talk to an additional person to find it, but don't, don't be swayed
by low H index by low journal impact factor.
It's just an arbitrary number that a white man made up like 30 years ago.
It does not matter ultimately, and think of it that way.
Like do your research.
Thank you, Beth.
It's music to my ears because it's one of the things I talk about where it's like, you
could spend your time worrying about what everybody thinks about you.
And you will always still find the people who are not impressed, or you could just focus
on work that creates impact, knowing that you are serving communities that care about
the work you do.
And, and then find a way to tell the story in a way that, that makes sense to you and
that people can understand.
So I appreciate that.
Thank you.
Yeah.
Thanks so much for letting me share.
Cause I feel like we speak on deaf ears a lot of time when we're talking to admins, but
you know, I'll just keep yelling at them.
It's fine.
No, no, no, it's great.
I think you are part of the revolution and it's an important revolution because what
are we about?
Are we about creating good work that, that changes people's lives?
Or are we about just pretending to do that?
And wouldn't it be great to be able to change lives and also be able to demonstrate how
it's impactful by the numbers, but just because you can't do that, doesn't mean you cannot
create a narrative that shows the work you've done.
Exactly.
Well, Beth, it's been such a pleasure having you on the show.
Thank you so much for being here.
Thank you so much for inviting me.
It's always a pleasure to hang out with you.
Well, everyone you've heard Beth, somebody needs to hear this.
There's someone you know, who is working right now on their promotion packet and they're
pulling out their hairs because they can't get their H index above the five.
You need to share this episode with them so that their lives can be transformed forever.
All right.
Thank you for listening.
And we look forward to listen to talking with you again on the next episode of the clinician
researcher podcast.
We're going to be listening to this episode of the clinician researcher podcast where
academic clinicians learn the skills to build their own research program, whether or not
they have a mentor.
If you found the information in this episode to be helpful, don't keep it all to yourself.
Someone else needs to hear it.
So take a minute right now and share it.
As you share this episode, you become part of our mission to help launch a new generation
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