BEGIN:VCALENDAR PRODID:-//Microsoft Corporation//Outlook 16.0 MIMEDIR//EN VERSION:2.0 METHOD:PUBLISH X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VTIMEZONE TZID:Central Standard Time BEGIN:STANDARD DTSTART:16011104T020000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZOFFSETFROM:-0500 TZOFFSETTO:-0600 END:STANDARD BEGIN:DAYLIGHT DTSTART:16010311T020000 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZOFFSETFROM:-0600 TZOFFSETTO:-0500 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT CLASS:PUBLIC CREATED:20230118T224037Z DESCRIPTION:Speaker:\nAlina Arseniev-Koehler\, Assistant Professor\, Sociol ogy\, Purdue University\n\nTitle:\nStigma’s Uneven Decline \n\nAbstract: \nHas the stigma targeting diseases declined? We analyze 4.7 million news articles to create new measures of stigma for 106 health conditions from 1 980-2018\, using word embedding methods for text analysis. We then examine how this stigma changed for different types of conditions across time usi ng mixed effects regression modeling. We find that in the 1980s\, most dis eases were marked by strong connotations of disgust\, immorality\, and neg ative personality traits. Since then\, stigma declined dramatically for ch ronic illnesses: cancers\, neurological conditions\, genetic diseases\, an d many other conditions have shed most of their negative connotations. But for other types of conditions\, stigma proved especially resistant to cha nge. Across the decades\, behavioral health conditions (mental illnesses\, addictions\, and eating disorders) persistently connoted immorality and n egative personality traits. Infectious diseases remained strongly linked t o attributions of disgust. Stigma has transformed from a sea of negative c onnotations surrounding most diseases to a narrower set of judgments targe ting conditions where the primary symptoms are aberrant behaviors. (This t alk is based on research with Rachel Best at the University of Michigan).\ nSpeaker Bio:\n​ Alina Arseniev-Koehler is a computational and cultur al sociologist with substantive interests in language\, health\, and socia l categories. Alina strives to clarify core concepts and debates about cul tural meaning in sociology. For example\, how do individuals learn and dep loy stereotypes? Empirically\, Alina focuses on cases where meaning is lin ked to inequality and health\, such as the moral meanings attached to body weight\, the stigmatizing meanings of disease\, and gender stereotypes. T o investigate these topics\, Alina uses computational methods and machine learning\, especially computational text analysis.\nAlina’s work also ci rcles around a methodological question: how can scientists measure meaning s encoded in text data\, such as news articles and social media posts? Com putational text analysis requires scientists to mathematically model the n uanced ways in which human language encodes and conveys meaning. As highli ghted by Alina’s work\, innovation in computational text analysis is tig htly intertwined with innovation in theoretical understanding of meanings. \nAlina received a B.A. in Sociology from University of Washington in 2014 \, and a master’s and Ph.D. in Sociology from the University of Californ ia\, Los Angeles in 2022.\nLocation:\nIn person: Chambers Hall \, 600 Foster Street\, Lower Level\nR emote option: https://northwestern.zoom.us/j/91034727443 \nPasscod e: NICO23\nAbout the Speaker Series:\nWednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems and data science. It brings together attendees ranging from graduate students to se nior faculty who span all of the schools across Northwestern\, from applie d math to sociology to biology and every discipline in-between. Please vis it: https://bit.ly/WedatNICO for information on future speakers.\n \n \n DTEND;TZID="Central Standard Time":20230308T130000 DTSTAMP:20230118T224037Z DTSTART;TZID="Central Standard Time":20230308T120000 LAST-MODIFIED:20230118T224037Z LOCATION:In person at Chambers Hall\, or remote via Zoom PRIORITY:5 SEQUENCE:0 SUMMARY;LANGUAGE=en-us:Wed@NICO\, 3/8\, Alina Arseniev-Koehler TRANSP:OPAQUE UID:040000008200E00074C5B7101A82E0080000000080052B384D2BD901000000000000000 01000000018F8C80CB2695D44AF5A969ACC248DCB X-ALT-DESC;FMTTYPE=text/html:

Speaker:

Alina Arseniev-Koehler\, Assis tant Professor\, Sociology\, Purdue University

Title :

Stigma’s Uneven Decline \;

Abstract:

Has the stigma targeting diseases declined? We analyze 4.7 mil lion news articles to create new measures of stigma for 106 health conditi ons from 1980-2018\, using word embedding methods for text analysis. We th en examine how this stigma changed for different types of conditions acros s time using mixed effects regression modeling. We find that in the 1980s\ , most diseases were marked by strong connotations of disgust\, immorality \, and negative personality traits. Since then\, stigma declined dramatica lly for chronic illnesses: cancers\, neurological conditions\, genetic dis eases\, and many other conditions have shed most of their negative connota tions. But for other types of conditions\, stigma proved especially resist ant to change. Across the decades\, behavioral health conditions (mental i llnesses\, addictions\, and eating disorders) persistently connoted immora lity and negative personality traits. Infectious diseases remained strongl y linked to attributions of disgust. Stigma has transformed from a sea of negative connotations surrounding most diseases to a narrower set of judgm ents targeting conditions where the primary symptoms are aberrant behavior s. (This talk is based on research with Rachel Best at the University of M ichigan).

S peaker Bio:

Alina A rseniev-Koehler is a computational and cultural sociologist wit h substantive interests in language\, health\, and social categories. Alin a strives to clarify core concepts and debates about cultural meaning in s ociology. For example\, how do individuals learn and deploy stereotypes? E mpirically\, Alina focuses on cases where meaning is linked to inequality and health\, such as the moral meanings attached to body weight\, the stig matizing meanings of disease\, and gender stereotypes. To investigate thes e topics\, Alina uses computational methods and machine learning\, especia lly computational text analysis.

Alina’s work also circ les around a methodological question: how can scientists measure meanings encoded in text data\, such as news articles and social media posts? Compu tational text analysis requires scientists to mathematically model the nua nced ways in which human language encodes and conveys meaning. As highligh ted by Alina’s work\, innovation in computational text analysis is tight ly intertwined with innovation in theoretical understanding of meanings.

Alina received a B.A. in Sociology from University of Wash ington in 2014\, and a master’s and Ph.D. in Sociology from the Universi ty of California\, Los Angeles in 2022.

Location:

In person: Chambers Hall\, 600 Foster Street\, Lower Level
Remote opti on: https://northwestern.zoom.us/j/91034727443
Pass code: NICO23

About the Speaker Series:

Wednesday s@NICO is a vibrant weekly seminar series focusing broadly on the t opics of complex systems and data science. It brings together attendees ra nging from graduate students to senior faculty who span all of the schools across Northwestern\, from applied math to sociology to biology and every discipline in-between. Please visit: h ttps://bit.ly/WedatNICO for information on future speakers.

 \;

  \;

X-MICROSOFT-CDO-BUSYSTATUS:BUSY X-MICROSOFT-CDO-IMPORTANCE:1 X-MICROSOFT-DISALLOW-COUNTER:FALSE X-MS-OLK-AUTOFILLLOCATION:FALSE X-MS-OLK-CONFTYPE:0 BEGIN:VALARM TRIGGER:-PT15M ACTION:DISPLAY DESCRIPTION:Reminder END:VALARM END:VEVENT END:VCALENDAR