Journey Lecture Donna Spiegelman

Transcript

• 00:00Alright. I think we are
• 00:01going to get started.
• 00:04Welcome everyone
• 00:05to the second journey lecture
• 00:07of this very special
• 00:09series of journey lectures that
• 00:11we have introduced
• 00:12as a part of the
• 00:14data science, data equity initiative
• 00:16at the Yale School of
• 00:17Public Health. And welcome everyone,
• 00:20this afternoon.
• 00:21And, it's my honor and
• 00:22pleasure that my dear colleague
• 00:24and much admired friend,
• 00:26professor Donna Spiegelman has actually
• 00:29agreed to do the journey
• 00:30lecture. And I'm gonna tell
• 00:31you a little bit about,
• 00:33the history of this journey
• 00:34lecture, but also while I
• 00:36have the podium, say a
• 00:38little bit about data science
• 00:39and data equity.
• 00:40And so this is a
• 00:41initiative that we launched about
• 00:43six months ago.
• 00:45And after eighteen years at
• 00:46the great institution of the
• 00:48University of Michigan, I moved
• 00:49to another great institution,
• 00:51at Yale. And I'm really
• 00:53thankful to people in the
• 00:55room who has made the
• 00:56transition possible and very, very
• 00:58enjoyable and welcoming.
• 01:00But as a group, what
• 01:02is our broader goal? Our
• 01:04broader goal is to make
• 01:05data science knowledge,
• 01:07tools, and resources available to
• 01:08communities
• 01:09near and far,
• 01:11promoting equitable scientific discoveries,
• 01:14policy decisions,
• 01:15public health practice, and health
• 01:17care.
• 01:18And I care as I
• 01:19look at this vision statement,
• 01:21I cannot think of a
• 01:22better person than professor Spiegelman
• 01:24who has embodied almost
• 01:27all of it. Data science
• 01:28knowledge, resources, tools, communities near
• 01:31and far,
• 01:32discoveries, public health practice,
• 01:34and decisions and policy making.
• 01:38So with
• 01:39that, how does this data
• 01:40science and data equity,
• 01:43weave into the SPH
• 01:45strategic vision of linking science
• 01:47to society?
• 01:49It's pillar four, shaping the
• 01:51future of public health data
• 01:53science and AI.
• 01:54And you have four pillars
• 01:56essentially to build infrastructure,
• 01:58to do educational programming,
• 02:01as well as really think
• 02:02about what is data. Data
• 02:04as a dialogue, as a
• 02:06discourse in terms of privacy,
• 02:08security,
• 02:09and practice data science with
• 02:11a touch of ethics, equity,
• 02:13and humanism.
• 02:15And we definitely want to
• 02:16create robust domestic and international
• 02:18partnerships on public health data
• 02:20science. And, again, Donna's work
• 02:23actually encompasses
• 02:24all of these initiatives and
• 02:26the strategic
• 02:27plan.
• 02:28So
• 02:29as,
• 02:31I'm I'm going to hand
• 02:32it the hand over the
• 02:33floor soon to,
• 02:34Melody who is going to
• 02:36introduce Donna formally.
• 02:38But as I said, journey
• 02:39lectures are nontechnical
• 02:41lectures talking about people's lives.
• 02:43And as Jeff told me,
• 02:45the previous journey lecturer,
• 02:47and Donna told me that
• 02:49it is incredibly
• 02:50hard to stand up for
• 02:52an academic and talk about
• 02:54non academic part of your
• 02:55life. We are not trained
• 02:57to do that.
• 02:58But to add a touch
• 02:59of fun, we have added
• 03:01a snack.
• 03:02So for Jeff, when he
• 03:03sent,
• 03:05I really did not understand.
• 03:07You know, I grew up
• 03:07in India.
• 03:08And so I had to
• 03:10Google. And, actually, I asked
• 03:11GPT and good old reason
• 03:13and pin it, and then
• 03:15Donna upgraded us to a
• 03:17bit more.
• 03:18And so,
• 03:19please help yourself to the
• 03:20locks and beagles,
• 03:21outside this room, after the
• 03:23talk.
• 03:25And then the upcoming journey
• 03:26lecture is going to be
• 03:27by another much admired colleague,
• 03:29Professor Hong Yu Zhao, on
• 03:31April nine, one to two
• 03:32pm.
• 03:33So,
• 03:35as I have the podium,
• 03:36I also want to announce
• 03:37many of us are organizing
• 03:39this conference about,
• 03:41also integrating
• 03:42local and global communities around
• 03:45data.
• 03:46Digital health equity conference,
• 03:48March four and five, it's
• 03:49going to happen in client
• 03:50fourteen. We look look forward
• 03:52to having many of you
• 03:53there.
• 03:54And then
• 03:55another Donna event, which I
• 03:57wanted to get every on
• 03:59everybody's radar.
• 04:01Believe it or not, she
• 04:02is turning seventy.
• 04:04And so we are going
• 04:05to have a one day
• 04:06birthday conference celebrating her
• 04:09pioneering work in measurement error,
• 04:11in causal inference, in clinical
• 04:13trials, and beyond, and talk
• 04:15about her journey one more
• 04:16time,
• 04:17on October third. It's a
• 04:19Friday. So please mark your
• 04:21calendars and save the date
• 04:23for that event. We are
• 04:24looking forward to that celebration,
• 04:25and we are going to
• 04:26bring back many of Donna's
• 04:28former trainees
• 04:29and the family, and so
• 04:31it is going to be
• 04:32a whole day of fun.
• 04:34With that, I am going
• 04:35to so the journey lecture
• 04:37tradition
• 04:38is sort of like a
• 04:39moment. Right? Capturing
• 04:40a moment in the journey
• 04:42of a scholar.
• 04:43And a big part of
• 04:44our scholarship is really our
• 04:46students
• 04:47and Melody,
• 04:49Owen, who is Donna's current
• 04:52trainee and doctoral student at
• 04:53Yale School of Public Health
• 04:55is going to do the
• 04:56honor
• 04:57of,
• 04:58sharing a bit about Donna
• 05:00and
• 05:01and introducing this illustrious
• 05:03statistician epidemiologist
• 05:05and,
• 05:05humanist
• 05:06to this audience.
• 05:08So let me tell you
• 05:09a little bit about Melody.
• 05:10Melody is a very accomplished
• 05:12statistician.
• 05:13She's a PhD candidate here
• 05:15at the Yale School of
• 05:16Public Health. Yay.
• 05:17And
• 05:18a really star student in
• 05:20the department of biostatistics.
• 05:22She is in the implementation
• 05:24science concentration pathway and is
• 05:26working
• 05:27under the mentorship of, Doctor.
• 05:29Spiegelman.
• 05:30Her research focuses on cluster
• 05:32randomized trials and hybrid studies.
• 05:35And includes study design methodology,
• 05:37causal inference, and software development.
• 05:40She is a former research
• 05:41statistician at many institutions,
• 05:44precision health economics and outcome
• 05:46research, where she conducted network
• 05:48meta analysis
• 05:49as a
• 05:50lead statistician.
• 05:52And also has worked as
• 05:54a lead statistician
• 05:55with many pharmaceutical companies including
• 05:58Merck, Gilead, and Pfizer.
• 06:00She earned a master's degree
• 06:01in statistics from Carnegie Mellon
• 06:03University and a double degree
• 06:05in mathematics and statistics
• 06:07from Amherst College. So if
• 06:09we can think about data
• 06:10dreaming, Melody is certainly a
• 06:13data dreamer. So with that,
• 06:14let us put our hands
• 06:16together to welcome
• 06:17Melody Owen.
• 06:23Thank you so much for
• 06:24being here today, and thank
• 06:26you, doctor Mukherjee, for that
• 06:27introduction.
• 06:28I really love the the
• 06:30spirit and setup of these
• 06:31journey lectures because as doctor
• 06:33Mukherjee mentioned, you know, in
• 06:34academia, academia, we're not really
• 06:35trained to talk about our
• 06:37personal lives and what brought
• 06:38us here. But, you know,
• 06:39academia is just one facet
• 06:41of us, and I think
• 06:42it's really important that we
• 06:43share and listen to each
• 06:44other's stories in academia. So
• 06:47in the spirit of that,
• 06:48I thought I would share
• 06:49some fun facts about me,
• 06:51which are very important. I
• 06:53am most importantly a dog
• 06:54mom.
• 06:55I am a pianist, an
• 06:56animal lover, a plant enthusiast,
• 06:59hater of cold weather, especially
• 07:01recently, as I'm sure we
• 07:03all are,
• 07:04and I am very much
• 07:05obsessed with the color pink.
• 07:07If any of you have
• 07:08gone in the CMIP's office,
• 07:09I'm sure you will be
• 07:10able to point out my
• 07:11cubicle,
• 07:12because there's a lot of
• 07:13pink there. And just because
• 07:14I try to, whenever I
• 07:15have an opportunity, show off
• 07:17my dogs, these are my
• 07:18two Italian greyhounds, Molly and
• 07:20Ziggy.
• 07:21Molly's in the pink, and
• 07:22Ziggy is in the green.
• 07:23And this was us at
• 07:24the pumpkin patch last fall.
• 07:26And, yes, I did let
• 07:27them each pick out a
• 07:27pumpkin. It was very fun.
• 07:31And so I've been at
• 07:32Yale for five years now,
• 07:34and I was asked to
• 07:34share some memorable moments. And,
• 07:36I have so many, but
• 07:38one that stands out to
• 07:39me is the Biostats Boating
• 07:40Adventure at Candlewood Lake in
• 07:42the fall of twenty twenty
• 07:43two. We rented a boat
• 07:45and got a tour guide
• 07:46to show us around the
• 07:47lake and we had snacks
• 07:48and it was such a
• 07:49fun memory.
• 07:50And, you know, the animal
• 07:51lover that I am, I
• 07:52had to share a picture
• 07:53of this very majestic crane
• 07:54that we saw.
• 07:56And so I've taken a
• 07:58lot of courses at Yale,
• 07:59and I've really enjoyed that
• 08:01clearly because I've taken twenty
• 08:02one courses,
• 08:04during my time here at
• 08:05Yale from
• 08:06statistics, biostatistics,
• 08:08epidemiology,
• 08:09public health history, and implementation
• 08:11science.
• 08:12And I definitely would say
• 08:13that my favorite course was
• 08:15the advanced methods for implementation
• 08:17and prevention science taught by
• 08:19doctor Donna Spiegelman.
• 08:20And if I had to
• 08:21sum up this course, I
• 08:22would say that bridging the
• 08:23gap between evidence and impact,
• 08:25advanced implementation science equips us
• 08:28to design, analyze, and advance
• 08:30studies that drive real world
• 08:32change. And,
• 08:34I find myself whenever I
• 08:35am explaining
• 08:36implementation science to my friends
• 08:38or family, this comic that
• 08:40Donna shared,
• 08:42on the first day of
• 08:43class always stands out to
• 08:44me, which says, you know,
• 08:45the latest research shows that
• 08:47we really should do something
• 08:48with all this research,
• 08:50which I definitely think gets
• 08:51to the heart of what
• 08:52we do in implementation science.
• 08:55And this is the course
• 08:56that I found,
• 08:57what my dissertation topic would
• 08:59be. I,
• 09:00as doctor Mukherjee mentioned, I
• 09:02do cluster randomized trial work
• 09:03with hybrid designs,
• 09:05and I definitely recommend any
• 09:06students in the audience if
• 09:08you have the chance to,
• 09:10take this course, I highly
• 09:11recommend it. Even if you're
• 09:12not in the pathway, I
• 09:14think it's really important in
• 09:15public health.
• 09:16And other favorites that I
• 09:17have include implementation science taught
• 09:20by Doctor. Luke Davis, causal
• 09:21inference taught by Doctor. Fan
• 09:23Li,
• 09:23advanced causal inference by Doctor.
• 09:25Laura Frustier, and frontiers of
• 09:27public health who I took
• 09:28with Doctor. Sten Vermund.
• 09:31But now moving on to
• 09:32the reason why we're all
• 09:33here, Doctor. Donna Spiegelman. She
• 09:35has many very impressive titles,
• 09:38she is the Susan Dwight
• 09:39Bliss Professor of Biostatistics,
• 09:41she's the Director for the
• 09:43Center of Methods and Implementation
• 09:44and Prevention Science,
• 09:46She is professor of statistics
• 09:47and data science and also
• 09:49professor of medicine with a
• 09:50concentration
• 09:51in cardiovascular
• 09:52medicine.
• 09:53She's the assistant director for
• 09:55global oncology at the Yale
• 09:56Cancer Center, and she's also
• 09:58a professor of epidemiologic
• 10:00methods emerita at Harvard.
• 10:02She earned her SCD in,
• 10:04at Harvard in both biostatistics
• 10:07and epidemiology.
• 10:08She has mentored countless students,
• 10:11junior faculty, and researchers,
• 10:14and she has made many
• 10:15prominent contributions in fields including
• 10:17implementation science,
• 10:19obesity research, cancer, global health,
• 10:22HIV and AIDS,
• 10:24cardiovascular
• 10:25diseases, mental health, and much
• 10:27more. And in preparation for
• 10:28this, I was,
• 10:30reviewing her CV and it's
• 10:32very impressive. I'm just in
• 10:33awe of it, and it's
• 10:34almost a hundred pages long
• 10:35and,
• 10:36I was very, very just,
• 10:39impressed by it all. And
• 10:40so just to name some
• 10:41of the awards that she
• 10:43has won previously,
• 10:44she's won many distinguished awards
• 10:46acknowledging her work and impact
• 10:48in statistics, biostatistics,
• 10:50epidemiology,
• 10:51sign and scientific research in
• 10:52general.
• 10:53Among these are she was
• 10:55ranked four hundred ninety six
• 10:56globally and three hundred and
• 10:58thirty fifth in the US
• 10:59of best scientists in the
• 11:00world in twenty twenty three.
• 11:03She was ranked number two
• 11:04hundred and forty one globally
• 11:05and one sixty two in
• 11:07the US and ranking of
• 11:08top one thousand scientists
• 11:10in the field of medicine
• 11:11in twenty twenty three. She's
• 11:13recognized in the list of
• 11:14women who have made noteworthy
• 11:16contributions to or achievements in
• 11:18statistics by Wikipedia.
• 11:20She was BMC's top author
• 11:22in twenty twenty one, and
• 11:23she was recognized as a
• 11:25highly cited researcher
• 11:26by the Clarivate Web of
• 11:28Science in twenty eighteen, twenty
• 11:29nineteen, twenty twenty, and twenty
• 11:31one,
• 11:32just to name a few.
• 11:35And my favorite memory of
• 11:37Donna is definitely the CMIP's
• 11:39return to school party hosted
• 11:41at her home.
• 11:43She has a lovely home
• 11:44right by the beach, and
• 11:45these are some pictures that
• 11:46we took when we,
• 11:48did a walk by the
• 11:50beach, and it was such
• 11:51a beautiful day.
• 11:53Donna is very welcoming
• 11:55in her classroom. She makes
• 11:57people feel,
• 11:59very included, and that definitely
• 12:01extended to her home.
• 12:03As soon as we all
• 12:04showed up, doctor Spiegler made
• 12:06us feel so at home.
• 12:08And,
• 12:09I one thing that really
• 12:11stands out to me about
• 12:12that day is that I
• 12:13am vegan, and so I
• 12:14have a lot of dietary
• 12:15restrictions. And so I always
• 12:16stress out about events and
• 12:18having to eat maybe before
• 12:19or after,
• 12:21but she remembered this and
• 12:22was just so accommodating to
• 12:24me and,
• 12:25was checking in and making
• 12:27sure that I was finding
• 12:28things to eat, and,
• 12:29that really stands out to
• 12:31me.
• 12:32And so before I passed
• 12:34it off to her, what
• 12:35I wanted to leave with,
• 12:37was that although I am
• 12:38just inspired and in awe
• 12:40by her career and all
• 12:41of her successes,
• 12:43I am more inspired by
• 12:45the fact that she cares
• 12:46very deeply about her students.
• 12:49Every week when we meet,
• 12:51she is encouraging.
• 12:52She is patient with me.
• 12:54She cares about my well-being,
• 12:56not just as a student,
• 12:57but as a person.
• 12:58You know, I've been at
• 12:59Yale for a while now,
• 13:01and there have been a
• 13:02lot of challenges that have
• 13:03come up for me professionally
• 13:04and personally.
• 13:06And she has been my
• 13:07advocate. She has fought for
• 13:09me, and she's encouraged me
• 13:11to,
• 13:13take breaks when I need
• 13:14to. And I it's not
• 13:16lost on me that this
• 13:17is not the typical experience
• 13:19necessarily
• 13:20of PhD students, but I
• 13:22am very fortunate that this
• 13:24is my experience. So without
• 13:26further ado, I will pass
• 13:27it off to doctor Donna
• 13:29Spiegelman.
• 13:38Well, thank you so much,
• 13:39Melody.
• 13:40I just wanna make sure
• 13:41this mic is gonna pick
• 13:42me up well enough or
• 13:43I need to use your
• 13:44mic.
• 13:47Let's see.
• 13:49Is this working? Not really.
• 13:51I think I'm gonna have
• 13:52to use the hand mic.
• 13:56Yeah. So, Melody, thank you
• 13:57for that amazing
• 13:59introduction. It makes me feel
• 14:00so good. And, you know,
• 14:02times like this, you don't
• 14:04necessarily realize what kind of
• 14:05difference or impact you're having
• 14:06on people. So just to
• 14:08hear that acknowledgement,
• 14:10just means so much to
• 14:11me. And it's also very
• 14:12reinforcing
• 14:13in terms of, like, continuing
• 14:14on to do some of
• 14:16the things I'm doing and
• 14:17knowing that they're appreciated.
• 14:18I also wanna thank Dean
• 14:20Bromar Mokherjee for making it
• 14:21possible for me to tell
• 14:23my life story to all
• 14:24of you guys, and I
• 14:25think there's lots of people
• 14:26also on Zoom who can
• 14:28be here. It's I never
• 14:30dreamed that I would be
• 14:31asked to do this. It's
• 14:32sort of almost unimaginable. And
• 14:34then I feel like I
• 14:35should also thank Dean Ranney,
• 14:36who couldn't be here because
• 14:38it's school vacation week, and
• 14:39she's off with her kids
• 14:41on a ski vacation, I
• 14:42think. But I'm sure behind
• 14:43the scenes, she's also made
• 14:45this event possible, and I'm
• 14:47very grateful to her as
• 14:48well.
• 14:49So
• 14:53let's see now.
• 14:54I have to figure out
• 14:55how to advance this. Maybe
• 14:57it's the mouse. Does anyone
• 14:58know what advances it? Okay.
• 15:00There we go.
• 15:02Yeah. So Melody actually,
• 15:05summarized a what how I'm
• 15:06structuring this is I'm gonna
• 15:07say kind of like where
• 15:09I am today in terms
• 15:10of my accomplishments and work.
• 15:12Then I'm gonna go go
• 15:13way back to my great
• 15:14grandparents and my grandparents
• 15:16and show how we got
• 15:17to where we are and
• 15:18then sort of come back
• 15:19to the present. And I
• 15:20may run out of time
• 15:21and not be able to
• 15:22actually cover the present very
• 15:24much, but we'll see how
• 15:25far we get. And, Bromar,
• 15:27please, don't be shy about
• 15:28cutting me off when the
• 15:29time is up.
• 15:31So, Melody mentioned already my
• 15:33high rankings on these various
• 15:35research indexes.
• 15:36One thing,
• 15:38they also give these indexes
• 15:39separately for everybody and then
• 15:41for women.
• 15:42And, when the indices
• 15:44are done for women,
• 15:46my ranking goes way, way
• 15:47up. Up. And, I wanted
• 15:49to just make a note
• 15:50of that because we all
• 15:52know that women in research
• 15:53and in the professional world
• 15:55do face additional challenges that
• 15:58can make it harder for
• 15:59us to achieve and especially
• 16:00at the same rate of
• 16:02productivity.
• 16:03We sometimes people say we
• 16:04can go longer, but we
• 16:06were slower. That's just a
• 16:08gross generalization.
• 16:09But,
• 16:10we do have quite a
• 16:11bit more responsibilities when it
• 16:13comes to children, the home,
• 16:15elder parents, and so forth.
• 16:17Typically then, our male counterparts,
• 16:19although, of course, there's exceptions.
• 16:21And so it's nice to,
• 16:23look at the ranking also
• 16:25by women as well as
• 16:26kind of overall. And then,
• 16:28you know, I can see
• 16:29that, my rankings do go
• 16:31up quite a bit. I
• 16:31have a very high h
• 16:32index.
• 16:34Melanie mentioned already I have
• 16:35a joint doctorate in biostatistics
• 16:37and epidemiology.
• 16:38There's a few other people
• 16:39in the world who have
• 16:40this. Not very many, like
• 16:41maybe just three or four.
• 16:44And I'll tell you a
• 16:45little later how I got
• 16:46there. I'm also a, NIH
• 16:49Director's Pioneer
• 16:50Award recipient to call the
• 16:52DP one, and I received
• 16:53that in twenty fourteen.
• 16:55It's a,
• 16:56two point five million dollar
• 16:58direct cost grant
• 17:00given to a senior scientist
• 17:02who wants to redirect their
• 17:03career, at least to some
• 17:05extent, into an area, a
• 17:07new area. So it's called
• 17:08high risk, high reward because
• 17:10it's always very risky to
• 17:11redirect your career. I was
• 17:13already doing measurement error and
• 17:15analytic epidemiology and all that
• 17:17sort of thing. And then
• 17:18I felt and you're gonna
• 17:19learn more about this too.
• 17:20I wanted to switch to
• 17:21implementation science and implementation science
• 17:24methods, which I had especially
• 17:26in the methods, I had
• 17:27very little background
• 17:28in. And then this grant
• 17:30made it possible for me
• 17:31to do this. And,
• 17:33here I have a little
• 17:33bit from a the epidemiology
• 17:35monitor. The epi monitor is
• 17:37kind of a kinda casual
• 17:39newsletter in the epidemiology
• 17:41community that has job ads
• 17:42and short articles, and they,
• 17:44covered it,
• 17:46a little bit of it
• 17:47when it happened because it
• 17:48was kind of a big
• 17:48deal in epidemiology
• 17:50for somebody to get the
• 17:51Pioneer Award. It usually goes
• 17:53to very hardcore basic scientists,
• 17:55chemists, and physicists,
• 17:57and people like that.
• 17:59So I don't know if
• 18:00there's anything I wanted to
• 18:01say about that except maybe,
• 18:05you know, it kind of
• 18:05says why was I interested
• 18:07in making the switch.
• 18:09I wanted to make more
• 18:10of a difference and have
• 18:11more of a direct impact
• 18:13on public health.
• 18:14And I had seen through
• 18:16some of my work in
• 18:17the delivery and monitoring of
• 18:19PEPFAR,
• 18:20our our big US HIV
• 18:22AIDS program that had been
• 18:23going on for maybe thirty
• 18:24years that has just in
• 18:26the past week or two
• 18:27been, possibly canceled by the
• 18:29Trump administration.
• 18:31I was very involved in
• 18:32its delivery and evaluation in
• 18:34the greater Dar es Salaam
• 18:35area of Tanzania for probably
• 18:38maybe ten years or so.
• 18:40I saw that how interventions
• 18:42might be altered or evaluated
• 18:44to have even bigger impact,
• 18:45to be more cost effective
• 18:47and so forth. And that's
• 18:48how I kind of got
• 18:49interested in implementation science.
• 18:56And then,
• 18:57as that Pioneer Award was
• 18:58wrapping up,
• 19:00I'm thinking, well, what am
• 19:01I gonna do now? And,
• 19:03the idea I had was
• 19:04to have some sort of
• 19:05center like we have now
• 19:06at Yale, CMIPs.
• 19:09And,
• 19:10I had thought thought about
• 19:12having it at Harvard where
• 19:13I had been for probably
• 19:14at that point twenty five
• 19:16years or making a move
• 19:17to do it somewhere else.
• 19:19And sometimes, I mean, this
• 19:20is another sort of career
• 19:21thing.
• 19:22If you wanna make a
• 19:23big change in your career,
• 19:25it's not I wouldn't say
• 19:26nobody could ever do that
• 19:28at the place where they
• 19:29are, but it seems that
• 19:31making a move is a
• 19:33much easier way to do
• 19:34that. It's much more greatly
• 19:34appreciated. Deans have money to
• 19:34recruit new people to start
• 19:34new
• 19:36appreciated. Deans have money to
• 19:38recruit new people to start
• 19:40new programs, but they usually
• 19:42don't have money set aside
• 19:43to put into somebody who's
• 19:44already there kind of like
• 19:46as a lame duck.
• 19:47And, I couldn't really get
• 19:49traction,
• 19:50at the Harvard School of
• 19:51Public Health. I have,
• 19:53Sten, Vermont,
• 19:54I've I had encountered, just
• 19:56like Braumar,
• 19:57through networking at various
• 19:59international conferences and meetings and
• 20:01so forth. And I had
• 20:02been talking to him about
• 20:03this concept. And then,
• 20:05when he became dean here
• 20:07at Yale, I reached out
• 20:08to him and I said,
• 20:09hey. How about that center
• 20:11we've been talking about? Would
• 20:12you like to have that
• 20:13at Yale? And he said,
• 20:14wow. Really? You'll do that?
• 20:16And I said, yes. And
• 20:17so that's how it happens,
• 20:19you know, a combination of
• 20:20network. And where were we
• 20:21talking about this? In Swaziland.
• 20:24So,
• 20:25I'm very grateful to Stan
• 20:27for making this happen.
• 20:28And,
• 20:29and now I'm gonna just
• 20:30say a little bit about
• 20:32another maybe sort of career
• 20:33sort of thing is,
• 20:35it was a very generous
• 20:37offer that it was kind
• 20:39of like an offer you
• 20:40can't receive.
• 20:41I had four,
• 20:43faculty slots for tenure track
• 20:45faculty. I had a generous
• 20:46startup package.
• 20:48You know, I became an
• 20:49endowed professor as Melody pointed
• 20:51out,
• 20:53full time admin and so
• 20:54forth.
• 20:56The center succeeded.
• 20:57I'm sure I could take
• 20:58some credit for it, and
• 20:59all of you guys have
• 21:00been working with me. But
• 21:01the fact that we had
• 21:02these resources
• 21:04made it hard to fail
• 21:05when you have the the
• 21:07right amount of resources to
• 21:08do something. And sometimes people
• 21:10get various sorts of encouragement
• 21:13to start an initiative or
• 21:14whatever, and they really don't
• 21:16get the resources. And you
• 21:17just struggle. So
• 21:20I just, feel very lucky
• 21:21that I was able to
• 21:23come here and do this
• 21:24and really got this robust
• 21:26package. So,
• 21:28here, you know, this is
• 21:29at around five years. We
• 21:31have,
• 21:32we have our four tenure
• 21:34track faculty,
• 21:35Xin Zhou, family, Ashley Hageman,
• 21:37Drew Cameron. I felt like
• 21:39I could have made it
• 21:39all biostatistic
• 21:41biostatistics,
• 21:42but in implementation science is
• 21:44inherently multidisciplinary.
• 21:45And I wanted to make
• 21:46sure that we could really
• 21:47have a full complement of
• 21:49the types of expertise we
• 21:51needed to to do the
• 21:52work we did. So, Shin
• 21:54and Fan are
• 21:56outstanding biostatisticians.
• 21:58Ashley Hageman is a medical
• 22:00anthropologist
• 22:01with a deep expertise in
• 22:03qualitative research methods. And Drew
• 22:06is a health economist with
• 22:07deep expertise in cost effectiveness
• 22:10evaluation
• 22:11and health economics, particularly in
• 22:13low and middle income country
• 22:15settings. So we have a
• 22:16great team and then, we
• 22:18had, Raul Hernandez Ramirez, started
• 22:20out as an associate research
• 22:22scientist,
• 22:23is now a research scientist.
• 22:24We had Tony Tang, who
• 22:26started as an ARS, became
• 22:27an RS, and now is
• 22:29a assistant professor in cardiovascular
• 22:31medicine, but working very closely.
• 22:33And then recently, we've gotten
• 22:34a bunch of more grants
• 22:35and,
• 22:36we have three new ARSs.
• 22:38Mona Abdo, who just had
• 22:39a baby a week ago,
• 22:40so she's on maternity leave,
• 22:42Anna Porter,
• 22:43and,
• 22:44Nikkita Rao. And, thanks to
• 22:46COVID,
• 22:47we could attract the very
• 22:49best talent even remotely.
• 22:51So both Anna and Nikkita
• 22:53are fully remote, and I've
• 22:55never yet met Nikkita in
• 22:57person. I we have met
• 22:59Anna now several times in
• 23:00person.
• 23:02And, these are some of
• 23:03the accomplishments
• 23:04of CMIPs up to this
• 23:06point. I mentioned the hirings.
• 23:09Over the first five years,
• 23:10we published two hundred and
• 23:11fifty four papers as a
• 23:13team.
• 23:14We have,
• 23:16we started four new courses
• 23:18at the school,
• 23:20and we, brought in almost
• 23:22sixty million dollars worth of
• 23:24grants either directly as
• 23:26PIs, MPIs, site PIs,
• 23:29project directors, and so forth,
• 23:30and as part of the
• 23:32technical team of other people's
• 23:34grants where we're collaborating. And
• 23:35we did the statistics, the
• 23:37qualitative research, the design, and
• 23:39so forth. And at the
• 23:40same time, we have around
• 23:42forty two million dollars pending
• 23:44in other large grants. And
• 23:45it's a process so this
• 23:46was like a year ago.
• 23:48Some maybe some grants have
• 23:49phased out. Some of the
• 23:51pendings have phased in. There's
• 23:52new pendings, but it's a
• 23:53good snapshot.
• 23:57And then,
• 23:58me, I think maybe, Melody
• 24:00has already said much of
• 24:02it. I do have nearly
• 24:04eight hundred publications, as she
• 24:05mentioned, the very long CV.
• 24:07We'll talk a little bit
• 24:08about how did I get
• 24:09all that work done.
• 24:11And, what the grants that
• 24:13I'm currently PI or MPI
• 24:15of around nines right now,
• 24:17twenty six maybe over the
• 24:18course of my career. I've,
• 24:20written eight book chapters.
• 24:22And then we have a
• 24:23big pipeline,
• 24:24so it's not over. And
• 24:25we'll see at the end
• 24:26if I have time. There's
• 24:27thirty three submitted papers right
• 24:29now out there and thirty
• 24:31six in prison in preparation.
• 24:33So it's a very active
• 24:35group of, really interesting things
• 24:37in A number of you
• 24:38here are the people working
• 24:39on these things with me.
• 24:41So that's the present
• 24:43between what Melanie Melanie said
• 24:45and here. And now we're
• 24:46gonna say, how did I
• 24:47get here?
• 24:49So now we're gonna go
• 24:50to my family history.
• 24:52So my maternal grandparents, Rose
• 24:54Silbert Rifkin and Victor Rifkin.
• 24:56My great grandparents on that
• 24:58side,
• 24:59Javera Rohinski Silbert and Moshe
• 25:01Mayer Silbert.
• 25:02My paternal grandparents, Anne Khan
• 25:05Spiegelman and Joe Spiegelman, my
• 25:07great grandmother Celia Khan, and
• 25:09then my parents, Rota Rifkin,
• 25:10Spiegelman and Stanley Spiegelman. So
• 25:12I'm gonna tell you about
• 25:14all of these different people,
• 25:15what I know about them.
• 25:17So my grandparents are all
• 25:18Jewish immigrants from Eastern Europe.
• 25:21Belarus, which is here
• 25:23wait. Why isn't
• 25:24the where's that?
• 25:27Oh, there where is it?
• 25:29Oh, there oh, it's going
• 25:30oh, there it is. Okay.
• 25:32Here. It's not a very
• 25:33good one. So here's Belarus.
• 25:34Most people haven't heard of
• 25:35it.
• 25:37But it is a country
• 25:38beach. You can see it
• 25:38borders on Latvia, Lithuania,
• 25:40Poland, Ukraine, and then this
• 25:42is Russia over here.
• 25:44So, that's an important place
• 25:46where many of my grandparents
• 25:48came from. Another one is
• 25:49Poland over here and then
• 25:51Austria down here.
• 25:53I know most about my
• 25:55parent maternal grandmother and grandfather
• 25:57because I did an oral
• 25:58history with my grandmother
• 26:01a long time ago in
• 26:02nineteen seventy nine.
• 26:03So I'm gonna play a
• 26:04little clip of it.
• 26:07Her story starts in a
• 26:08one room house in Sylhet,
• 26:10Belarus.
• 26:11And I asked her, what
• 26:12was your house like, Nana?
• 26:15I hope this will be
• 26:16loud enough.
• 26:19Okay. So first, tell me
• 26:20what your house looked like,
• 26:21the house that you were
• 26:22born. I'm telling you, it
• 26:23was a very small one
• 26:24room house. Your house was
• 26:26one room? Yes.
• 26:28And,
• 26:30what since I remember we
• 26:32were four children and my
• 26:33parents, the rest of my
• 26:35brothers and sisters were out
• 26:36of the house already. Mhmm.
• 26:38Some of them were in
• 26:39America,
• 26:40and some of them were
• 26:41working in bigger cities.
• 26:44And I and one of
• 26:46my sisters and two brothers
• 26:47were at home Uh-huh. At
• 26:48the time I was growing
• 26:50up.
• 26:52Okay. Who built your house?
• 26:54Gentle peoples were rented there
• 26:55from. Gentle people. Uh-huh.
• 26:58And,
• 26:59what did you have heat
• 27:00in the house?
• 27:02No. We had a stove.
• 27:04Wood we used to warm
• 27:06it with wood. Mhmm. It's
• 27:07like a regular like you
• 27:08see on the farms,
• 27:10those brick stove. Mhmm. And
• 27:12you
• 27:21did you have a bathroom
• 27:22in the house?
• 27:23No. No. Where'd you have
• 27:24a bathroom? Oh,
• 27:27And was it on the
• 27:28street? It wasn't up on
• 27:29the street. It was back
• 27:30in the back of the
• 27:31house.
• 27:33No. I mean, was the
• 27:34house on the street?
• 27:35Yeah. And were there other
• 27:37houses next to it? Right.
• 27:38So were all your neighbors
• 27:39Jewish?
• 27:41Well, anyway, we can, and
• 27:43was that loud enough for
• 27:44people? Could you hear it?
• 27:45Oh, good. I'm so glad.
• 27:47So yeah. So that's a
• 27:48little bit about what her
• 27:49their family's living circumstances
• 27:51were like at that time.
• 27:53Okay. So first, tell me
• 27:54what your house looked like,
• 27:55the house that you were
• 27:56born. I'm telling you, it
• 27:57was a very small one
• 27:59room house. You have I
• 28:00know how to do that.
• 28:01Okay. And then I just
• 28:02noted because they were going
• 28:03outside to go to the
• 28:04bathroom. This was in Belarus.
• 28:06The average temperature in the
• 28:07winter is twenty five twenty
• 28:09five degrees Fahrenheit.
• 28:11Does not sound like a
• 28:12lot of fun.
• 28:15And, here,
• 28:16is their journey in, Europe
• 28:18before they came to the
• 28:19United States. So she started
• 28:21out here in Siletz, which
• 28:23is in Belarus,
• 28:24and then they moved, and
• 28:25you're gonna hear why they
• 28:26moved,
• 28:27to Nova ZIP code, which
• 28:29is actually right now in
• 28:31Russia proper. It may not
• 28:32have been at that time.
• 28:34And then I think there
• 28:35were some problems, and then
• 28:36they moved to Gomel, which
• 28:38is also in Belarus.
• 28:39And then from there, you'll
• 28:40see they came to the
• 28:41United States.
• 28:42So I asked her, why
• 28:44did you leave Siletz, Nana?
• 28:46And she starts to tell
• 28:47the story of a, you
• 28:48know, very violent,
• 28:50incident that occurred to the
• 28:51family by, people who aren't
• 28:53Jewish that lived there, you
• 28:55know, Belarusian people.
• 29:00Well,
• 29:01when the peasant the young,
• 29:03people came and then they
• 29:04were getting
• 29:06Oh, when the peasant, the
• 29:07young, people came, and then
• 29:08they were begging the way
• 29:09they wanted to kill the
• 29:09Jews. And my father was
• 29:10you know, he was they
• 29:10were begging the way they
• 29:12if they wanted to kill
• 29:13the Jews. And my father
• 29:14was
• 29:15you know, he was used
• 29:16to fix the machines.
• 29:18And he wasn't dead, and
• 29:19we were afraid that
• 29:23And a night later,
• 29:25we had these guys come
• 29:27in. I recognized them. And
• 29:28he came over. One came
• 29:29over to us. We we
• 29:31heard time by the banding
• 29:32around.
• 29:33And,
• 30:01a tragedy. Yes. But,
• 30:05he don't tell him till
• 30:06he finally found it.
• 30:08Alright. So I'll just quickly
• 30:10say, I thought it was
• 30:10a little hard to hear
• 30:11myself. But, like, a day
• 30:13or two later, another man,
• 30:14I don't know if it
• 30:15was one or more, came
• 30:16by people they knew, not
• 30:17strangers,
• 30:18and broke into the house
• 30:19and demanded their money.
• 30:21They were not rich.
• 30:23But my grandfa my great
• 30:24grandfather having anticipated this because
• 30:26of what happened a couple
• 30:28of nights before buried their
• 30:29money. So they just had
• 30:30a little bit of money
• 30:31to give to these people
• 30:33that broke into their house
• 30:34and they said,
• 30:35they held a knife to
• 30:36my grandfather and they said,
• 30:37you dirty Jew, give us
• 30:39your money. And, my grand
• 30:41that my grand great grandfather
• 30:43gave them the money he
• 30:43had. And
• 30:45after that, they moved to
• 30:46Nova ZIP code. And you
• 30:47wonder why so many Jewish
• 30:49people immigrated to the United
• 30:50States.
• 30:52This is not a atypical
• 30:53situation. In
• 30:54fact, many people had worse
• 30:56experiences.
• 30:56They weren't killed. Nobody hurt
• 30:58them, actually. They were just
• 31:00terrorized.
• 31:01So,
• 31:02that's, what happened and they
• 31:03went to Gomo and then,
• 31:05from there. Oh, when the
• 31:07cousins, the young people came
• 31:09and they
• 31:10okay. So then from there,
• 31:11they traveled to Riga, Latvia
• 31:14and then to New York
• 31:15City. That's about a five
• 31:16thousand mile trip.
• 31:18My grandmother,
• 31:19the one who's talking,
• 31:20we call her Nana Rose.
• 31:21She arrived with her parents
• 31:23and some brothers and sisters
• 31:24between twenty ten and nineteen
• 31:26twenty three. She came in
• 31:27nineteen twenty three, which was
• 31:29the year, I think, that
• 31:30they really clamped down on
• 31:31immigration. So if she had
• 31:33come a little later, she
• 31:34they may not have been
• 31:34able to come at all.
• 31:36And they moved to Brooklyn,
• 31:38New York. And my grandfather,
• 31:40her husband, who wasn't her
• 31:41husband then, owned and worked
• 31:43six days a week in
• 31:44a hand laundry.
• 31:45And, she worked originally in
• 31:47a shirtwaist factory. And then
• 31:49after she got married, she
• 31:50assisted my grandfather in the
• 31:52hand laundry.
• 31:54So here, now, these people
• 31:56that you were just hearing
• 31:57about, this is the man
• 31:58who the knife was held
• 31:59to his throat, my great
• 32:01grandfather.
• 32:02This is in New York
• 32:03at my grandmother and grandfather's
• 32:05wedding.
• 32:06And this is his wife,
• 32:07Dvera.
• 32:08And then here's my grandmother
• 32:10and my grandfather and many
• 32:11other relatives. I think I
• 32:12have cousins that are watching
• 32:13on Zoom, and some of
• 32:14these people are their grandparents.
• 32:17But, she Dvera,
• 32:20she was a beloved person.
• 32:21So in the Jewish tradition,
• 32:23we name children after a
• 32:25person who we really loved
• 32:26who died. And then now
• 32:28that we're in the United
• 32:29States, we don't use the
• 32:30actual name. We just use
• 32:31the first letter. So Tavera
• 32:33is Devorah in Hebrew or
• 32:35Deborah in English. And so
• 32:37my cousin Debbie, who's a
• 32:38little bit older than me,
• 32:39she got Debbie or Deborah,
• 32:40the real name. And then
• 32:42I got Donna, and then
• 32:43my other cousin got Deidra.
• 32:45But we're all named after
• 32:46the same person, Tavera.
• 32:49And then here's my grandparents
• 32:51on their wedding. They were
• 32:52married for forty one years
• 32:53until my grandfather's death in
• 32:55nineteen sixty nine from a
• 32:56heart attack, which I can
• 32:57even say as an epidemiologist.
• 33:00And some of you might
• 33:01remember, but heart disease was
• 33:03very, very prevalent,
• 33:04like, twenty and thirty and
• 33:06forty and fifty years ago.
• 33:07And especially men were very
• 33:09vulnerable,
• 33:10and they would die of
• 33:11heart attacks in their fifties
• 33:12and sixties. It was very
• 33:14common. It's very uncommon now.
• 33:17So amazing things have happened,
• 33:19I think, both in terms
• 33:20of prevention and care. So
• 33:22if my grandfather
• 33:23was was, sixty nine years
• 33:25old today, I doubt he'd
• 33:27be dying tomorrow. He'd probably
• 33:29live for another twenty years.
• 33:32And then they had my
• 33:33aunt,
• 33:34Doris, and my mother, Rhoda.
• 33:35And here they are, and
• 33:36then here they are a
• 33:37little older looking very lovingly
• 33:39at their mother.
• 33:41So this this is my
• 33:42mother's sister that she grew
• 33:43up with. And then a
• 33:44little bit about my father's
• 33:45family.
• 33:46So they also were immigrants.
• 33:48My grandmother here came from
• 33:50Poland at the age of
• 33:51six.
• 33:52My grandfather, Papa Joe, came
• 33:54from Austria. I'm not really
• 33:55sure what age. And I
• 33:57called my aunt Dierine who
• 33:58is right here. She's the
• 34:00youngest sister of this blended
• 34:02family of my grandmother,
• 34:05my,
• 34:06her husband, Joe Spiegland, was
• 34:08her second husband, his two
• 34:10sons, and then they had
• 34:11my aunt Dierine.
• 34:13And aunt Irene is still
• 34:14alive. Nobody else is still
• 34:15alive.
• 34:16And she said this is
• 34:17what she said. Nana Anne
• 34:19went to high school and
• 34:20graduated, which of course was
• 34:21a very big deal in
• 34:22those days. There's a lot
• 34:23of pride about that. She
• 34:25went on to vocational school
• 34:26to cut hair, permanence, and
• 34:28color. She then opened a
• 34:30beauty parlor.
• 34:31Papa Joe didn't finish high
• 34:32school. He worked along with
• 34:34his family to put food
• 34:35on the table. At a
• 34:36young age, he started the
• 34:37trucking company in the garment
• 34:39center of Manhattan.
• 34:40Grandma Celia Khan, who's right
• 34:42here,
• 34:43was amazing. When she came
• 34:45here, she had Nana Ann
• 34:46and two sons and went
• 34:47to night school to learn
• 34:48English.
• 34:49She had three more children
• 34:50here. Years later, when she
• 34:52was past seventy, she worked
• 34:54as a matron at a
• 34:55movie theater near where she
• 34:56lived. She would collect the
• 34:58ticket stubs.
• 34:59And so yeah. So here
• 35:00they all are on my
• 35:01father's side.
• 35:03My mother lived at home
• 35:04and she went to Brooklyn
• 35:05College
• 35:06to become a teacher. And
• 35:08so then there's a question,
• 35:09oh, why did she choose
• 35:10to become a teacher? So
• 35:11my daughter, my older daughter,
• 35:13Nessa Rose Sheer,
• 35:14has carried on the tradition
• 35:16and my mother died in
• 35:17March. But in December, just
• 35:19before that, she did an
• 35:20oral history of my mother.
• 35:22So we have my grandmother
• 35:23and now we have my
• 35:24mother. And so she asks
• 35:25my mother
• 35:26how she decided to become
• 35:28a teacher. Well, you'll find
• 35:29out it wasn't really very
• 35:30much of a decision. Decide
• 35:31what you were gonna do
• 35:32after high school.
• 35:34Oh, well, it was understood
• 35:36in our household. It's not
• 35:38very loud. College, and we're
• 35:39gonna be teachers. Okay.
• 35:41Yeah. Yeah. And you were
• 35:43It's not loud enough, is
• 35:44it? No. That's Alright. I'm
• 35:45gonna have to take it
• 35:46off. So basically, the mother
• 35:47says,
• 35:49they were hope her parents
• 35:51hoped that she would go
• 35:52to college and
• 35:53she did. And the only
• 35:54option for women in those
• 35:56days was to be a
• 35:57teacher.
• 35:58And so that's what she
• 35:59did.
• 36:00She doesn't talk about it
• 36:01with regret,
• 36:03like she wishes she did
• 36:04something else. She embraced teaching.
• 36:06She
• 36:07was the very best teacher
• 36:08she could be. Her friend,
• 36:09Marge, is here, is also
• 36:10a teacher. They work together
• 36:12in schools.
• 36:14But yeah. In those days,
• 36:15women,
• 36:16you know, depending on what
• 36:18your ethnic background was, for
• 36:20Jewish women in those days,
• 36:21you were gonna be a
• 36:22teacher.
• 36:23Probably for Irish women, it
• 36:25was gonna be nurse.
• 36:26And, for other ethnic groups,
• 36:28probably other options.
• 36:29So, that's how my mother
• 36:31became a teacher.
• 36:33And, she worked as an
• 36:35elementary school teacher and married
• 36:36at twenty three, had me
• 36:38at twenty five and my
• 36:39sister at twenty seven. She
• 36:41went back to work when
• 36:42I was in sixth grade
• 36:43as a remedial reading teacher
• 36:45and worked for another forty
• 36:46years, retiring at the age
• 36:48of seventy
• 36:49five due to impending blindness
• 36:51due to macular
• 36:52degeneration,
• 36:53a condition that I unfortunately
• 36:54have inherited.
• 36:56Heartbreaking to me that the
• 36:57reading teacher, an avid reader,
• 36:59could not read by the
• 37:00time she was in her
• 37:01mid eighties.
• 37:03But,
• 37:04she died last March at
• 37:05the age of ninety three,
• 37:06and I was so happy
• 37:08to have made the move
• 37:09to Yale because I had
• 37:10been up in Boston,
• 37:11so that I could be
• 37:12there for my mother during
• 37:13her last years
• 37:15of ill health and decline.
• 37:17And, I thank Dean Vermont
• 37:18for that as well, making
• 37:20it possible for make this
• 37:21to move into this amazing
• 37:22job where I could also
• 37:24be really close to my
• 37:25mother.
• 37:26So here's my father.
• 37:28He lived right around the
• 37:29corner from my mother on
• 37:31Lenox Road in Eat Flash,
• 37:32Black Bush, Brooklyn
• 37:33with his mother. I've already
• 37:35told you about them. And
• 37:36he had two stepbrothers, Mickey
• 37:37and Donnie, and a half
• 37:39sister Irene.
• 37:40He also lived at home
• 37:41and went to Brooklyn Polytech
• 37:43to become an engineer.
• 37:45And, I have the slide
• 37:46rule here because
• 37:47I don't know. I was
• 37:48at a dinner sometime with
• 37:49some younger people, and nobody
• 37:51had ever heard of a
• 37:52slide rule. And I don't
• 37:54know if there's people here
• 37:55who have, but even for
• 37:56me,
• 37:57when I first started maybe
• 37:58in later high school and
• 37:59early college,
• 38:01calculators just started coming into
• 38:02play. There really weren't computers
• 38:04or they were very hard
• 38:05to access them. And the
• 38:07way you multiplied,
• 38:08you know, multiple digit numbers
• 38:10did multiple,
• 38:11digit division,
• 38:12did logs, exponents,
• 38:15trigonometric
• 38:17functions. You could do all
• 38:19these things on this slide
• 38:20rule.
• 38:21And my father knew how
• 38:22to do it, and he
• 38:23even taught me how to
• 38:24do it. And I did
• 38:24know how to do it
• 38:25at one time. I don't
• 38:26remember at all now.
• 38:27But anyway, that's his engineering
• 38:29background. And,
• 38:31he went on in at
• 38:32night school and got a
• 38:33master's in industrial engineering at
• 38:34Columbia, and my mother got
• 38:36a master's in remedial reading,
• 38:38from the University of Bridgeport.
• 38:42My parents married in nineteen
• 38:44fifty three and divorced in
• 38:45nineteen seventy five. It was
• 38:47not a happy marriage. And
• 38:48unlike my mother and grand,
• 38:50mother, I did not grow
• 38:51up in a happy home.
• 38:53Along with me, they had
• 38:54my younger sister, Ellen, who
• 38:56lives in Topsin, Maine with
• 38:57her husband, Bobby Turcotte. And
• 38:59if you're wondering why he's
• 39:00in uniform, he was not
• 39:01a career military person, but
• 39:03these pictures were taken,
• 39:06around probably nineteen fifty three
• 39:08to nineteen fifty four. He
• 39:09volunteered for the US army
• 39:11and was put in the
• 39:12Army Corps of Engineers,
• 39:14and he was even stationed
• 39:15in Korea for some time.
• 39:17And there were still a
• 39:17very, you know, after World
• 39:18War two, like being in
• 39:20the US military was really
• 39:22a badge of great pride.
• 39:24And, men really,
• 39:25felt, at least in the
• 39:27community of men and parent
• 39:28men that I was around,
• 39:30to have been in the
• 39:30army and the military was
• 39:32something that was was really
• 39:34important to them and their
• 39:34self images as men even.
• 39:39So,
• 39:40I mentioned that my mother
• 39:42died on March twenty ninth
• 39:43two thousand,
• 39:44twenty four, and, we had
• 39:46an obituary in the Stanford
• 39:47Advocate. That's where we grew
• 39:49up. That's where my mother
• 39:50lived from around nineteen sixty
• 39:52until she died.
• 39:53And,
• 39:54my daughter,
• 39:55wrote this really wonderful obituary.
• 39:57And maybe I'll just read
• 39:58the last paragraph.
• 40:00So she says, Rhoda was
• 40:01the life of the party.
• 40:03So to celebrate her life,
• 40:05go out to the opera
• 40:06or a good
• 40:08show,
• 40:09then to your favorite restaurant.
• 40:11Bring your family, your friends,
• 40:14order
• 40:14some
• 40:17Soup. Order soup. Oh, order
• 40:18soup, preferably matzo ball. And
• 40:20maybe I need to put
• 40:21my glasses on.
• 40:23Preferably matzo ball. Or I
• 40:24can look up here.
• 40:26I forgot about that. So,
• 40:28yeah, orders order soup, preferably
• 40:31with matzo ball, and send
• 40:32it back to the kitchen
• 40:33if it's only warm because
• 40:35life is short and you
• 40:36deserve your soup piping hot.
• 40:40And my mother did not
• 40:41hesitate to send the soup
• 40:43back if it wasn't
• 40:44hot enough.
• 40:47So now we're getting to
• 40:48me. That's my family. And
• 40:49if people have more questions
• 40:51about all of that, I
• 40:52don't I hope we may
• 40:53have time in q and
• 40:54a, but I also welcome
• 40:55people you can email me
• 40:57later, say, well, why this
• 40:58or how did that happen?
• 40:59I'd be happy to answer
• 41:00it.
• 41:01So I grew up in
• 41:02Stamford, Connecticut. We started out
• 41:03living in Brooklyn near all
• 41:05these different family members I've
• 41:06showed you,
• 41:07at at,
• 41:09I was and, until I
• 41:10was five on Caton Avenue
• 41:11in East Flatbush, Brooklyn for
• 41:13those of you who know
• 41:14Brooklyn. Then my father got
• 41:16a job at Pitney Bowes
• 41:17and we moved to Stamford,
• 41:18Connecticut, where I lived until
• 41:20I left home in eighteen
• 41:21to go to college at
• 41:22Brandeis in the Boston area.
• 41:24I lived in the Boston
• 41:25area for forty three years
• 41:26until I came to New
• 41:27Haven in July of,
• 41:29twenty eighteen. Our house had
• 41:31a river in the backyard
• 41:32and woods nearby. I roamed
• 41:34the woods often alone, and
• 41:35I just I say often
• 41:36alone because things were safe
• 41:37then. Like, there was no
• 41:39worry about me, a girl,
• 41:41roaming in the woods alone
• 41:42at that time. Now I
• 41:43would never let my daughters
• 41:45roam in the woods alone
• 41:46at this point in time
• 41:48throughout elementary school.
• 41:50As an adult, I continued
• 41:51to roam the woods through
• 41:53hiking and backpacking, mostly in
• 41:55the White Mountains of New
• 41:55Hampshire where I and my
• 41:57two daughters are members of
• 41:58the forty eight four thousand
• 42:00footers club. There are forty
• 42:01eight mountains
• 42:02in the White Mountains of
• 42:03New Hampshire that are four
• 42:04thousand feet or more high,
• 42:06and we've all done them
• 42:08all, all forty eight. I've
• 42:10also trekked to Machu Picchu
• 42:11in Peru and attempted Mount
• 42:13Kilimanjaro
• 42:14in Tanzania, which I didn't
• 42:15make. My daughter did. And
• 42:17made it to Mount Meru,
• 42:18which is a somewhat lower
• 42:19mountain in Tanzania.
• 42:21And then here are some
• 42:22certificates I've gotten. This is
• 42:23the Mount Meru one. This
• 42:25is the forty eight four
• 42:26thousand footer one.
• 42:29I was what is now
• 42:30called gender nonconforming
• 42:32as a child, then called
• 42:33a tomboy.
• 42:34I was not interested in
• 42:35playing with dolls and I
• 42:36did not like wearing dresses.
• 42:38Finally, in eighth grade, thanks
• 42:40to all of the cultural
• 42:41changes of the sixties,
• 42:43including the women's movement, girls
• 42:45no longer had to wear
• 42:46dresses to school.
• 42:47I was so happy.
• 42:49And also,
• 42:50I did not like boy
• 42:51toys such as guns or
• 42:52trucks.
• 42:53So that didn't really leave
• 42:54me, with a lot of
• 42:56friend options.
• 42:58When I was nineteen, thanks
• 42:59to the women's and gay
• 43:00liberation movements of the sixties
• 43:02and early seventies, I came
• 43:03out as a lesbian. And
• 43:05at twenty, had my first
• 43:06lesbian relationship with a woman,
• 43:08Linda Bolt, who I met
• 43:09at the gay bar twelve
• 43:11seventy in Boston.
• 43:12We lived together for two
• 43:13to three years and it
• 43:14was a beautiful,
• 43:15loving, healing experience for me.
• 43:19I was different.
• 43:21I did chemistry and biology
• 43:22experiments in the basement
• 43:24using kits made for kids
• 43:25that could be bought at
• 43:26that
• 43:27time. I bred mice, experimenting
• 43:29with genetics with white and
• 43:31brown mice.
• 43:32I studied
• 43:33species of trees,
• 43:35insects, dogs, seashells,
• 43:37rocks and minerals using books
• 43:39like this. I don't know
• 43:40if anyone has ever seen
• 43:41a book like this,
• 43:43and knew many, many of
• 43:45them
• 43:45remembering them to this day.
• 43:47Like, who's heard of a
• 43:48dugong?
• 43:50Anyone?
• 43:51Okay. A couple of people
• 43:52have been in Australia. So
• 43:53it's a a mammal like
• 43:55a manatee
• 43:56that is only occurs in
• 43:58Australia.
• 43:59And I had never heard
• 44:01of it until my daughter
• 44:02went to Australia for her
• 44:03junior year abroad in college.
• 44:05And I thought, god, I
• 44:06thought I knew every single
• 44:07mammal. How could I not
• 44:09know about the dugong? But
• 44:10it's not in this book.
• 44:14I sold seeds and got
• 44:16a pup tent, which my
• 44:17father and I put up
• 44:18in the backyard and I
• 44:19was allowed to sleep in
• 44:20it. And I love camping
• 44:21to this day.
• 44:23I played with my cousins.
• 44:24We colored obsessively
• 44:26and played board games. I
• 44:27particularly loved Monopoly,
• 44:29Clue, which is a little
• 44:30scary because it has to
• 44:31do with murder and murder
• 44:32weapons,
• 44:34mousetrap and twister.
• 44:36The neighborhood was filled with
• 44:38kids and we played kickball
• 44:40outside the street whenever we
• 44:41possibly could. I love playing
• 44:43kickball and I was good
• 44:44at it. My sister and
• 44:45I also experienced intermittent
• 44:47anti Semitic harassment and bullying.
• 44:50For example, when we first
• 44:51moved to the neighborhood, kids
• 44:53screamed at us, go back
• 44:54to Israel
• 44:55and you killed Jesus.
• 44:57My mother told us we
• 44:58weren't from Israel, but from
• 45:00Brooklyn. So then they screamed,
• 45:01go back to Brooklyn.
• 45:03In junior high, on the
• 45:04bus on the bus on
• 45:06the way to school, they
• 45:07threw pennies at the Jewish
• 45:08boy in the neighborhood.
• 45:11Actually, there's a I wanna
• 45:13go to a different slide.
• 45:14Oh, I guess it's gone.
• 45:15Okay. I was gonna show
• 45:16something else. I loved reading
• 45:18and read constantly from an
• 45:19early age. I wrote my
• 45:21full name, the last name
• 45:22Spiegelman, with all the letters
• 45:24on a New York Public
• 45:25Library card when I was
• 45:26four and got my own
• 45:27library card so I could
• 45:28take out my own books.
• 45:30And in second grade, I
• 45:31read The Adventures of Huckleberry
• 45:33Finn, the original version.
• 45:36So, I mentioned these things
• 45:37because my parents were very
• 45:39impressed with my reading and
• 45:40writing abilities
• 45:41as a young age at
• 45:42a young age.
• 45:44And I I remain a
• 45:45voracious reader to this day.
• 45:47I'm currently reading The Lady
• 45:49in the Teacup, which is
• 45:50a very accessible
• 45:51history of statistics.
• 45:52And I keep track of
• 45:53everything I read. So I've
• 45:55read, at least, in the
• 45:56past, say, twenty years. I've
• 45:59read a hundred and sixty
• 46:00six books since twenty sixteen,
• 46:02averaging about eighteen books per
• 46:04year, mostly novels, but also
• 46:06non fiction. I like to
• 46:07read every night before I
• 46:08turn off the light to
• 46:09go to sleep.
• 46:11And I'm really thrilled that
• 46:12I'm in a book group
• 46:13right now with my daughter
• 46:14and a number of my
• 46:15women first and second cousins.
• 46:17And our partial focus is
• 46:18books on or about Jewish
• 46:20women. And here's our next
• 46:21book, Catter Skills Fall by
• 46:23Allegra Goodman.
• 46:25And so here are some
• 46:25books I've recently read. I
• 46:27point out this one on
• 46:28the, left here, Beyond Jagged
• 46:30Edges of Silhouette Trees. It's
• 46:31a novel written by, my,
• 46:33a recent partner that I've
• 46:35been involved with. It's an
• 46:36excellent book and you can
• 46:37buy it in Amazon. I'm
• 46:38very impressed with her writing
• 46:40and and what she's done.
• 46:41And these are some other
• 46:42really good books I've read
• 46:43recently. And here, just to
• 46:45get an idea, here's where
• 46:46I keep an Evernote.
• 46:47Here's where I keep the
• 46:48list of books and I
• 46:49also write little comments about
• 46:50them. So sometimes I get
• 46:52into conversations with people and
• 46:54they say, oh, what's a
• 46:55good book? And I'll say,
• 46:56oh, I think you might
• 46:56like this and I'll tell
• 46:58them a little bit about
• 46:59the notes.
• 47:01So I also loved music
• 47:02growing up. Like, I really
• 47:04loved music, and I still
• 47:05do.
• 47:07So when I was in
• 47:08third grade, I got my
• 47:09first album, Meet the Beatles,
• 47:11and a small phonograph.
• 47:12I played the album over
• 47:14and over in my room.
• 47:15I love the Beatles all
• 47:16the way up to the
• 47:17Abbey Road album. The White
• 47:19Album also stands out in
• 47:20my mind, although it was
• 47:21a little scary.
• 47:23In fourth grade, I started
• 47:24playing the flute and here
• 47:25I am doing that. I
• 47:26continued with formal lessons until
• 47:28seventh grade and have played
• 47:30the flute on and off
• 47:31my entire life. As a
• 47:32young adult, I also taught
• 47:33myself tenor sax and played
• 47:35in several bands.
• 47:38The civil rights movement brought
• 47:39desegregation
• 47:40to the Stanford public schools.
• 47:42And in seventh grade, our
• 47:43junior high was desegregated
• 47:45because the neighborhoods were completely
• 47:47segregated
• 47:48in Stanford,
• 47:49as they pretty much are
• 47:51everywhere.
• 47:52Black and white kids were
• 47:54all bussed together to the
• 47:55same junior high school and
• 47:56and then high school. So
• 47:58now I wanna try to
• 47:59get this to play. Oh,
• 48:00it's doesn't seem to have
• 48:01the okay.
• 48:03Too bad.
• 48:06I think I'm gonna read
• 48:07it from here.
• 48:10I heard what was called
• 48:11soul music, now called r
• 48:13and b, for the first
• 48:14time due to desegregation
• 48:16and the mixing of people
• 48:18from different cultures.
• 48:20And I loved it. In
• 48:21eighth grade girls gym class,
• 48:22I chose to do the
• 48:23extra size routine assignment to
• 48:25Gladys Knight and the pips.
• 48:26I heard it through the
• 48:27grapevine.
• 48:28The white girls laughed at
• 48:30me and called me a
• 48:30racist name I won't repeat
• 48:32here.
• 48:33This didn't stop me from
• 48:34loving soul music. And by
• 48:35high school, I found friends
• 48:36who also liked it, white
• 48:38friends.
• 48:39We would get together and
• 48:40dance for hours. I still
• 48:41love dancing to soul music
• 48:43and R and B. And
• 48:44here I am doing the
• 48:45funky chicken with my first
• 48:46boyfriend, Peter Peter Bolton.
• 48:49And I had really wanted
• 48:50to play. I heard it
• 48:51through the grapevine. But it
• 48:52doesn't seem like it seems
• 48:54like we lost that ability.
• 48:58So
• 48:59racism, antisemitism,
• 49:01sexism,
• 49:02and homophobia.
• 49:03I just have to say
• 49:05that I witnessed and experienced
• 49:06much racism,
• 49:08antisemitism,
• 49:09and homophobia
• 49:10growing up. These things are
• 49:11real, very real. And in
• 49:13this time, I think I
• 49:14just wanted to mention it.
• 49:16But, you know, we might
• 49:18think it's out there. Some
• 49:19of us might think it's
• 49:20out there with other people,
• 49:21but many of us, and
• 49:22I'm sure there's people in
• 49:23this room who have also
• 49:25experienced it. Sometimes we don't
• 49:26talk about it, but, you
• 49:28know, I mentioned some of
• 49:29the incidents that I've had
• 49:30in that regard, and I
• 49:31could tell you many more
• 49:32if we had time. But,
• 49:34it was very much in
• 49:35the background and,
• 49:37you know, we're it's a
• 49:38part of this country and
• 49:39part of what life is
• 49:40like here.
• 49:42In eighth grade
• 49:43okay. Now I think that
• 49:44one's gonna go on.
• 49:48These links don't seem to
• 49:49be live.
• 49:51Okay. In eighth grade, I
• 49:52took the train to New
• 49:53York City and went to
• 49:54Madison Square Garden with my
• 49:56friend, Mike Kelly, and saw
• 49:57Sly in the family's zone.
• 49:59Many kids weren't allowed to
• 50:00go to the city without
• 50:01parents, but since my parents
• 50:03came from the city, they
• 50:04allowed me. We were stoned
• 50:05on pot.
• 50:07Drugs and drinking were part
• 50:08of my life throughout junior
• 50:09high, high school, and college.
• 50:11And that's how it was
• 50:12then. And here's Sly. I
• 50:13loved Sly and the Family
• 50:15Stone and,
• 50:16you know, it was some
• 50:17of their my favorite music.
• 50:19I'm sorry I can't play
• 50:20it.
• 50:22So now we're on to
• 50:23college. That's my growing up.
• 50:25A snippet of my growing
• 50:26up, the good and the
• 50:27bad.
• 50:28And now I'm in college.
• 50:29I went to Brandeis because,
• 50:31one,
• 50:33I wanted to be in
• 50:34the Boston area, which was
• 50:35a hotbed of political and
• 50:37cultural activism.
• 50:39Two, Angela Davis went to
• 50:41Brandeis.
• 50:42Three, my mother agreed to
• 50:44let me date non Jewish
• 50:45boys in high school if
• 50:46I went to Brandeis for
• 50:47college.
• 50:49I loved Brandeis. Suddenly, it
• 50:51was normal to be Jewish,
• 50:52to look Jewish.
• 50:53Everybody liked me. No one
• 50:55made fun of me. The
• 50:56classes were interesting and on
• 50:57all different subjects. We could
• 50:59go to gay bars in
• 51:00Boston on the weekends.
• 51:02I self studied Freud in
• 51:04high school because I wanted
• 51:05to understand why I was
• 51:06gay and why my father
• 51:08was so angry and violent
• 51:09when I was growing up.
• 51:10Then I majored in psychology
• 51:12in college. Unfortunately,
• 51:14neither Freud nor the psychology
• 51:16classes I took answered these
• 51:17questions.
• 51:19Luckily, my father, who by
• 51:21this time worked for IBM,
• 51:22which was in its heyday,
• 51:23suggested I learn computer programming
• 51:26because I could always get
• 51:27a job in that. I
• 51:28taught myself Fortran from some
• 51:30workbooks my father brought home
• 51:31from the office. And then
• 51:33I took a computer class
• 51:34at college, and here's a
• 51:35sample of some code from
• 51:37a program that we've written
• 51:39that's on my website, and
• 51:40I just pulled out a
• 51:41snippet from it. But this
• 51:42is sort of what Fortran
• 51:44code looks like.
• 51:46So between college and grad
• 51:47school, I worked as a
• 51:49programmer using Fortran at several
• 51:51companies outside of Boston. I
• 51:53love programming,
• 51:54but I didn't like the
• 51:55work
• 51:56I didn't find the work
• 51:57of the, at the companies
• 51:59meaningful.
• 52:00Then I saw an ad
• 52:01in the Boston Globe for
• 52:02a Fortran programmer at the
• 52:04Occupational
• 52:05Health Program at the Harvard
• 52:06School of Public Health. I
• 52:08applied,
• 52:09went for the interview, did
• 52:10really well on the Fortran
• 52:11test they gave me, and
• 52:13I got the job.
• 52:15My life was changed.
• 52:18I loved the work. I
• 52:19loved the studies. I loved
• 52:21programming. I loved biostatistics.
• 52:23I love
• 52:24epidemiology.
• 52:26The occupational health program, which
• 52:27is where I was hired
• 52:29at Harvard, was a cool
• 52:30place to work. The faculty
• 52:32and students were all drawn
• 52:33to occupational health as a
• 52:35bridge between labor rights and
• 52:37grassroots organizing for social change,
• 52:39and the intersection of that
• 52:40with health, science, and medicine.
• 52:43David Wegman was the leader
• 52:44of this program. He's up
• 52:45there on the top left.
• 52:47And was my first mentor
• 52:48supporting me with only a
• 52:50bachelor's degree in publishing my
• 52:51first paper. And And here
• 52:53is my first paper. It
• 52:54was published in nineteen eighty
• 52:56three in the American Journal
• 52:57of Epidemiology,
• 52:59and it's called Interactive Electronic
• 53:01Computing of the Mortality
• 53:03Odds Ratio. It's actually a
• 53:04software paper.
• 53:08And a year or two
• 53:09after I started at Harvard
• 53:11in the occupational health program,
• 53:12Jamie Robbins joined us.
• 53:14He impressed me,
• 53:16immediately with how smart he
• 53:18was by showing off how
• 53:19he could do exponents in
• 53:21his head.
• 53:24He is the smartest person
• 53:25I've ever met.
• 53:26Another colleague, Ellen Eisen, was
• 53:28also in the occupational health
• 53:30program at the time. She
• 53:30was a PhD student, and
• 53:32she's become a lifelong friend
• 53:34and colleague.
• 53:36You know, I think I'm
• 53:37gonna skip. How are we
• 53:38doing with time, Brahma?
• 53:41Technically, we have five minutes
• 53:43off, but,
• 53:45again, ideally,
• 53:48I
• 53:50Okay.
• 53:51Alright. I'll I'll so I'm
• 53:52gonna skip. I was very
• 53:53involved in the union drive,
• 53:55the clerical and technical workers
• 53:56union drive when I was
• 53:57working as a programmer at
• 53:59Harvard. We lost that election,
• 54:02but we did it did
• 54:03eventually win two elections later.
• 54:05And then I moved on
• 54:06to graduate studies.
• 54:08So,
• 54:10I, learned,
• 54:11as I said, that I
• 54:12loved epidemiology and biostatistics,
• 54:14and that's what I wanted
• 54:16to do. But was it
• 54:17epidemiology
• 54:18or was it biostatistics?
• 54:20That was a very hard
• 54:21decision.
• 54:22So I talked to the
• 54:24late Jim Ware, who I
• 54:25had taken a biostat class
• 54:27from. As an employee, you
• 54:28were allowed to take one
• 54:29class per semester for free.
• 54:31And I asked him, should
• 54:32I apply for the master's
• 54:34program in biostatistics or epidemiology?
• 54:36And he said, well, epidemiology
• 54:39is dominated by medical doctors,
• 54:41and you're not a medical
• 54:42doctor. Are you good at
• 54:43programming and math? And I
• 54:45said, well, I like programming
• 54:46and I'm good at it.
• 54:48Math, oh, what did I
• 54:49say here? I hadn't taken
• 54:50math since AP Calculus in
• 54:52high school.
• 54:53Why? Because I saw no
• 54:54use for it. And as
• 54:56you could see, I had
• 54:56a lot of other interests.
• 54:59So,
• 55:00as Jeff mentioned, he had
• 55:02some slides called math. So
• 55:03now I can tell you
• 55:04my story with math.
• 55:05So,
• 55:07I wanted I was advised
• 55:09to go to the biostat
• 55:10master's program, and then to
• 55:11do that, I had to
• 55:12take more math. AP calculus
• 55:14from high school is not
• 55:15enough.
• 55:17So,
• 55:18I've had to restudy my
• 55:20high school calculus notes and
• 55:21textbook. I took multivariable
• 55:24calculus and linear algebra at
• 55:25Harvard College, and I studied
• 55:27for my GREs.
• 55:28I applied and was accepted
• 55:29to the master's program,
• 55:31in biostat at the Harvard
• 55:33School of Public Health. I
• 55:34love the biostat classes. I
• 55:36continued with data anal analysis
• 55:38projects with colleagues in the
• 55:40occupational health program while I
• 55:42labored over some of the
• 55:43rigorous theoretical classes.
• 55:45The courses were excellent, and
• 55:47they taught me the additional
• 55:48advanced mathematics that I needed
• 55:50as we went along. I
• 55:52used my twelfth grade calculus
• 55:53and much of the math
• 55:54I learned in grad school
• 55:55nearly every day for my
• 55:57work now.
• 55:59From there, I realized I
• 56:00wanted to get a doctorate.
• 56:01So I applied to a
• 56:02number of schools of public
• 56:04health that allowed for joint
• 56:05doctorates in biostat and epidemiology.
• 56:08I could go back to
• 56:09that again. It didn't seem
• 56:10possible with the master's degree,
• 56:12but I could go back
• 56:13to it with the doctorate.
• 56:14So UW,
• 56:15University of North Carolina, and
• 56:17Harvard all allowed people to
• 56:19apply for a joint doctorate.
• 56:21I was accepted to all
• 56:22of them, and although the
• 56:23University of Washington's department was
• 56:25much more oriented toward statistical
• 56:28methods for epidemiologic
• 56:29research,
• 56:30and the Harvard Biostat department
• 56:32was much more oriented towards
• 56:33clinical trials, which I wasn't
• 56:35even interested in,
• 56:37I went to Harvard to
• 56:38stay in Boston and remain
• 56:39with my community of mostly
• 56:41lesbian friends that I was
• 56:42having a great time with
• 56:43in Jamaica Plain.
• 56:46So that's how I did
• 56:47that. And now I'll I'll
• 56:49mention in nineteen eighty five,
• 56:51I became lovers with Elaine
• 56:53Shear. We met in Jamaica
• 56:54Plain in a Jewish women's
• 56:56study group on Jewish and
• 56:57Middle Eastern history
• 56:59with a focus on the
• 56:59history of the Jewish presence
• 57:01in the Middle East and
• 57:02its relationship to the Arab
• 57:04world.
• 57:04To this day, the struggle
• 57:06for Israeli Palestinian peace has
• 57:08been a major focus of
• 57:09our lives. And if I
• 57:10have time, I'll even be
• 57:11able to talk a little
• 57:12bit more about that. I
• 57:13don't think I am though.
• 57:14Two years later, she moved
• 57:16in with me to my
• 57:17second floor apartment in the
• 57:18triple decker I owned in
• 57:20Jamaica Plain, and our two
• 57:21dogs, Casey and Crystal, became
• 57:23sisters. We were together for
• 57:25thirty three years.
• 57:29And here's a few more
• 57:30pictures of us.
• 57:32Back to graduate studies.
• 57:35So I took courses, really
• 57:36incredible courses where I learned
• 57:38everything that I use all
• 57:40the time now in my
• 57:41work. Survival analysis from the
• 57:43late Steve Legakos, discrete data
• 57:45analysis from Nan Laird,
• 57:47statistical inference from Butch Siadis
• 57:49who's over here,
• 57:52a very abstract linear algebra
• 57:53based regression course from Cyrus
• 57:55Maeda down there.
• 57:57I took epidemiologic methods from
• 57:59Ken Rothman, the late Oli
• 58:01Meitinen, and Alec Walker. I
• 58:02took nutritional epidemiology
• 58:04from Walter Willett.
• 58:06And this was a little
• 58:08slide about Jamie because Jamie
• 58:09then started
• 58:11moving into novel methods around
• 58:13this time. And it was
• 58:15all motivated
• 58:16by figuring out a way
• 58:17to adjust for bias due
• 58:19to what was called the
• 58:20healthy worker effect,
• 58:21with the idea that,
• 58:23in an occupational health study,
• 58:25the people who are kind
• 58:27of the healthiest and least
• 58:28susceptible
• 58:29can stay on in the
• 58:30workforce the longer and then
• 58:32have the longest exposures
• 58:34to the point where it
• 58:35could actually look like the
• 58:36long exposures are beneficial.
• 58:39Because the people who are
• 58:40staying on and getting the
• 58:41most exposures
• 58:42are the ones that are
• 58:43the healthiest and dying the
• 58:44soonest, whereas the people who
• 58:46got hit by bad exposures
• 58:48are dying. They may have
• 58:49half the exposure of the
• 58:50long term employees.
• 58:52So his first approach was
• 58:54this nineteen eighty six paper
• 58:55in an obscure journal where
• 58:57he basically just finally stratified
• 58:59by the work history. So
• 59:00you only,
• 59:02compare a case to a
• 59:04control that has the exact
• 59:05same work history
• 59:06up to the last time,
• 59:08like the last year, in
• 59:09which there might be a
• 59:10difference. And then you see
• 59:11and it's hard to see
• 59:12here, but when you do
• 59:13that, there's zeros
• 59:15in these two by two
• 59:16tables. Like, there's no data.
• 59:18So he then had to
• 59:19come up with different modeling
• 59:20based approaches and so forth,
• 59:22and that led to, I
• 59:23think, a sort of the,
• 59:24g,
• 59:25g estimation
• 59:26and various sorts of things.
• 59:27But this was the very
• 59:28beginning of it.
• 59:30And,
• 59:31like I said, you know,
• 59:31I took the class twice.
• 59:33The first year where he
• 59:34said everything was all wrong,
• 59:35he was doing it all
• 59:36over, and then the second
• 59:38year where he was getting
• 59:39clearer on his methodologies.
• 59:42And here are some of
• 59:43my friends, my lifelong friends
• 59:44that I studied. I, as
• 59:46being in Biostat and EPI,
• 59:47I took and passed both
• 59:49the EPI qualifying exam and
• 59:51the Biostat qualifying exam. So
• 59:53here is my best friend
• 59:54in graduate school, Fang Wang
• 59:56Clow. She was one of
• 59:57the first people to come
• 59:58over from China when it
• 59:59came became possible for people
• 01:00:01to come from China and
• 01:00:02study in graduate school.
• 01:00:04And, some colleagues, Matt Longnecker,
• 01:00:07who was the former mentor
• 01:00:08of our current ARS, Anna
• 01:00:09Porter. So it's amazing how
• 01:00:11things are connected. And then
• 01:00:13Mauricio Hernandez Avila, who's become
• 01:00:15very high up in the
• 01:00:17public health community in Mexico,
• 01:00:19and we've kind of stayed
• 01:00:20in touch. And others as
• 01:00:21well, but these were some
• 01:00:22of my main friends studying
• 01:00:24for these two different qualifying
• 01:00:25exams. And,
• 01:00:26yeah, FANG especially were, like,
• 01:00:28really, really close.
• 01:00:30So my doctoral thesis,
• 01:00:33so I had to find
• 01:00:33a thesis topic.
• 01:00:35And,
• 01:00:36I mentioned faculty in the
• 01:00:38Harvard Biostat department weren't working
• 01:00:40on epi methods. No one.
• 01:00:42Absolutely no one.
• 01:00:44Jamie wasn't even in the
• 01:00:45biostat department. He was in
• 01:00:47the occupational health program. And
• 01:00:49when he got tenure, he
• 01:00:50got it in the epidemiology
• 01:00:51department, not the biostat department.
• 01:00:54So why was this? Well,
• 01:00:56Marvin Zellin, who was the
• 01:00:57long term chair of the
• 01:00:59Harvard Biostat department, was a
• 01:01:00hardcore randomista.
• 01:01:02So if you're not familiar
• 01:01:03with that term, these are
• 01:01:04people who only believe we
• 01:01:05can gain knowledge in human
• 01:01:07studies if they're randomized.
• 01:01:09And if the study isn't
• 01:01:11randomized, it's garbage, it's biased,
• 01:01:13it's intractable,
• 01:01:15we can't pay any attention
• 01:01:16to it. That's a very
• 01:01:17hardcore randomista.
• 01:01:19So there are people in
• 01:01:20the economics world now who
• 01:01:21are very hardcore randomistas.
• 01:01:24And also some people in
• 01:01:25the medical world. But Salin
• 01:01:27was one of them. And
• 01:01:28then Brian McMahon was the
• 01:01:29long term department chair of
• 01:01:30Epi. And in those days,
• 01:01:32people would be chair for,
• 01:01:33like, ten and twenty years.
• 01:01:34I don't know how long
• 01:01:35they they were chairs.
• 01:01:37They didn't speak to each
• 01:01:38other. There was no interaction
• 01:01:40between the two departments.
• 01:01:42On the epi side,
• 01:01:43epidemiologists
• 01:01:44doing methods largely thought that
• 01:01:46biostatisticians
• 01:01:47didn't understand data, science, or
• 01:01:49public health
• 01:01:50and applied methods in thoughtless
• 01:01:52formulaic ways that missed the
• 01:01:53key issues in the data
• 01:01:55and the science. For example,
• 01:01:57using a p value of
• 01:01:58point o five to decide
• 01:01:59whether a covariate and I
• 01:02:00have that in quotes because
• 01:02:02in epidemiology, and now you
• 01:02:03all know from causal inference,
• 01:02:05there are all kinds of
• 01:02:06variables that have different roles.
• 01:02:08And what what their role
• 01:02:10is depends on what you
• 01:02:11might do about them in
• 01:02:12a model or an analysis.
• 01:02:14But at that time, they
• 01:02:16on the biostat side, they
• 01:02:17were just covariates.
• 01:02:19Should and on the biostat
• 01:02:20side, there was an abiding
• 01:02:21assumption that epidemiologists
• 01:02:23were bad at math and
• 01:02:24therefore stupid.
• 01:02:26So this did not make
• 01:02:27for a happy marriage.
• 01:02:30So the conflict is played
• 01:02:31out in a book, in
• 01:02:32the movie, A Civil Action.
• 01:02:33You might wanna watch it,
• 01:02:35where the Harvard epi department
• 01:02:37defended industry and the biostat
• 01:02:39department defended the residents of
• 01:02:41the town of Woburn, Mass.
• 01:02:43And this was about tox
• 01:02:45toxic waste,
• 01:02:46deposits
• 01:02:47in Woburn and whether it
• 01:02:48caused clusters of childhood leukemia.
• 01:02:51They testified against each other
• 01:02:53in court, literally face to
• 01:02:55face in the same courtroom.
• 01:02:58Although Marvin Zellin generally skewed
• 01:03:00non randomized studies, he adopted
• 01:03:02observational epi methods to link
• 01:03:04the toxic waste dumps to
• 01:03:05cancer clusters.
• 01:03:07In my view, in the
• 01:03:08end, it seems that it's
• 01:03:08been very difficult to establish
• 01:03:10causal links between
• 01:03:12toxic waste stumps and cancer
• 01:03:14clusters. But anyway, this was
• 01:03:15the environment when I was
• 01:03:16a graduate student. These things
• 01:03:18were happening.
• 01:03:21So my doctoral thesis continued.
• 01:03:24I met with Walter Willett,
• 01:03:25who I take in nutritional
• 01:03:26epidemiology,
• 01:03:28and I asked him because
• 01:03:29I was I always all
• 01:03:30my research is motivated by
• 01:03:32data and real life problems
• 01:03:33and especially problems that are
• 01:03:35important and that I'm personally
• 01:03:37interested in.
• 01:03:38So I was interested in
• 01:03:40nutritional epidemiology and the relationship
• 01:03:42between diet and health. And
• 01:03:43I went to Walter and
• 01:03:44I said, well, what kind
• 01:03:45of methods questions are coming
• 01:03:47up in nutritional epi that,
• 01:03:49you know, I could possibly
• 01:03:50work on as a biostat,
• 01:03:51an epi methods thesis?
• 01:03:53And he said, measurement error.
• 01:03:56It just immediately resonated. Like,
• 01:03:58that was it. There was
• 01:03:59no decision. I never considered
• 01:04:01another thing. That was, like,
• 01:04:03what my thesis topic was
• 01:04:04gonna be.
• 01:04:05So, he had already done
• 01:04:07some preliminary work, and he
• 01:04:08had done conducted the first
• 01:04:10validation study, and he had
• 01:04:12been working on this problem
• 01:04:13with Bernie Rosner
• 01:04:14a little bit.
• 01:04:16They had a paper that
• 01:04:17had been rejected from statistics
• 01:04:18and medicine
• 01:04:19probably around nineteen eighty eight
• 01:04:21that,
• 01:04:24was a sort of an
• 01:04:25ad hoc regression calibration estimator,
• 01:04:28but it didn't have any
• 01:04:29theoretical justification.
• 01:04:30And I wrote here, I
• 01:04:32didn't think it had a
• 01:04:33variance derivation, but I actually
• 01:04:34do think Bernie used the
• 01:04:35delta method and did derive
• 01:04:37the variance.
• 01:04:38But they didn't have any
• 01:04:39we didn't have any theoretical
• 01:04:41justification, but I had this,
• 01:04:42like, great theoretical and rigorous
• 01:04:44training now from the Harvard
• 01:04:45Biostat department. So
• 01:04:47I,
• 01:04:49I
• 01:04:50came up with three different
• 01:04:51Taylor series expansions.
• 01:04:53One around the measurement error,
• 01:04:54one around the absolute disease
• 01:04:56frequency, and one around the
• 01:04:57relative risk. And then once
• 01:04:59you do that expansion and
• 01:05:00you drop the second order
• 01:05:01plus terms, you can, integrate
• 01:05:04out the likelihood with the
• 01:05:05normal measurement error model and
• 01:05:07get close form expressions
• 01:05:08that will give you an
• 01:05:09estimator and justify
• 01:05:11this,
• 01:05:12estimator. So,
• 01:05:13I added that contribution to
• 01:05:15the paper.
• 01:05:16And then time five more
• 01:05:17minutes. Okay. And then I
• 01:05:19also did simulation
• 01:05:20studies and so forth. And
• 01:05:21then the paper was accepted
• 01:05:22and it's actually one of
• 01:05:24our most highly cited papers
• 01:05:25in measurement error even though
• 01:05:26it's just univariate.
• 01:05:28And then we extended it
• 01:05:29to multivariate in nineteen ninety
• 01:05:31and nineteen ninety two and
• 01:05:32developed software that supports it
• 01:05:34all in SAS.
• 01:05:36So anyway, this was my
• 01:05:38dissertation committee.
• 01:05:39So Bob Gray was my
• 01:05:41advisor.
• 01:05:42He's not that well known.
• 01:05:44You might not know of
• 01:05:44him. He's done some important
• 01:05:45papers in survival analysis. But
• 01:05:47what made him a good
• 01:05:48adviser for me was I
• 01:05:50was off on my own
• 01:05:51thing, out of sync with
• 01:05:52the department,
• 01:05:54interested in epi methods.
• 01:05:55And he was willing to
• 01:05:57meet with me and discuss
• 01:05:58papers that I was reading.
• 01:05:59All those papers by Prentiss
• 01:06:01and Breslow about survival data
• 01:06:03analysis
• 01:06:04and Poisson regression and different
• 01:06:06things that just were not
• 01:06:07being discussed at all in
• 01:06:09the Harvard Biostat department.
• 01:06:10I read the, book, The
• 01:06:12Analysis of Case Control Studies
• 01:06:14by Breslow from cover to
• 01:06:15cover. And I I could
• 01:06:16go to his office and
• 01:06:17say, how did they get
• 01:06:18from here to there? And
• 01:06:19he could always show me,
• 01:06:20like, what the logic was.
• 01:06:22So, that was great because
• 01:06:23I got a really good
• 01:06:24background in these things by
• 01:06:26doing this study with him.
• 01:06:27And then here are my
• 01:06:28other three committee members. You'll
• 01:06:30notice they're all men.
• 01:06:32In fact, there were very
• 01:06:33few women faculty at that
• 01:06:34time at all. Just Nan
• 01:06:36Laird in biostatistics,
• 01:06:38she was Fang's advisor, my
• 01:06:39friend Fang, and then Nancy
• 01:06:41Waller in epidemiology who was
• 01:06:42doing infectious disease epidemiology.
• 01:06:45Everybody else was male. And
• 01:06:47I think in other departments,
• 01:06:48they might not have even
• 01:06:49had any women, like environmental
• 01:06:50health, and I don't think
• 01:06:51they've had a woman had
• 01:06:53a woman for probably ten
• 01:06:54or twenty years. Anyway, so
• 01:06:56that was the situation. I
• 01:06:57know you guys are all
• 01:06:58seeing things very differently now.
• 01:07:00Here's my software page that
• 01:07:02shows the software we developed,
• 01:07:04those I just mentioned as
• 01:07:05well as many other things.
• 01:07:07So maybe I'll just end
• 01:07:08with motherhood because that's such
• 01:07:09an important part of my
• 01:07:11life. So,
• 01:07:12I was this is related
• 01:07:14to work and life.
• 01:07:16So I was six months
• 01:07:18pregnant when I started my
• 01:07:19job at the Harvard School
• 01:07:20of Public Health.
• 01:07:21I was afraid to tell
• 01:07:22anyone that I was pregnant
• 01:07:24because I was afraid I
• 01:07:25would lose my job. Don't
• 01:07:26forget I was also a
• 01:07:27lesbian. I wasn't married,
• 01:07:29and I was pregnant.
• 01:07:31Everyone thought that I was
• 01:07:32just gaining weight.
• 01:07:34In those days, there were
• 01:07:35no recruitment packages.
• 01:07:37So I was asked to
• 01:07:38teach epi two zero two
• 01:07:39b. It's the it's sort
• 01:07:41of intermediate epidemiology
• 01:07:43methods. My very first semester
• 01:07:45in the fall, which I
• 01:07:46was happily agreed to. After
• 01:07:48I started work, I told
• 01:07:49Demetrius Tricopoulous, who was the
• 01:07:51chair now, the late Demetrius
• 01:07:53Tricopoulous,
• 01:07:54that I was pregnant and
• 01:07:55due to go out on
• 01:07:56maternity leave in November. My
• 01:07:58daughter was due November thirtieth,
• 01:08:00you know, in the fall
• 01:08:01semester.
• 01:08:02He was completely gracious about
• 01:08:03it and told asked found
• 01:08:05Lucas Nius to step in
• 01:08:06on my behalf.
• 01:08:08So here are our two
• 01:08:09daughters, Nessarose Shearer and Ariela
• 01:08:11Shearer. They have Elaine, my
• 01:08:12ex wife's last name. I'm
• 01:08:14the birth mother.
• 01:08:16She was born on November
• 01:08:17thirtieth.
• 01:08:18She's now thirty two years
• 01:08:19old and works as an
• 01:08:20environmental educator for NatureBridge
• 01:08:22in Yosemite National Park and
• 01:08:24as a summer park ranger
• 01:08:26at Sequoia Kings Canyon National
• 01:08:28Park at the Charlotte Lakes
• 01:08:29Ranger Station, twelve miles from
• 01:08:31the nearest road. And Ariela
• 01:08:33was born October twenty fourth
• 01:08:34nineteen ninety six. She's twenty
• 01:08:36eight. She's graduating from Harvard
• 01:08:38Medical School in May and
• 01:08:40will then begin a residency
• 01:08:41in surgery. Well, she's hoping
• 01:08:43to stay in the Boston
• 01:08:44area and I hope she
• 01:08:45will as well.
• 01:08:46We raised our daughters in
• 01:08:47a Jewish home that was
• 01:08:49important to us. Like me,
• 01:08:50they both had bat mitzvahs,
• 01:08:52which were joyous family events,
• 01:08:53and we had a beautiful
• 01:08:55home.
• 01:08:56And I'll show you. These
• 01:08:57are just a few pictures
• 01:08:58from our home and our
• 01:08:59family having dinners, Thanksgiving dinners.
• 01:09:01Marge, I think you're right
• 01:09:03here, Marge. Yeah. And you
• 01:09:04might see some other people.
• 01:09:05I don't know if David
• 01:09:06was here.
• 01:09:07And then,
• 01:09:09you may all wonder, well,
• 01:09:10who is the father of
• 01:09:11these kids?
• 01:09:12So the father is here,
• 01:09:14Mike Wolfson.
• 01:09:15He's a senior research scientist
• 01:09:17at the Department of Environmental
• 01:09:19Health at the Harvard School
• 01:09:20of Public Health. He lived
• 01:09:21right down the street from
• 01:09:22us in Jamaica Plain. He's
• 01:09:24a very patient man. It
• 01:09:26took me two years to
• 01:09:27get pregnant with Nessarose, who
• 01:09:28I had at the age
• 01:09:29of thirty seven
• 01:09:30and Ariel at the age
• 01:09:31of forty one. So all
• 01:09:33of you women out there,
• 01:09:34there's much better technology
• 01:09:35now for delaying childbirth, but
• 01:09:37I even managed to get
• 01:09:39pregnant,
• 01:09:40you know, thirty plus years
• 01:09:42ago, with the technology we
• 01:09:44had at those ages.
• 01:09:46After some infertility treatments that
• 01:09:48didn't work, I went to
• 01:09:50a crystal healer
• 01:09:52at the advice of a
• 01:09:53woman I met at a
• 01:09:53Yiddish culture conference and got
• 01:09:55pregnant that month.
• 01:09:57So that's always a funny
• 01:09:58thing that I got pregnant
• 01:10:00with Nassau Rose because of
• 01:10:01a treatment from a crystal
• 01:10:02healer, me of all people,
• 01:10:04who is so scientific
• 01:10:06and data driven.
• 01:10:08So this is just a
• 01:10:09little bit about our family
• 01:10:11life and things that we
• 01:10:12did.
• 01:10:13Yeah. And then I have
• 01:10:14think I guess I should
• 01:10:15really wrap up. So this
• 01:10:16about the public schools, I
• 01:10:17was gonna tell you about
• 01:10:18the two state solution to
• 01:10:20the Israeli Palestinian
• 01:10:21conflict
• 01:10:22and teach about that. I
• 01:10:23think it's really important, especially
• 01:10:25now. I don't know. Should
• 01:10:26I take, like, two seconds
• 01:10:28to say? So,
• 01:10:30I was involved in a
• 01:10:31national Jewish peace movement called
• 01:10:33that
• 01:10:34became J Street. And my
• 01:10:36friend Debbie Elkin, who's here
• 01:10:37in the audience, was somebody
• 01:10:38who worked with me on
• 01:10:39that. She was chair of
• 01:10:40our New Haven chapter when
• 01:10:42I was in Boston. And
• 01:10:43I learned about the two
• 01:10:44state solution very early on
• 01:10:47and as a young adult.
• 01:10:48And the idea is that
• 01:10:49basically
• 01:10:50the overall land of Israel
• 01:10:52or Israel Palestine can be
• 01:10:53divided into a Palestinian state
• 01:10:56and a and a Jewish
• 01:10:57state of Israel. That was
• 01:10:58originally what happened in nineteen
• 01:11:00forty seven with the UN
• 01:11:01partition plan.
• 01:11:02So now, you know, many,
• 01:11:04many years later, this is
• 01:11:05a possible map that I
• 01:11:06took from the Internet where
• 01:11:07the green areas are the
• 01:11:09areas that could be the
• 01:11:10Palestinian state, where there's majority,
• 01:11:14Palestinian Arabs, very usually very,
• 01:11:16very high majority. You can
• 01:11:17see there's a little line
• 01:11:18here. That's the road between
• 01:11:20Gaza and the West Bank.
• 01:11:21You think, oh my god.
• 01:11:22How could a country be
• 01:11:23separated? That's it. I think
• 01:11:24it's not even more than
• 01:11:25an eighteen mile road. These
• 01:11:27are really small land masses.
• 01:11:29And you could also say,
• 01:11:30oh, but it's not fair.
• 01:11:31Look how much land Israel
• 01:11:32has compared to the Palestinians.
• 01:11:34But almost all of this
• 01:11:35down here is uninhabitable
• 01:11:37desert. So it's it's really
• 01:11:38we're just talking about this
• 01:11:39area around here where people
• 01:11:41can actually live. So that
• 01:11:43would be the idea in
• 01:11:44terms of how to divide
• 01:11:45up the land,
• 01:11:46and then there's other points
• 01:11:47that need to be resolved.
• 01:11:48One is Jerusalem.
• 01:11:50Jerusalem is very important to
• 01:11:51both the Jewish people, Israelis,
• 01:11:53Muslims,
• 01:11:54and Arabs, and the ideas
• 01:11:55that Jerusalem would be the
• 01:11:57divided capital of the two
• 01:11:58states. And there are extremely
• 01:12:00detailed maps, like, of every
• 01:12:02house and neighborhood about which
• 01:12:04one would go to Palestine
• 01:12:05and which one would go
• 01:12:06to Israel.
• 01:12:07So that's solvable. That's what
• 01:12:09I'm trying to say. And
• 01:12:10when we gave our talks,
• 01:12:11when we were doing this
• 01:12:12work, we'd say these things
• 01:12:13are solvable. It's not like
• 01:12:14this intractable thing that, oh,
• 01:12:17what are we gonna do?
• 01:12:18It's hopeless.
• 01:12:20Then the next issue is
• 01:12:21the settlement. So we know
• 01:12:22that there are Jewish settlements
• 01:12:24here in the West Bank.
• 01:12:25There aren't any in Gaza
• 01:12:26anymore, and let's hope it
• 01:12:27stays that way. But there
• 01:12:29are some here. Most of
• 01:12:30them are right on the
• 01:12:31border, the big ones. And
• 01:12:33so the idea is that
• 01:12:34there would be a land
• 01:12:35exchange, so the really big
• 01:12:36settlements could just be part
• 01:12:37of Israel, and then the
• 01:12:39Palestinian state would get an
• 01:12:40equal amount of land somewhere
• 01:12:42else to compensate for not
• 01:12:44evacuating
• 01:12:45fifty thousand settlers from a
• 01:12:47big settlement.
• 01:12:48And then the ones, these
• 01:12:49tiny little hilltop ones, those
• 01:12:50people will have to be
• 01:12:51evacuated.
• 01:12:53And then the last thing
• 01:12:54is the refugee issue. So
• 01:12:56the idea would be the
• 01:12:57Palestinians have a state and
• 01:12:59refugees will have the right
• 01:13:00to return to the Palestinian
• 01:13:02state.
• 01:13:03So that's the basic framework
• 01:13:04of the two state solution,
• 01:13:06and that's something we worked
• 01:13:07very hard on. There's also
• 01:13:09now people are talking about
• 01:13:10a twenty three state solution,
• 01:13:12which is,
• 01:13:13the two state solution is
• 01:13:14a subset of the twenty
• 01:13:15three state. Because the twenty
• 01:13:17three state is like, this
• 01:13:18is a regional issue. It's
• 01:13:19not just about Israel and
• 01:13:20Palestine, but it's about the
• 01:13:22twenty three countries of the
• 01:13:23Middle East.
• 01:13:25And ideally,
• 01:13:26they should, Israel should be
• 01:13:28normalized into the Middle Eastern
• 01:13:29region. Like, in the UN,
• 01:13:31I think it's it's part
• 01:13:32of Europe. It's not even
• 01:13:33part of the Eastern Mediterranean
• 01:13:35region because it doesn't get
• 01:13:36along with the other countries.
• 01:13:39But it would be a
• 01:13:40full regional solution with all
• 01:13:41twenty one states and a
• 01:13:43list. Israel would be one
• 01:13:44of them, and Palestine would
• 01:13:45be another, and Egypt would
• 01:13:46be one, and Jordan and
• 01:13:48so on. So that's the
• 01:13:49idea. And I'll just go
• 01:13:50down to the very end.
• 01:13:50I was gonna talk about
• 01:13:51my research and controversies with
• 01:13:54my research,
• 01:13:55but I will go and
• 01:13:56also what we're doing now.
• 01:13:58But I have I'll say,
• 01:13:59where will the journey go
• 01:14:00from here?
• 01:14:01So this is me, Ariela
• 01:14:03Neceros now. We were on
• 01:14:04the beach in Puerto Escondido
• 01:14:06in Oaxaca, Mexico at the
• 01:14:08end of December. And I
• 01:14:09just wanna say thank you
• 01:14:10to my family, including my
• 01:14:12daughters, the loves of my
• 01:14:13life, my friends, many of
• 01:14:15whom have been my by
• 01:14:16my side for over forty
• 01:14:17years, and all of you
• 01:14:19amazing colleagues here in the
• 01:14:21US and around the world
• 01:14:22with whom I've worked over
• 01:14:23the years and I'm working
• 01:14:24with now. And then again,
• 01:14:25I'm thanking Dean Vermaar, who's
• 01:14:27given me the opportunity to
• 01:14:29tell this story,
• 01:14:30and may the journey continue.
• 01:14:51Thank you so much, Donna.
• 01:14:55I don't know what to
• 01:14:57say. We don't wanna use
• 01:14:58this. That one wasn't working
• 01:14:59very well. Thank you.
• 01:15:02So thank you so much,
• 01:15:03Donna. And,
• 01:15:07I just know I I
• 01:15:08do not know. Standing in
• 01:15:10today's world, just hearing about
• 01:15:11identities
• 01:15:12is really hard,
• 01:15:15but I hope this space
• 01:15:16is
• 01:15:17safe enough and brave enough
• 01:15:19for all of us
• 01:15:20to express
• 01:15:21how we feel.
• 01:15:23So,
• 01:15:24as a, you know, woman
• 01:15:26who has worked in the
• 01:15:27academy
• 01:15:28twenty
• 01:15:29years later than you,
• 01:15:31just hats off,
• 01:15:33kudos,
• 01:15:34and thank you for what
• 01:15:35you did and how what,
• 01:15:37you know, people from
• 01:15:39past have done to bring
• 01:15:40us here.
• 01:15:41So progress is not just
• 01:15:43in one day and it
• 01:15:44is a continuous work in
• 01:15:45progress. So I I really
• 01:15:46thank you for that.
• 01:15:48Melody,
• 01:15:49I was hoping that you'll
• 01:15:51present this certificate of tribute
• 01:15:53to professor Spiegelman.
• 01:15:55And I'm sorry that we
• 01:15:56ran out of time to
• 01:15:57hear the last part. Maybe
• 01:15:59we can come back and
• 01:16:00journey lecture two point o
• 01:16:01with Donna Spiegelman. So, how
• 01:16:03many people will like that?
• 01:16:05Yes? Everybody in the audience?
• 01:16:07So yes? Oh. Yeah.
• 01:16:10And and and, you know,
• 01:16:12it's like, you know, respect,
• 01:16:13not really people when people
• 01:16:16come
• 01:16:17up to you with respect
• 01:16:18and admiring your strength,
• 01:16:20that's what the best moments
• 01:16:22for an academic are. So
• 01:16:23we all are I can
• 01:16:25speak from the on behalf
• 01:16:26of the ad audience that
• 01:16:27we are all here in
• 01:16:29awe and admiration of your
• 01:16:31courage and your strength and
• 01:16:32your conviction.
• 01:16:33And so Melody is going
• 01:16:34to present that,
• 01:16:36certificate to you, and maybe
• 01:16:37we can take a photo.
• 01:16:39With Melody. Yes.
• 01:16:41To be able to introduce
• 01:16:42you, and I'm privileged to
• 01:16:44give you this certificate of
• 01:16:45tribute. So thank you for
• 01:16:46everything that you do, and
• 01:16:48thank you for inspiring everyone
• 01:16:49for Lifetime. Thank you so
• 01:16:51much, Melody.
• 01:16:57But I can't anticipate pictures.
• 01:17:03Tony, you have
• 01:17:05okay.
• 01:17:07Those of you who joined
• 01:17:09us online,
• 01:17:10you know, well wishes and
• 01:17:12friends and admirers of Donna,
• 01:17:14thank you so much.
• 01:17:15I wanted to give you
• 01:17:16this
• 01:17:17melody because
• 01:17:19this these are some goodies
• 01:17:21because, yes, you have to
• 01:17:22when you do some work,
• 01:17:23you have to get rewarded.
• 01:17:25And there
• 01:17:26and every every person who
• 01:17:28grows up in India cannot
• 01:17:30say thank you without Cadbury's.
• 01:17:32So there is a Cadbury's
• 01:17:33chocolate in there.
• 01:17:35And for Donna, I have
• 01:17:36also something very special
• 01:17:38because I know that Donna
• 01:17:40likes books.
• 01:17:41So there is a very
• 01:17:43famous Bengali poet who is
• 01:17:45less known to the world.
• 01:17:47I worked really hard to
• 01:17:48get a old translation of
• 01:17:49that poet because I cannot
• 01:17:51read Bengali poems in English.
• 01:17:53Right? Like, that's that's weird.
• 01:17:54But,
• 01:17:55I found a translation, and
• 01:17:57this is for you with
• 01:17:58some Cadbury's chocolate as well.
• 01:18:00So thank you so much.
• 01:18:07I know that we are
• 01:18:09running out of time in
• 01:18:10terms of the formal presentation,
• 01:18:11but if you had any
• 01:18:13questions, because I think that
• 01:18:14this is a rare opportunity
• 01:18:15for students
• 01:18:16and colleagues to ask Donna
• 01:18:19some questions,
• 01:18:20I just open up the
• 01:18:21floor because there is nothing
• 01:18:22scheduled here, and I think
• 01:18:23it's important to allow that
• 01:18:25space. But if you have
• 01:18:26some other obligations, you're welcome
• 01:18:28to leave because we completely
• 01:18:29recognize that.
• 01:18:31And those of you who
• 01:18:33are online also, please feel
• 01:18:34free to ask questions or
• 01:18:35put it in the chat.
• 01:18:39Yes. Jeff.
• 01:18:42Jeff.
• 01:18:46That was lovely to hear,
• 01:18:47Donna. I have a question,
• 01:18:48and it sort of relates
• 01:18:49to a number of different
• 01:18:50parts of your talk.
• 01:18:52You've obviously gone through a
• 01:18:53couple different transitions from one
• 01:18:54thing to another. And one
• 01:18:56part that just really sort
• 01:18:57of fascinated me is how
• 01:18:58you ended up going into
• 01:19:00your PhD,
• 01:19:01more on the sort of
• 01:19:03epi side of things,
• 01:19:04getting a biocessed degree, and
• 01:19:06then immediately afterward becoming the
• 01:19:08theoretical partner to
• 01:19:10more epidemiology people who weren't.
• 01:19:11And I just wanted to
• 01:19:12I wondered if you could
• 01:19:13narrate a little bit about
• 01:19:14how that went for you.
• 01:19:15And and let me explain
• 01:19:16the reason why I'm asking
• 01:19:17that. The reason why I'm
• 01:19:18asking that is I think
• 01:19:19a lot of times people
• 01:19:21I mean, what's really admirable
• 01:19:23about that is how you
• 01:19:24embraced what you had recently
• 01:19:25learned, you know, relatively you
• 01:19:27know, not super late in
• 01:19:27your career, but relatively later
• 01:19:29in life and used it.
• 01:19:30And and it's a very
• 01:19:31important skill to take on
• 01:19:33as you move on through
• 01:19:34life to realize that just
• 01:19:36because you, you know, start
• 01:19:37start from here, you can
• 01:19:39learn this material and then
• 01:19:40be the resource for doing
• 01:19:41that. And I just wonder
• 01:19:42if you could speak a
• 01:19:43little bit to that, like,
• 01:19:44how it worked for you
• 01:19:45and how,
• 01:19:47other people might learn from
• 01:19:48your, experience doing that.
• 01:19:52I think it's not.
• 01:19:55Maybe I didn't convey well
• 01:19:57kind of what happened because
• 01:19:59soon as I got to
• 01:19:59the occupational health program,
• 01:20:02I was doing statistics,
• 01:20:04analyzing data, and then realizing
• 01:20:06that there were all these
• 01:20:07unanswered questions about statistical methods
• 01:20:09and methods that we needed.
• 01:20:11So whether I was in
• 01:20:12epi or biostat, it was
• 01:20:13always epi methods.
• 01:20:15Like, I'm not a environmental
• 01:20:17epidemiologist.
• 01:20:18I'm not a cancer epidemiologist.
• 01:20:20I know a lot about
• 01:20:21those things because I've worked
• 01:20:22on a lot of those
• 01:20:23studies,
• 01:20:24but where my real deep
• 01:20:25expertise is in is in
• 01:20:27statistical and quantitative methods for
• 01:20:29epidemiologic
• 01:20:30research
• 01:20:31and implementation
• 01:20:32science. And that actually never
• 01:20:33changed.
• 01:20:34So,
• 01:20:35it was confusing because say
• 01:20:37in some we don't have
• 01:20:38it here. But, like, in
• 01:20:39the Harvard epi department, there's
• 01:20:40like a sequence of epi
• 01:20:42methods courses that are and
• 01:20:44some of them are as
• 01:20:45rigorous, if not more quantitative
• 01:20:47courses in biostat.
• 01:20:49But in most other schools,
• 01:20:51all the quantitative stuff is
• 01:20:52in the biostat, and then
• 01:20:53the epi department focuses on
• 01:20:55the domain areas, like environmental,
• 01:20:57infectious, whatever. But that wasn't
• 01:20:59the case. So, anyway, I
• 01:21:00was always doing epi methods,
• 01:21:02quantitative methods related to epidemiologic
• 01:21:06research and the uses of
• 01:21:08biostatistics
• 01:21:09to develop epi methods.
• 01:21:15Is there a question online?
• 01:21:19Sure. Can you hear me
• 01:21:20okay?
• 01:21:21Yes, Stan. We are welcome
• 01:21:24back. Thank you. Donna,
• 01:21:26it it wasn't
• 01:21:27more than a few months
• 01:21:29after you and I were
• 01:21:30hiking
• 01:21:31after a meeting at Swatini.
• 01:21:32We were hiking in the
• 01:21:33mountains.
• 01:21:35I'm sure you remember that
• 01:21:36as well as I do.
• 01:21:37And then a few months
• 01:21:38later, you had a shocking
• 01:21:40cardiac event.
• 01:21:42And I wonder if you
• 01:21:43would just tell the audience
• 01:21:44how that
• 01:21:45what your thoughts were about
• 01:21:47your life, about your career,
• 01:21:49about your family after that
• 01:21:50life threatening event.
• 01:21:53Okay. Yeah. So I had
• 01:21:54left that unpleasant memory out,
• 01:21:57but, you know, it is
• 01:21:58still very much part of
• 01:21:59my life. So as you
• 01:22:00all know, I'm about to
• 01:22:01be seventy. And, when I
• 01:22:03came to Yale,
• 01:22:04in February of twenty nineteen,
• 01:22:07I had a heart attack
• 01:22:08in my office. Just it's
• 01:22:10Albert Coe's office now. That
• 01:22:12was my office, and I
• 01:22:12had a heart attack there.
• 01:22:14And, I had no heart
• 01:22:15disease. It was a congenital
• 01:22:17aneurysm
• 01:22:18of my left descending artery
• 01:22:20that kind of bubbled up
• 01:22:21and then caused a clot
• 01:22:22and then caused a heart
• 01:22:23attack. And luckily, because I
• 01:22:25was, you know, literally three
• 01:22:27to five minutes away from
• 01:22:29the emergency room of Yale
• 01:22:30Hospital, I was taken right
• 01:22:32over there,
• 01:22:33and they I had a
• 01:22:34CABG, open heart surgery in
• 01:22:36a CABG. And then,
• 01:22:38I had cardiac rehab and
• 01:22:40so on. And,
• 01:22:41I, was out, I think,
• 01:22:43for maybe two months or
• 01:22:44maybe even two and a
• 01:22:45half months
• 01:22:46recovering. I mean, it was
• 01:22:47horrible. It's absolutely horrible.
• 01:22:49And, you know, you just
• 01:22:50have to just like my
• 01:22:52mother with her blindness and,
• 01:22:54you know, as we all
• 01:22:55get older, like, all kinds
• 01:22:56of things happen and you
• 01:22:58just make the best of
• 01:22:58it. You know, some people
• 01:22:59have had cancer.
• 01:23:01You know, you try to
• 01:23:02get better. You try to
• 01:23:03I have to take lots
• 01:23:04of medicines every day and
• 01:23:05I don't like doing it,
• 01:23:06but I do it. I
• 01:23:08try to stay in shape.
• 01:23:09I try to keep my
• 01:23:09weight down. I try to,
• 01:23:11eat healthy and try to
• 01:23:13just enjoy this most of
• 01:23:15my life as I possibly
• 01:23:16can and not be dragged
• 01:23:17down by the fact that
• 01:23:18I've had some health challenges.
• 01:23:24Thank you. Any other questions?
• 01:23:33So I have one question.
• 01:23:35Hi. So
• 01:23:37if you had
• 01:23:38one month, the next month
• 01:23:40of your calendar without any
• 01:23:42meetings,
• 01:23:44in that in that utopian
• 01:23:46world,
• 01:23:47what did you spend the
• 01:23:48next month on?
• 01:23:50Well, Archana knows the answer
• 01:23:52to this.
• 01:23:53So we have,
• 01:23:55been working,
• 01:23:56around the world in developing
• 01:23:58programs and strategies for reducing
• 01:24:01cardiometabolic
• 01:24:03risk and lowering hypertension.
• 01:24:05And, we have a group
• 01:24:07of colleagues
• 01:24:08from,
• 01:24:09India, Nepal,
• 01:24:10Bangladesh,
• 01:24:12China, and Malaysia,
• 01:24:14where we're putting together a
• 01:24:15program project,
• 01:24:17to, kind of have a
• 01:24:18consolidated development of such a
• 01:24:20program that could be scaled
• 01:24:22up, and we're gonna use
• 01:24:23Lago
• 01:24:23to,
• 01:24:25fine tune the elements of
• 01:24:26the program as we go
• 01:24:28along. We're gonna look at
• 01:24:29spillover,
• 01:24:30and we were given you
• 01:24:31have to write a letter
• 01:24:32of request to NHLBI
• 01:24:34to
• 01:24:35submit a program project, and
• 01:24:36we went back and forth
• 01:24:37with them a bunch of
• 01:24:38times. But we were invited
• 01:24:39to submit the application,
• 01:24:41and that application is due
• 01:24:43May twenty fifth.
• 01:24:45So if I had a
• 01:24:46month, I would just work
• 01:24:47on this program project. That's
• 01:24:48a very nerdy answer. You
• 01:24:50probably weren't wanting to hear
• 01:24:51it. No. No. No. No.
• 01:24:52No. No. Honesty
• 01:24:54honesty is appreciated. So this
• 01:24:55is who you are.
• 01:24:57So on that note,
• 01:25:00on this wonderful afternoon, let
• 01:25:01us just celebrate who we
• 01:25:03are and have the courage
• 01:25:05to say that this is
• 01:25:06who we are as statisticians
• 01:25:08and as humans. And,
• 01:25:10thank you for your candor.
• 01:25:11Thank you for your
• 01:25:13braveness,
• 01:25:14and thank you for all
• 01:25:15the intellectual developments that has
• 01:25:18advanced our field.
• 01:25:20And I wish you and
• 01:25:21your loved ones and your
• 01:25:22beautiful daughters all the best.
• 01:25:24Thank you so much, everyone.