Yale Psychiatry Grand Rounds: February 11, 2022

Transcript

• 00:00I'm very pleased to introduce
• 00:03Professor Betsy Levy Paluck to give
• 00:06the annual lecture for the Division
• 00:07of Prevention and Community Research.
• 00:09Doctor Pollack is professor and acting chair
• 00:12of psychology at Princeton University,
• 00:14where she is also professor of public
• 00:16affairs and the faculty associate
• 00:18in the Department of Politics.
• 00:19She also serves as deputy director of the
• 00:22common Treatment Center for Behavioral
• 00:24Science and Policy at Princeton.
• 00:26After completing her undergraduate and
• 00:28doctoral degrees in psychology at Yale,
• 00:30she spent two years as an Academy
• 00:32scholar at Harvard.
• 00:33Before joining the faculty at Princeton,
• 00:35where she has remained ever since.
• 00:38Doctor Pollack is a leading researcher on
• 00:40prejudice and intergroup conflict reduction.
• 00:42Conducting her research using field
• 00:44experiments in the US and Africa,
• 00:46and focusing on mass media and
• 00:49interpersonal communication.
• 00:50Much of our research has examined
• 00:52social norms and group influence
• 00:54through peers and role models.
• 00:56Narrative communication,
• 00:57and group discussion as a vehicle
• 01:00for behavior change her research
• 01:02on social norms and social networks
• 01:04has identified strategies for
• 01:06reducing discrimination,
• 01:07as well as bullying and ethnic conflict.
• 01:09In various contexts,
• 01:10including American high schools
• 01:12and post conflict, Rwanda.
• 01:14Her translation of theories
• 01:16and social psychology,
• 01:18which are usually developed and
• 01:20tested in laboratory experiments
• 01:22into real-world interventions and
• 01:23randomized control of field experiments,
• 01:25has resulted in discoveries of
• 01:27new ways to positively influence
• 01:30individual and group behavior.
• 01:32Doctor Pollock is the author of
• 01:34numerous publications and the
• 01:35recipient of many honors and awards,
• 01:37including an early career award from
• 01:39the Society for the Study of Peace,
• 01:42Conflict,
• 01:42and Violence with the American
• 01:45Psychological Association and in two
• 01:472017 selection as a MacArthur Fellow,
• 01:49which involves recognition as one
• 01:52of 24 talented individuals showing
• 01:54extraordinary originality and
• 01:56dedication in creative pursuits.
• 01:58As activists, artists,
• 02:00scholars or scientists and receiving
• 02:02an unrestricted fellowship.
• 02:04For five years from the Kathryn D
• 02:06from the John D and Catherine T.
• 02:08MacArthur foundation.
• 02:09In addition to MacArthur funding, Dr.
• 02:12Pollack has been funded by the
• 02:14National Science Foundation,
• 02:15the Canadian Institute for Advanced Research,
• 02:17and numerous foundations,
• 02:19including WT, Grant, Russell,
• 02:21Sage Spencer and Guggenheim.
• 02:23We are very pleased to have her talk
• 02:25with us today about prejudice reduction,
• 02:27progress and challenges.
• 02:29Doctor Powell.
• 02:32Thank you so much for that welcome.
• 02:34I'm really excited to be here. You know I am.
• 02:39When about two years ago when I completed
• 02:42this manuscript that I'm going to
• 02:44talk to you about today, I hit send.
• 02:47We went into lockdown a few days
• 02:49later and a few days later,
• 02:52after that I had a baby and I really had
• 02:55no idea that I would be able to share
• 02:58this paper with as many audiences as I have.
• 03:01I, I just couldn't expect that
• 03:03zoom would allow me to do this,
• 03:05and that's a silver lining
• 03:07for me like this right now.
• 03:09There's a silver lining.
• 03:10Despite all of the isolation
• 03:13that came afterward.
• 03:14Because this is a paper that
• 03:16I feel so strongly about,
• 03:18and to me it it it's a circling back of
• 03:25a broad look that I took at the prejudice
• 03:27reduction field very early in my career.
• 03:29And I'll tell you about about why
• 03:31that is so I'm I'm also just really
• 03:33excited to be here because this
• 03:35is the first psychiatry audience
• 03:36I've presented to on the topic.
• 03:38And that's just really meaningful for me.
• 03:41I love presenting to lots
• 03:43of different audiences,
• 03:44and this paper has been taken out
• 03:46over the course of the pandemic
• 03:48to many different audiences,
• 03:49and I've had really interesting
• 03:51feedback from them,
• 03:52and I really look forward
• 03:53to your feedback as well.
• 03:54So thanks again for having me.
• 03:57I want to start out by acknowledging
• 03:59my Co authors on the paper.
• 04:01Ronnie Parrot,
• 04:02who is on the left hand side and is a
• 04:05professor at Hebrew University Chelsea Clark,
• 04:07who is an absolute star graduate student.
• 04:11So watch that space for
• 04:13Chelsea and Donald Green,
• 04:15who was my mentor at Yale and he was in the
• 04:18political science department at the time.
• 04:21You know, of course,
• 04:22he's my forever mentor now and we
• 04:25recently as I as I just mentioned,
• 04:27so we we.
• 04:28Published this paper called the
• 04:29Prejudice Reduction Progress and
• 04:31Challenges in the annual review of
• 04:33psychology and in this paper we're
• 04:36asking what works to reduce prejudice,
• 04:39and this was a paper that I wrote.
• 04:41This was a a calling back to a
• 04:44previous paper that I wrote with Don
• 04:45my advisor as a graduate student,
• 04:47and it was inspired when Don was
• 04:50teaching a course on political
• 04:52intolerance and hate crime,
• 04:54and I was his TA from the psychology
• 04:56department and.
• 04:57He said to me, you know,
• 04:59we're going to spend a long time
• 05:01going over the the political and
• 05:04social and economic conditions that
• 05:07lead to intolerance to to hate crime.
• 05:09It's a.
• 05:10It's a fairly stern and depressing slog,
• 05:13and I like to end on, you know,
• 05:16some notes of promise.
• 05:17So what do we know about about
• 05:19reducing prejudice and and it's
• 05:22behavioral expressions from psychology?
• 05:24I said no problem, I've got you.
• 05:27You know our field was.
• 05:28You know in part founded around this,
• 05:30there is such a such a big
• 05:32field prejudice reduction.
• 05:33I'll come back with some really
• 05:35convincing papers and he said,
• 05:36you know, to be convincing.
• 05:37I would like them to have
• 05:39some causal identification.
• 05:40I would like them, you know,
• 05:42to have some behavioral measurement,
• 05:44not just attitudinal.
• 05:45I said got it, and I found that
• 05:48the search was a lot harder than
• 05:49I thought it would be that I had.
• 05:51Maybe some unfounded optimism
• 05:53in in what we had found so far
• 05:55in the psychology literature.
• 05:57And so I just kept searching and
• 05:59it ended up in this mega paper,
• 06:01in which we essentially hoovered
• 06:03up all that there was not just
• 06:05in the field of psychology,
• 06:06but in all of the social sciences.
• 06:08The the policy literature,
• 06:10the grey literature.
• 06:11So we were searching for,
• 06:12published and unpublished,
• 06:13and even across the biomedical sciences,
• 06:15to ask you know, what, what,
• 06:17what's being done in many,
• 06:18many different fields.
• 06:19It resulted in this paper,
• 06:21which was really a narrative review
• 06:24because there were so many studies out there.
• 06:27That were quite descriptive and
• 06:29descriptive of really interesting
• 06:31ideas on how to reduce prejudice,
• 06:33but the evidence and this is
• 06:35what we argue in this paper,
• 06:38was depressingly thin,
• 06:39particularly for this question
• 06:41that I've put here up at the top.
• 06:44What works to reduce prejudice?
• 06:45What?
• 06:46What can cause reductions in attitudes,
• 06:49emotions, norms,
• 06:51or particularly behaviors?
• 06:52And so the call that we put
• 06:55in this paper was.
• 06:57To see more experimentation that
• 06:59could tell us something about
• 07:01causal inference and to see it
• 07:03out in the field to see whether
• 07:05behavior could change in that rich
• 07:07thicket of reality out there.
• 07:09And and you know,
• 07:11particularly whether these
• 07:12programs could be successful in
• 07:14the places they were intended for,
• 07:17so we were less interested in the in
• 07:20the proof of concept as small lab studies.
• 07:23But that that was the call that we put out,
• 07:24and so now it's 12 years later and I
• 07:27have a lab of my own with students of my own,
• 07:30and it almost became a personality test
• 07:32for us as we started discussing this,
• 07:34Ronnie was the postdoc in my lab at the time.
• 07:36Chelsea was a new graduate
• 07:38student and we said,
• 07:39you know,
• 07:39do we think the field has changed since this
• 07:42this call to arms in the in the last paper?
• 07:44I shouldn't say call to arms it's senses.
• 07:46You know this Clarion call or
• 07:48this this this encouragement,
• 07:49right?
• 07:49So we decided to review the
• 07:51literature again going back that.
• 07:53The past number of years since
• 07:55we published that paper.
• 07:56OK,
• 07:56so that's my that's the
• 07:57history of this paper,
• 07:59and we decided to ask three
• 08:01questions in this paper.
• 08:02So what's happened in the last dozen years?
• 08:05What are the average effects
• 08:06of the interventions?
• 08:07So in my last paper in our last paper,
• 08:10we used studies that were
• 08:12purely qualitative all the
• 08:14way to purely quantitative,
• 08:16and we decided to really
• 08:18focus on studies this time
• 08:20that had quantitative measures so that we
• 08:23could have calculate an average effect.
• 08:25We also decided to focus on experiments
• 08:27so that we could really focus in on
• 08:29what do we know about causal effects.
• 08:32And then finally the third
• 08:33question that this paper poses.
• 08:35Can social science answer the public
• 08:37call to reduce prejudice in the world?
• 08:39And since I just gave you the timeline of
• 08:42of when I hit send on the final draft,
• 08:45you know that the the the public
• 08:48school got a lot louder.
• 08:50As as we were publishing this paper,
• 08:53and so the stakes seemed to be appropriately
• 08:56high for asking this question of
• 08:58how do we answer that call, right?
• 09:01I have the social sciences and the
• 09:03biomedical sciences responded in
• 09:05a way that we're here for them.
• 09:07With effective programming and
• 09:09effective social science,
• 09:11social change theories when when
• 09:13it's actually being asked for.
• 09:16OK, so I'm just going to give you the
• 09:18answers to all of these questions right
• 09:19now and then I'll spend the rest of my time.
• 09:21Defending them with data
• 09:23and see what you think.
• 09:24So the first answer there's been an
• 09:27uptick in prejudice reduction research.
• 09:29Some of this research is just
• 09:31going to become classic.
• 09:32It's going to be taught
• 09:33in the social sciences,
• 09:34not just in classes that focus
• 09:38specifically on on conflict or prejudice
• 09:41or or intolerance and hate crimes.
• 09:44But everywhere because these
• 09:46papers are just really these,
• 09:47these research projects are just phenomenal,
• 09:49and I'm going to tell you
• 09:50about some of them today.
• 09:52However,
• 09:52the modal research is very different
• 09:55from these future classics.
• 09:58See, that's partly mathematical.
• 09:59Of course,
• 09:59the mode has to be different
• 10:01from the outliers,
• 10:01but there's ways that I want to
• 10:04characterize modal research and even
• 10:06the majority of the research that
• 10:08really give me and us great pause in
• 10:10recommending some of these strategies,
• 10:12and in particular some of the most
• 10:15popular prejudice reduction ideas out
• 10:17there treasured by the lay public,
• 10:20but also scientists alike.
• 10:21We actually don't find that
• 10:23much support for them, right?
• 10:24So I'm going to be presenting
• 10:26on what I want to.
• 10:28Underline as an absence of evidence
• 10:30is not evidence of absence, right?
• 10:32So we're not finding as much
• 10:34backlash effects as just gaps.
• 10:36And then finally,
• 10:37and I think this is the sourest note,
• 10:40the most rigorous research in this review
• 10:43shows very small reductions in prejudice.
• 10:46OK?
• 10:48So from there and in the paper,
• 10:51we ask well what should the next
• 10:53generation of prejudice reduction
• 10:55research look like based on this?
• 10:57And then in the most editorial
• 10:59touch to this talk I want to
• 11:01speak at the end on whether we're
• 11:02using the right model of change,
• 11:04it's going to be a very evidence driven talk.
• 11:07This is just going to be my opinion and
• 11:08and our opinion as a as an author group,
• 11:11so I'll get to that at the end.
• 11:13And that's where I especially
• 11:15invite your feedback.
• 11:16OK, so now the evidence
• 11:17for what I just argued.
• 11:19First, there is an increase in
• 11:21most types of prejudice reduction
• 11:22research that black line at the
• 11:24top shows any kind of research.
• 11:26This is broken down by methodology,
• 11:28but I could do this for in a
• 11:29number of different ways and I'll
• 11:31start showing you that later.
• 11:33You see that it's mostly driven
• 11:34by studies that are taking place
• 11:36in the scientific lab or online
• 11:38and online studies really take
• 11:40off people running studies on.
• 11:43M Chirk and prolific doing online
• 11:47brief interventions that Orange
• 11:49Line measuring field experiments is
• 11:51toggling down at the bottom about,
• 11:53you know, 023 or 4 experiments per year.
• 12:01We used this is a a Prisma diagram just
• 12:04to show you that how did we come about?
• 12:08All of these studies?
• 12:09Well it's a very transparent process.
• 12:11We we followed biomedical meta analytic
• 12:13standards and you can see all of our studies.
• 12:16All of our code and you know Prisma
• 12:18diagrams that show you how we make
• 12:20decisions about inclusion in our study
• 12:21throughout the entire thing it's up
• 12:23on dataverse for any of you who are
• 12:26interested but just to take you briefly
• 12:28and narratively through that process.
• 12:30We searched through five separate
• 12:31databases to find all of the studies
• 12:34that are in this meta analysis.
• 12:36Four of them are open to all,
• 12:37one is a proprietary Princeton
• 12:40based text based search.
• 12:41Although we be include all of the keywords
• 12:44that we use in the text based search,
• 12:46these searches led to 16,000 results,
• 12:49non unique results that we spent
• 12:52one robust summer reviewing in full
• 12:55with a team of Masters students
• 12:57and then we we identified.
• 13:00About 1800 that were eligible,
• 13:02the Pi team read all of those
• 13:04and the criteria we had in mind.
• 13:06Very broad for the definition of prejudice.
• 13:09So we just described it as animus
• 13:11and it could be expressed in terms of
• 13:14an emotion and attitude of belief,
• 13:16a behavior we do not include sexism
• 13:19in this review in part just following
• 13:22the previous review standard.
• 13:24I can talk a little bit about that.
• 13:26You know why we made that decision in
• 13:28the first review? You know in part.
• 13:30I can say it's because these literatures
• 13:32are are surprisingly separate in
• 13:34their theoretical orientations,
• 13:35but but I can also answer more
• 13:37questions about that.
• 13:38We didn't review what is now being
• 13:42called affective polarization,
• 13:43and that is to say partisan bias.
• 13:45Bias and prejudice between Democrats and
• 13:48Republicans. But that's a literature.
• 13:49As you probably know, that's on the rise.
• 13:51So keep your eye on that literature.
• 13:53We also left out,
• 13:54you know some of the toy prejudices
• 13:56that that psychologists,
• 13:58social psychologists like to play with.
• 13:59So you're not going to see any studies.
• 14:00One year at testing prejudice from
• 14:03you know Ohio State students versus
• 14:06Michigan students.
• 14:07OK, and they all had to be experimental,
• 14:10so there had to be a random assignment
• 14:12to treatment and control or placebo
• 14:13so that we could understand the
• 14:15direction of effects and and causality.
• 14:17OK,
• 14:17so in our final sample we have 300
• 14:19and manuscripts and 418 experiments
• 14:21and we coded all of them.
• 14:23I want to tell you that if any
• 14:25of you use Instagram,
• 14:27this is like using the like gently.
• 14:31Filter the most flattering
• 14:32filter on the field,
• 14:33because when we took the quantitative
• 14:35data from these studies,
• 14:37we just let authors suggest to us what
• 14:39were their top most important outcomes
• 14:41so we would look at their abstract
• 14:44to see what they were featuring.
• 14:46As we know authors like to feature their
• 14:49most promising findings in the abstract,
• 14:52so we let the authors tell us.
• 14:55Does this mean that we might not
• 14:56be capturing some negative effects?
• 14:58It might so you know any.
• 15:01If anything, this meta analysis is
• 15:03giving you maybe a positive bias
• 15:05on on the fields, but that's how
• 15:08we chose quantitative findings.
• 15:09We chose 5 up to five outcomes
• 15:12from each study and average them.
• 15:14And then we also quoted them
• 15:16qualitatively so that we can tell you
• 15:18about the theoretical orientations
• 15:20of these papers and other types of
• 15:23features of their interventions and
• 15:25their study populations and so forth.
• 15:28OK, next points that I now next
• 15:30conclusion that I argued to you several
• 15:32of them are destined to become classics.
• 15:35Why, what?
• 15:36What do we like about studies so number one,
• 15:39their interventions are robust,
• 15:42their interventions that you could take
• 15:44to a community or an organization.
• 15:47A student group tomorrow if you wanted to.
• 15:50What that means is that they typically
• 15:53are aware of and have anticipated social,
• 15:56sometimes even political as well
• 15:58as psychological processes.
• 16:00In terms of trying to affect participants,
• 16:03and they're well described.
• 16:06They also use extremely robust methods,
• 16:08right?
• 16:08And so here's where I'm going to preview
• 16:11some complaints that we have later.
• 16:13These studies,
• 16:13by contrast to many others,
• 16:15have very large sample sizes.
• 16:17They typically measure behavior
• 16:19as well as attitudes or beliefs.
• 16:22There's a lot of attention to randomization.
• 16:24People are dropping out.
• 16:25They use appropriate econometric
• 16:27methods to address attrition.
• 16:30They've pre registered their their tests,
• 16:34and they use open data.
• 16:37So here's an interesting thing.
• 16:39We identify this group of studies
• 16:41so that we just think are absolutely
• 16:43terrific and they actually come from
• 16:45very different theoretical backgrounds
• 16:47and approaches, which is quite nice,
• 16:50despite the fact that they're all
• 16:51very different from one another.
• 16:53They all have promising positive
• 16:56but very small.
• 16:59Sexercises OK,
• 16:59so that's something to flag right away.
• 17:02Well,
• 17:02let me tell you about a few.
• 17:04One thing I want to tell you right
• 17:06away is that almost every single
• 17:08one was led by a doctoral student
• 17:10that is just so amazing.
• 17:12I mean,
• 17:13we faculty have no excuse on the one hand,
• 17:16the future is bright.
• 17:17On the other hand, wow,
• 17:18they're they're leading the way.
• 17:21Here are two studies that I want
• 17:23to tell you about that tests
• 17:24the effect of contacts, right?
• 17:26So the vaunted contact hypothesis, in which.
• 17:29And contact under certain
• 17:31conditions like cooperation,
• 17:32equal status, a common purpose and.
• 17:36You know, sort of authorities.
• 17:38Legitimization can reduce prejudice
• 17:41and and one treasured site for
• 17:46testing contact is team sports.
• 17:50There's a lot of programming around this.
• 17:52First of all,
• 17:53I've done a meta analysis of contact
• 17:55in the past and I want to tell you
• 17:57that we know a lot less about it.
• 17:59Its effects than we think we do,
• 18:02especially for policy outcomes,
• 18:04but these two studies stepped in to
• 18:06fill some of those gaps quite beautifully.
• 18:09Salma Moussa,
• 18:10in northern Iraq,
• 18:11organized a Soccer League between
• 18:14Christian and Muslim players.
• 18:16This isn't a Christian area,
• 18:18and so Muslims are the minority in that area,
• 18:21and they were randomized to be
• 18:23either on your team as a Christian
• 18:25player or on the opposite team so
• 18:27that she could test the idea of.
• 18:29Is it about contact?
• 18:30Do you need to be cooperating on the same
• 18:33team and then tested various outcomes,
• 18:35not only prejudice towards Muslims,
• 18:38but also ideas about policy and
• 18:41inclusiveness in policy and behaviors
• 18:43such as would you use a voucher given
• 18:47to you to eat at a Muslim restaurant
• 18:49in a Muslim neighborhood following
• 18:50your experience on the Soccer League?
• 18:55Completely independently,
• 18:55but at the same time and and
• 18:58equally brilliantly Matlow a
• 19:00doctoral student in economics went
• 19:02to India and organized cricket
• 19:03leagues for a low and high caste.
• 19:06Men doing the much the same
• 19:09kind of randomization.
• 19:10Also looking at things like would
• 19:14would men actually punish themselves
• 19:16and so it's very economic style.
• 19:18Measurement of behavior.
• 19:20Would men actually sort of
• 19:22inefficiently trade if they were given?
• 19:24Resources such as new sandals,
• 19:27mismatched sandals.
• 19:28Would they go to the lengths of trading
• 19:31with a low caste person to to get the
• 19:34right the right match for their sandal?
• 19:37Or would they discriminate and
• 19:38and get less good matches by by
• 19:41trading only with higher caste men.
• 19:42So really convincing interesting outcomes,
• 19:46behavioral outcomes and so forth.
• 19:49OK, another study that we just
• 19:51want to highlight as really robust.
• 19:54This study was done by a political
• 19:57science doctoral student who was
• 19:59interested in theories of confrontation.
• 20:01So does confronting a person
• 20:04who has done something racist?
• 20:07Does it work and does it work
• 20:08over the long term?
• 20:09And this was done on Twitter back when bots
• 20:13were not as widely recognized, a phenomenon.
• 20:16So it was, you know.
• 20:18Probably not something that can repeat.
• 20:21Can be repeated in the exact same form today,
• 20:24but it's an elegant 2 by two design
• 20:26in which first the student went
• 20:29online to find white men identified
• 20:31as white men by their avatars.
• 20:33Who would use the N word as a
• 20:36racial slur in the past week?
• 20:38Those those actual Twitter users
• 20:41were then randomly assigned to
• 20:43have a tweet tweeted at them by an
• 20:46avatar who was either identified
• 20:48by their picture as black or white
• 20:51and as high or low status.
• 20:52I put in quotes as identified
• 20:55by their number of followers.
• 20:57So either having a large following or
• 21:00small following and the tweet that
• 21:02that was sent to them from one of
• 21:04these users essentially said to them,
• 21:06you know you have to watch what
• 21:07you're saying. That's an incredibly.
• 21:10Hurtful word and that's you know.
• 21:12And so they they confronted them
• 21:13on the use of the word,
• 21:14and then monger actually just follows
• 21:17those users to see if they essentially
• 21:20recidivate if they use the word
• 21:22again and how long into the future
• 21:25does the effect of that confrontation last.
• 21:28She got long term measurement.
• 21:30Also open data.
• 21:31Everything was pre registered.
• 21:33This is quite heroic experiment.
• 21:38Diversity training and
• 21:40online diversity training.
• 21:41Short online diversity training
• 21:43used by a global corporation,
• 21:45and so done with the kind of
• 21:48sample that you really want.
• 21:51Enormous sample,
• 21:51one of the only samples in this meta
• 21:54analysis that could so convincingly
• 21:56analyze heterogeneous effects.
• 21:57That is,
• 21:58for whom did this online training work?
• 22:00If anyone,
• 22:01and I'm not telling you the
• 22:02results of all of these studies,
• 22:04'cause we'll get to that later.
• 22:05But one thing I just want to flag
• 22:07here is that some of what you suspect
• 22:10about diversity training maybe
• 22:12seem to come true in this study,
• 22:13which is that first of all part of
• 22:16the heroism of the study was that
• 22:19the authors actually had to create.
• 22:21Behavioral opportunities to see whether
• 22:26the employees of this company would
• 22:27take them up following the diversity
• 22:29training 'cause it turned out the
• 22:31company was not tracking the types of
• 22:33behaviors that we might be interested
• 22:35in and couldn't for legal reasons,
• 22:37share others like promotion and
• 22:39and and retention and so forth.
• 22:42So what they did was they measured
• 22:44following this online training.
• 22:45Did employees sign up for mentoring
• 22:49hour to mentor underrepresented?
• 22:52Members of the of underrepresented
• 22:55employees of the company,
• 22:58which for this company included
• 23:01women and and underrepresented
• 23:04in Minoritized employees.
• 23:07What they find is it's actually women and
• 23:10minoritized employees who are the ones
• 23:13who sign up for this this coffee hour.
• 23:15This mentoring hour to mentor
• 23:18others following this training.
• 23:20OK, so those are a few of what we called
• 23:22in the paper are landmark studies.
• 23:24There are more and I really encourage
• 23:25you to go and read about them,
• 23:27'cause they're just real feats,
• 23:29creative and and and brave.
• 23:32But the modal type of research
• 23:33is very different,
• 23:34and that's what I argued
• 23:35to you in the beginning.
• 23:36Why?
• 23:36Well,
• 23:37first of all,
• 23:37let me just describe all the
• 23:39different kinds of research that
• 23:41is in this meta analysis and these
• 23:45are categories that we created.
• 23:48There are types of interventions.
• 23:51In the meta analysis that you
• 23:53know fall under some of these,
• 23:55you know buckets these categories
• 23:57that we created and a couple of
• 23:59things I want to point out to you.
• 24:00First of all,
• 24:02that top bar that that represents a
• 24:05third of all activity in prejudice
• 24:07reduction over the past dozen years is
• 24:10called extended and imaginary contact.
• 24:12Now if you don't know what that is,
• 24:14it's it's an intellectual development in
• 24:16the in the study of intergroup contact,
• 24:19that's quite stunning.
• 24:21Basically the the the move that's
• 24:23been made in that literature over the
• 24:25past dozen years has been to say we
• 24:28have so much research on interpersonal
• 24:30contact and you can see down below.
• 24:32We think that face to face contact
• 24:34might not even be necessary anymore.
• 24:36So extended contact is knowing that
• 24:39one of your friends and your social
• 24:42network has a contact with an out
• 24:45group member and imaginary contact is
• 24:48exactly as it sounds it involves for example.
• 24:51White American being asked to
• 24:53imagine a conversation or contact
• 24:55with a black American right,
• 24:57so it's it's quite a notable thing that you
• 25:01know that's where the intervention is gone.
• 25:04You know, in the last dozen years,
• 25:06and it takes up 33% of all
• 25:08of our of our energies,
• 25:09or roughly 33%.
• 25:10Now the zoom bar is on my on my X axis,
• 25:14so I can't see the next category.
• 25:17Is cognitive and emotional training,
• 25:19and this includes many different types
• 25:22of psychological techniques for trying
• 25:25to encourage people to self regulate
• 25:27and rethink their biases.
• 25:30So cognitive training includes things
• 25:32like trying to suppress implicit.
• 25:34In automatic biases,
• 25:36emotional training addresses ways too.
• 25:41To regulate emotions like guilt
• 25:44or fear or shame in with respect
• 25:48to thinking about group members,
• 25:50social categorization is the next
• 25:52most frequent kind of intervention
• 25:54and it involves trying to
• 25:56rethink group boundaries and so,
• 25:58thinking about subordinate categories
• 26:00instead of dividing us up into fractional
• 26:03minority versus majority groups
• 26:05or dominant versus oppressed, etc.
• 26:08OK, so those are the most
• 26:10common types of interventions.
• 26:12And what I really want to point out here,
• 26:14and I'm mindful that I'm saying this to a
• 26:16group of people in a psychiatry department,
• 26:18is that the energy of the past dozen years
• 26:20has all been about prejudice reduction
• 26:23through mentalizing through our mental lives.
• 26:26OK, and I don't present
• 26:28that to you as good or bad.
• 26:30But those three top categories were
• 26:33all about an individual strategy
• 26:36for rethinking or imagining.
• 26:41You know conditions under which there
• 26:43should be less bias and prejudice.
• 26:45OK, going along with this,
• 26:48we had a category that we coded for each
• 26:51and every study that we called light touch,
• 26:53which is a bit of policy jargon,
• 26:55but we defined it really clearly.
• 26:56We said light touch means that it's brief,
• 26:59cheap and easy to implement this intervention
• 27:02brief meaning 15 minutes or less.
• 27:04So we had even a very clear
• 27:06definition of that that characterized
• 27:0976% of all interventions.
• 27:11That were studied or the past dozen years OK,
• 27:15and then the final way in which the
• 27:17modal type of research is very different.
• 27:19I already previewed in a sort of
• 27:23complaints earlier by by praising
• 27:26the the landmark studies.
• 27:28It's it's quite the mirror,
• 27:29opposite in the mode for the rest of these
• 27:32studies there are very small sample sizes.
• 27:35There's a great amount of attrition
• 27:37people dropping out of the intervention,
• 27:39but the analysts will simply.
• 27:42Compare who's in the control group in
• 27:43the treatment group afterward and say,
• 27:45well, they're they're roughly consistent,
• 27:47so we'll just proceed with our
• 27:49usual analysis.
• 27:49There's a lot of cluster randomization,
• 27:51but analysis at the individual level which
• 27:54which throws off the standard errors,
• 27:57and there's a great deal of lack of
• 27:59transparency, so not sharing data,
• 28:02not preregistration.
• 28:04OK so I'm just showing you this.
• 28:06It's it's quite small for you.
• 28:08I just want to characterize the
• 28:10rest of the sample when I'm.
• 28:12You know making these global descriptions?
• 28:14I want you to know that the types of
• 28:16outcomes that they're also measuring.
• 28:17The vast majority are still
• 28:19explicit attitudes or beliefs.
• 28:21There's still very little measurement
• 28:24of behavior, empathy, emotion,
• 28:26the types of prejudice, race,
• 28:28and ethnicity are still the most,
• 28:30and I say still because I did
• 28:33the previous meta analysis,
• 28:34so some of this is just really staying
• 28:36consistent with with past work,
• 28:38race and ethnicity appropriately
• 28:39are are still the most studied.
• 28:42Ability is is also studied a great deal.
• 28:47Prejudice against disabled people
• 28:49and then
• 28:50a Sergeant category is prejudice against
• 28:53immigrants, asylum seekers and refugees
• 28:56for quite understandable historical.
• 28:57You know trends in the past few years
• 28:59and then intervention studies these.
• 29:02These interventions that are being
• 29:04studied are still predominantly taking
• 29:06place on college campuses and now online.
• 29:08For example on Amazon in truck.
• 29:11OK, what's the average effect?
• 29:13So let's just get right into it.
• 29:15The average effect is d =
• 29:17.3 standard error of .02.
• 29:20For people who are not fluent indeed.
• 29:22And even though I I traffic in them,
• 29:24I like to try to make it make sense to me.
• 29:26This is the equivalent of taking
• 29:29someone who is rating and outgroup,
• 29:32say, black Americans.
• 29:33If it's a white American participant
• 29:36group rating that group on a feeling
• 29:38thermometer that ranges from zero to 100,
• 29:41with 0 being.
• 29:41Very cold 100 being I feel
• 29:43very warmly toward this group.
• 29:45Let's take someone with kind of what
• 29:46we might call a mild prejudice.
• 29:48So 10 points below the neutral point.
• 29:50This would.
• 29:51This would move them on average to a 48 OK.
• 29:54So it's worth taking a beat to
• 29:57consider whether we think that
• 29:59that's impressive or not.
• 30:01You know,
• 30:02in some ways you know I've placed
• 30:03it below the neutral point,
• 30:05and so now we're thinking.
• 30:06Well, there's.
• 30:07There's still basically just at neutral.
• 30:08Is that good?
• 30:09But recall that I've also told
• 30:11you that the predominant share
• 30:14of this this group of of studies
• 30:18only lasts for the intervention,
• 30:20only lasts for 15 minutes or or less,
• 30:22and so maybe that's quite impressive.
• 30:24Actually, for these brief.
• 30:26Light touch interventions.
• 30:27OK,
• 30:29but now I want to dig a little more
• 30:32deeply into this overall average effect,
• 30:34right?
• 30:35And I'm going to do that with
• 30:36my hands above the table.
• 30:37I'm not going to actually make
• 30:39any judgments of these papers,
• 30:41although I have many of them
• 30:43and happy to share.
• 30:44But I'm going to do this in a
• 30:46way that's quite mechanical.
• 30:47I'm just going to divide up all
• 30:50of these studies into Quintiles,
• 30:52and the quintiles will be determined by
• 30:54how many people are in your treatment group.
• 30:56OK,
• 30:56so this is just about a sample
• 30:58size analysis and what you see
• 31:00is that the bottom quintile,
• 31:01when I do this,
• 31:02this is the the column over here on
• 31:05the left hand side is 25 people or fewer.
• 31:08That's really small.
• 31:10The top quintile is 78 people or more.
• 31:15Also quite small for.
• 31:18For an intervention study right
• 31:20for randomized controlled trial.
• 31:22Now the other thing that we need
• 31:23to look at is the effect size,
• 31:25which is over here.
• 31:26I hope you can see my pointer
• 31:29in in the fourth column,
• 31:31the effect size if there's publication
• 31:34bias will track the the the sample size,
• 31:37and in fact we find that's
• 31:39exactly what it does,
• 31:40that it's these tiny tiny little
• 31:42studies that should not have any
• 31:44power to find an effect size
• 31:46that find a wopping effect size.
• 31:48Right, and of course,
• 31:50that's why they've been published
• 31:52because they found a significant effect.
• 31:55But that effect size that they find is
• 31:57double the average, and if you look at,
• 31:59you know the more high quality studies,
• 32:01just according to their sample size.
• 32:03I'm not making any other judgments
• 32:04that we could maybe argue about
• 32:06with respect to its measurement,
• 32:07or what it prioritizes or the intervention
• 32:09approach theoretical approach.
• 32:10Just looking at sample size,
• 32:12that average effect is a .18.
• 32:15OK, so that's a lot smaller.
• 32:18I'm just showing you how this.
• 32:19Actually moves in a linear direction.
• 32:21This is the average effect sizes
• 32:24and as the sample gets larger,
• 32:28so too does the effect size, right?
• 32:30So I'm just showing you the
• 32:32same thing in graphical form.
• 32:34So what is it?
• 32:35A .18 mean that average effects for
• 32:37the studies with the the greatest
• 32:39sample size that would move people
• 32:42who were raiding black Americans.
• 32:44The people, not people,
• 32:46white participants who were rating
• 32:48black Americans at a 40 they would
• 32:50be moved to a 44 on average.
• 32:53OK, so still positive movement.
• 32:57Half of the effects of above
• 32:59in some respects, right?
• 33:01Still worthwhile to pause to see
• 33:03whether we're pleased with that,
• 33:05and we could have an interesting
• 33:06argument about it, right? OK.
• 33:10So what's the average effect now?
• 33:11I'm just going to show you how
• 33:13the average effect moves down
• 33:16for every type of intervention.
• 33:18OK,
• 33:18and so you can find your favorite
• 33:21approach potentially on that.
• 33:22On that axis there.
• 33:23So all of these different intervention
• 33:26buckets from entertainment to peer
• 33:28influence to multicultural education,
• 33:30diversity trainings,
• 33:31interpersonal contact, right?
• 33:33So all of these effect sizes
• 33:35you should have seen them just
• 33:37jump down approaching 0 when we
• 33:39limit it to studies with larger.
• 33:41Sample size is OK, so I just I.
• 33:45I'll do that again,
• 33:47jump down right and one thing that I want
• 33:50you to pay close attention to is the ends.
• 33:52How many studies we have.
• 33:54The enlisted after the type of intervention
• 33:58here and I want you to drop your eyes down
• 34:01to the bottom of this figure and see that.
• 34:04In considering how many diversity trainings
• 34:07has been studied with experimental methods,
• 34:10once you restrict it to the
• 34:12sample size being 70 or more,
• 34:15there's only two.
• 34:16Two studies of diversity training
• 34:18in the last dozen years to try
• 34:20to understand the effects of dice
• 34:23diversity training that really have
• 34:25any shot at uncovering a well powered,
• 34:27you know, reliable effect.
• 34:29OK,
• 34:29and I've already told you about one of them,
• 34:31OK?
• 34:33So this brings us to my other arguments,
• 34:36which was that some of the most
• 34:38popular prejudice reduction
• 34:38ideas are not well supported.
• 34:40Well, diversity training is one of them.
• 34:41We are not at this stage in the
• 34:45scientific literature able to
• 34:47recommend the public that diversity
• 34:49trainings are an effective measure.
• 34:51Now this is not to say that I
• 34:53do not support having any kind
• 34:55of training in a workplace or
• 34:57any other kind of institution,
• 34:59but it is to say that it is.
• 35:03And an enormous problem that we don't
• 35:07know about their effects right?
• 35:09And so. Of course,
• 35:10this is averaging across any
• 35:11kind of diversity training,
• 35:13and I think that we can all think
• 35:15of diversity trainings that we've
• 35:16experienced or observed that we didn't
• 35:18think would have a positive effect
• 35:19and maybe some that we thought.
• 35:21Well, this is this.
• 35:22This is quite good, right?
• 35:24But there's no distinguishing among them,
• 35:26right?
• 35:26There's two studies in the past
• 35:28dozen years that have actually
• 35:30looked at their causal effects.
• 35:32And implicit bias has been something
• 35:34that we've talked a great deal
• 35:36about in the past dozen years.
• 35:38However,
• 35:39implicit bias trainings were included
• 35:42in that diversity training category.
• 35:45This is a surgeon category.
• 35:46There are a couple of investigators
• 35:48who I know of who have been producing
• 35:50more work on trying to understand the
• 35:53impacts of implicit bias training.
• 35:54In particular,
• 35:55the other thing that we looked
• 35:56for in this category is we just
• 35:58wanted to know there are some
• 36:00really good meta analysis.
• 36:01I could refer you to if you're interested on
• 36:04the extent to which implicit bias can change,
• 36:06period, right?
• 36:07Even in you know basic lab studies.
• 36:11We didn't include those here because
• 36:13they weren't actual interventions.
• 36:14What we were interested in here though,
• 36:15is just.
• 36:16What's the functional interdependence?
• 36:18What's the relationship between
• 36:20implicit bias and behavior?
• 36:21So forget about implicit bias training,
• 36:25what intervention out there,
• 36:27anything it could be contact.
• 36:30It could be emotional.
• 36:32Regulation it could be
• 36:34multicultural education.
• 36:35Do any of them change implicit bias?
• 36:38And if they do,
• 36:39it does behavior also change,
• 36:41right?
• 36:41So we were really interested if there
• 36:43were any studies that measured implicit
• 36:45bias or behavior as an outcome.
• 36:46We captured both of those.
• 36:49Both of those outcomes,
• 36:50whether or not they were reported
• 36:51in the abstract or not.
• 36:52'cause we were so curious about
• 36:54this question and I'm very
• 36:55sorry to tell you that again,
• 36:57this seems to be a magic number.
• 36:58There are two studies in the entire
• 37:01corpus from the past dozen years.
• 37:03That captured both implicit bias
• 37:05and behavior as an outcome in
• 37:07any kind of intervention study,
• 37:09so we really can't tell you
• 37:12what we know about interventions
• 37:14changing implicit bias,
• 37:16and they expect which that
• 37:17is expressed in what.
• 37:18I think we can.
• 37:19I think we could agree on that.
• 37:21We care most about which is behavior the
• 37:24expression of of prejudice and bias,
• 37:26right?
• 37:27Discrimination, hate crime,
• 37:29microaggressions,
• 37:30all of the things that we care about.
• 37:31OK, and then the final thing that I
• 37:33was really attentive to as a psychologist,
• 37:35because this is something in my
• 37:36field that I hear quite a bit about.
• 37:38Curious the extent to which this
• 37:40is discussed in in in psychiatry.
• 37:42Is that OK?
• 37:44Here goes the argument.
• 37:46OK,
• 37:46this is a very small change.
• 37:48This is small effect size
• 37:49that neither observed.
• 37:50But this is something that can
• 37:52build overtime. So in essence this
• 37:54can become self reinforcing people.
• 37:56Small attitude changes small changes in
• 37:59their emotional regulation around outgroups.
• 38:02Gonna have this positive reinforcement cycle.
• 38:05So it's a it's a perfectly
• 38:08valid theory of change,
• 38:10and we could find no evidence for it.
• 38:12But here again I want to be clear there's
• 38:14an absence of evidence and the way you
• 38:16look for it is you look to see whether
• 38:18any of these studies are measuring,
• 38:20change overtime longitudinally,
• 38:22and we found very few studies that did so.
• 38:27To the extent that it's not even
• 38:29worth mentioning what they found,
• 38:30because you know it was, you know,
• 38:32a few out of a body of of 400 plus OK.
• 38:37Alright, so the best research
• 38:38shows very small effects.
• 38:39That's the final argument that I made
• 38:41at the beginning, and I call this my.
• 38:43You know once more with feeling figure
• 38:45'cause I've already showed you these data,
• 38:47these are essentially the data from
• 38:49the table and then from the graph and,
• 38:51and this is charting the D,
• 38:53the effect size right on the Y axis.
• 38:56How?
• 38:56How big of an effect do we find against
• 39:00the standard error on on the X and
• 39:03what's important about this figure
• 39:04that's different is that you know these
• 39:06all of these dots are a different study.
• 39:08Right,
• 39:08and it's robust to the studies
• 39:09that are those outliers up there.
• 39:10But I just want to show you all the data.
• 39:12I'm not trimming anything,
• 39:13so these are all the studies
• 39:15in the meta analysis and this
• 39:17fitted regression line tilting,
• 39:19tilting downward to the left.
• 39:21This is what this line says.
• 39:25I've just complained to you about
• 39:26all of these methodological problems.
• 39:28You know there's a lot of error
• 39:29in these studies,
• 39:30so you know and and there's a
• 39:33lot of unrealistic effect sizes.
• 39:36But the lines tilt shows you that
• 39:39if we were just to spend the next
• 39:42dozen years testing the same ideas,
• 39:44the same interventions,
• 39:46and just tightening our methods,
• 39:47being much better about it.
• 39:49Preregistering much larger sample sizes etc.
• 39:52Etc.
• 39:52What this line suggests is that
• 39:55we would just keep finding smaller
• 39:57and smaller effects right,
• 40:00and the line in fact crosses 0.
• 40:02So the line is suggesting again,
• 40:04this is a prediction out of sample
• 40:05is that if we just kept doing this?
• 40:07If I could just keep simulating these same.
• 40:11Interventions with larger and
• 40:13larger and better methods.
• 40:15We might actually find out that
• 40:17we aren't having an effect, OK?
• 40:19So that's the most depressing
• 40:21argument of this of this paper.
• 40:24But I think it's a good place to
• 40:26pivot onto what the next generation
• 40:28of prejudice reduction research
• 40:29should look like.
• 40:30And we we have a lot of
• 40:33recommendations in in our paper and we,
• 40:35we give those recommendations to
• 40:38people who are interested in studying,
• 40:40designing and studying prejudice
• 40:43reduction interventions,
• 40:44both for the laboratory,
• 40:45which we think is extremely important.
• 40:47Even though I I myself,
• 40:48prioritize working in the field.
• 40:50But you know, especially for you know,
• 40:52research and development purposes we.
• 40:54We see the lab is extremely important and
• 40:56and for those interested in field work,
• 40:59I want to talk about something else.
• 41:00Though I'm not going to go through
• 41:02those recommendations today,
• 41:03I want to talk about the way we've
• 41:07been thinking about changing the way
• 41:09we think about the interventions
• 41:11themselves and using in fact,
• 41:13a different model of change and
• 41:15in thinking more about structural
• 41:17interventions and their effects. OK,
• 41:19so are we using the right model of change?
• 41:22Very mindful of my audience.
• 41:24I mean I'm always mindful of saying this
• 41:25even in front of my psychology audiences,
• 41:28but the current model of change is 1
• 41:30in which we really even though I know
• 41:33that these investigators don't believe
• 41:35that racism and religious prejudice
• 41:37and ethnic bias and all of these
• 41:39other prejudices that are studies,
• 41:40even though I know these these
• 41:42investigators don't really believe that
• 41:44it's just a psychological problem,
• 41:45they understand it's structural,
• 41:47it's really conceptualized as
• 41:48purely a psychological problem.
• 41:50In all of these interventions right?
• 41:52And So what we then do is we create these
• 41:55highly individualistic interventions right?
• 41:58These these mentalizing kinds of
• 42:00interventions in order to create
• 42:02individual psychological change as
• 42:04well as social societal change.
• 42:06So it's this bottom up cumulative.
• 42:09Theory of social change and I wanna I
• 42:11wanna talk about this alternative model
• 42:13which is to attack a psychological
• 42:16problem with a structural intervention
• 42:18in order to create individual
• 42:20psychological change.
• 42:21I don't want to throw out mental
• 42:23life as a target of intervention,
• 42:25but I want to think about what
• 42:28intervention might produce a larger effect,
• 42:30potentially right?
• 42:31Again, this is our editorial at the end.
• 42:35What do we mean by structural
• 42:36interventions and is this something
• 42:38that psychologists and psychiatrists
• 42:39can can participate in? I think so.
• 42:42Structure of course, means institutions,
• 42:45rules leaders.
• 42:46So the changing of laws and rules
• 42:49and organizational procedures,
• 42:52the decisions and communications
• 42:53from leaders absolutely.
• 42:55And and this is what is traditionally
• 42:58conceptualized as structural by all
• 43:00of my social science colleagues.
• 43:02But we also want us to think about.
• 43:04Social structures,
• 43:06so these are the levers that these
• 43:10are the levers of of change that
• 43:13involve collectives,
• 43:15but times when that kind of
• 43:18collective signal is not sparked
• 43:20by these traditional structures,
• 43:21but rather by more unofficial
• 43:24social grouping.
• 43:25So these mass collective
• 43:27experiences that we can have in
• 43:29media unofficial organizations,
• 43:31my graduate student and I were thinking
• 43:33about how to give an example of this,
• 43:35and we thought.
• 43:36You know,
• 43:36there's plenty of unofficial organizations
• 43:38that influence influences all the time.
• 43:41And she mentioned Black Twitter,
• 43:43which you know does not have a board
• 43:45of directors but has been extremely
• 43:47influential in guiding conversations
• 43:49around race and and culture and and politics,
• 43:52right?
• 43:53Mass media events in person gatherings,
• 43:56zoom gatherings,
• 43:58simultaneous collective experiences.
• 44:00This is hard, though,
• 44:02because behavioral theory,
• 44:03psychological theory only
• 44:05sometimes even mentions structure.
• 44:06In it and so let me start with
• 44:10some examples of theory that does
• 44:12relate to structure and and to
• 44:14give you examples of how I think.
• 44:16In the past dozen years and plus
• 44:18we've used a lot of psychological
• 44:20theory about prejudice to design
• 44:22interventions that are less structural,
• 44:24but we could design them to be more
• 44:27structural and and so here's my example.
• 44:29Social norms theory,
• 44:30which is a theory we work
• 44:32with a lot in my lab,
• 44:33does make predictions about leadership about
• 44:35how leaders can signal new social norms.
• 44:38About what is typical,
• 44:40what is desirable?
• 44:41Regarding prejudice and many other things,
• 44:43of course.
• 44:44And you know one thing that we've been
• 44:46trying to invest in is to investigate
• 44:49attitude and perceived norm change in
• 44:52response to Supreme Court decisions.
• 44:54To see the extent to which Supreme
• 44:57Court decisions about marginalized nized
• 45:00groups change the way we feel about them,
• 45:04think about them and the way we
• 45:06think that other people residing in
• 45:08the United States think about them.
• 45:09But, uh, less structural intervention.
• 45:11Based on this theory and one,
• 45:13this is an approach that you see a lot in.
• 45:16The meta analysis would be to send
• 45:18emails to people just individual
• 45:20prompts reminding them about the,
• 45:22say progressive orientation of their leader,
• 45:24right?
• 45:24And so it's a completely different
• 45:26experience to read an email
• 45:28that's addressed just to you,
• 45:30but I think that this example is just
• 45:31trying to highlight this approach.
• 45:33Both are testing the same idea,
• 45:35but would we expect one to have a
• 45:37much bigger effect than the other?
• 45:38We would, and so where should we putting?
• 45:41We be putting our?
• 45:42Energy is essentially in testing.
• 45:43Some of these theories.
• 45:45Let me take an individually oriented
• 45:48theory that doesn't really mention
• 45:50structure as we've defined it perspective.
• 45:52Taking theory is something that's
• 45:55that's very Sergeant right now
• 45:57in the literature on prejudice
• 45:59reduction and also attitude change
• 46:02and persuasion in particular.
• 46:03Scholars.
• 46:04In the past I would say 8 to 10
• 46:07years have been very interested in
• 46:09ideas about perspective giving,
• 46:11so not asking a person to try to imagine.
• 46:16Or to read about and then simulate
• 46:18the perspective of others right?
• 46:20But actually to sit in nonjudgmental,
• 46:23listening about and and while they
• 46:25listen to the perspective of others
• 46:27and in particular members of oppressed,
• 46:30marginalized,
• 46:30stigmatized group.
• 46:31So that's called perspective giving
• 46:33where you know the the onus is not
• 46:35on imagining it's it's it's on or
• 46:37the emphasis is not on imagining
• 46:39the perspectives, taking it,
• 46:40but rather listening, taking it in,
• 46:43giving and and then the person gives it.
• 46:45So here's an example of a very.
• 46:47What I would describe as a as a
• 46:49social structural intervention
• 46:50that tests this hypothesis.
• 46:52So a famous study that you probably
• 46:54have read about in the paper
• 46:57by Brockman and Kala.
• 46:58A used perspective,
• 47:00taking with canvassers who
• 47:03were organizing around
• 47:05issues of transgender rights in in
• 47:08Florida and testing whether going door
• 47:11to door and asking those who answered
• 47:15the door not to just listen to them
• 47:18about about the the issue in particular.
• 47:21In this first study was about why
• 47:25transgender individuals should use the the
• 47:27correct bathroom that that reflects their.
• 47:29Their gender instead they would knock
• 47:32on the door and ask the person who
• 47:34answered to tell them about a time when
• 47:36they felt that they had been excluded,
• 47:39marginalized for some aspect of their
• 47:41identity, and to listen to them and to
• 47:43that experience and then to relate that to
• 47:46the reason why they were canvassing today.
• 47:48To say that it was.
• 47:49It was similar to some of the
• 47:51issues that transgender people face.
• 47:53So what's structural about that?
• 47:56Because you know another way to test
• 47:58that idea is, you know, to text.
• 48:00People maybe a little nudge,
• 48:01stimulate perspective getting and sign
• 48:03up for text service and you know,
• 48:05get a get a message every day.
• 48:06You know.
• 48:07Try to try to think about transgender
• 48:08people and how it feels for them
• 48:10to blah blah blah right what?
• 48:11What structural about the first one to me?
• 48:14It's this collective that's brought
• 48:15into the experience.
• 48:16So sure, it's a dyadic intervention.
• 48:18Or maybe there's a triad there's.
• 48:20There's usually two people canvassing and
• 48:22listening to this person at the door,
• 48:24but I think that there's this
• 48:26imagined collective to it, right?
• 48:27Because when you open the door and canvases?
• 48:30Arrived to talk to you but you know
• 48:31is that those campuses are going to
• 48:33everybody else in your neighborhood,
• 48:35right?
• 48:35So your neighbors are having this
• 48:36experience at the same time,
• 48:38and you know also that these canvassers
• 48:41represent a larger collective and an
• 48:44organized group of political movements.
• 48:46And so you're,
• 48:47you're coming into contact with
• 48:49something quite larger that these
• 48:51people are are representing.
• 48:53And so I think that my prior would be
• 48:56that this this kind of intervention,
• 48:59right?
• 49:00Using the same theory,
• 49:01I don't think we should.
• 49:02Throw out our theories would be
• 49:05more effective,
• 49:06and indeed I mean this is just
• 49:08cherry picking an example for you,
• 49:09but this is a study that has gained
• 49:11so much traction in part because
• 49:14the intervention has quite long
• 49:16lasting effects and so these these
• 49:19investigators have now repeated this.
• 49:22The intervention with many different
• 49:24issues and targeting many different
• 49:26marginalized groups and they have a
• 49:28completely ingenious measurement strategy,
• 49:30which is to survey people online
• 49:33about these issues and ostensibly
• 49:36unrelated voter survey,
• 49:38and they find stable attitude change.
• 49:42Following these this canvas or visit
• 49:44that's even resistant to things like attack,
• 49:48ads and so forth when they they feature
• 49:50kind of the other side of these.
• 49:52Issues on these voter polls.
• 49:56OK.
• 49:58Right? Because of zoom,
• 50:00you think I'd be better.
• 50:02Because I do, my just can't see my last .0.
• 50:04Yes and there are many other
• 50:06structural intervention examples
• 50:07that I could get into it,
• 50:08but I I do want to leave time for questions,
• 50:10so I'm going to move to the end now.
• 50:14So what would this require?
• 50:16This kind of next generation, this this?
• 50:18These proposals about
• 50:20trying to use our theories,
• 50:22but to design more,
• 50:25more structural interventions with them.
• 50:27First of all, I think that it would
• 50:29demand of social scientists that we
• 50:31improve our skills at thinking about
• 50:33structural expressions of our theories.
• 50:35I think that we are we default often to
• 50:37thinking about these very individualized,
• 50:39personally delivered interventions.
• 50:41I think that we would have.
• 50:44To engage in much more collaborative
• 50:46work across disciplines.
• 50:48Because some of us specialize
• 50:50in these theories.
• 50:51Some of us specialize in understanding
• 50:53how to measure aspects of
• 50:56mental life and others of us are
• 50:58actually at the table when.
• 51:00Political campaigns are designed
• 51:02or new infrastructures in our
• 51:04communities are built and I think that
• 51:07collaborating together to think about
• 51:09you know these actual structures.
• 51:11These social structures and and
• 51:13how they can be used to test
• 51:16ideas about prejudice reduction
• 51:17would be much more fruitful.
• 51:19I also think that we need to more
• 51:22seriously invest in research on how
• 51:25more top down interventions can lead
• 51:27to backlash or to do to resistance.
• 51:32I think that it opens up this really
• 51:34interesting space for social scientists
• 51:36who aren't necessarily involved
• 51:38at the moment in equity reform to
• 51:40also be invested in equity reform,
• 51:42because equity reform,
• 51:43as I see it, so you know,
• 51:45outside of prejudice reduction in research,
• 51:48things like improving hiring practices,
• 51:52retention practices,
• 51:53improving the climate of universities,
• 51:58corporations, communities.
• 52:01You know the the the reforms that are
• 52:05being asked for are most often being asked
• 52:07for on the basis of justice and values,
• 52:10which is absolutely appropriate and
• 52:11should be the leading rationale for
• 52:14why these reforms should be made.
• 52:15But I think that this actually adds
• 52:17if we're going to seriously pursue
• 52:20more structural interventions and
• 52:21try to understand the psychological
• 52:24changes that we get from them that
• 52:26would actually add more social
• 52:28scientists to that push,
• 52:29because they'd be interested
• 52:30in studying these.
• 52:31These changes prospectively right,
• 52:33and so I I, I think that that's an
• 52:38interesting outcome of this kind of call.
• 52:40I, I think also just methodologically
• 52:42we're going to have to get a lot more
• 52:44familiar with or collaborate with other
• 52:46social scientists who can help us to
• 52:48design studies that aren't just little,
• 52:51you know,
• 52:52two by two you know experiments,
• 52:54but use, you know,
• 52:56more creative strategies for
• 52:58studying the the the real world.
• 53:00And it's it's thicket of various variables
• 53:03and and threats to causal inference.
• 53:07And so I'm going to end there and thank
• 53:09you so much for your attention and I'd
• 53:12love to hear questions and feedback.