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Digital Humanities Initiative

The CUNY Digital Humanities Initiative (CUNY DHI), launched in Fall 2010, aims to build connections and community among those at CUNY who are applying digital technologies to scholarship and pedagogy in the humanities. All are welcome: faculty, students, and technologists, experienced practitioners and beginning DHers, enthusiasts and skeptics.

We meet regularly on- and offline to explore key topics in the Digital Humanities, and share our work, questions, and concerns. See our blog for more information on upcoming events (it’s also where we present our group’s work to a wider audience). Help edit the CUNY Digital Humanities Resource Guide, our first group project. And, of course, join the conversation on the Forum.

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Fwd: [DHSI] Teaching Cultural Analysis of Datasets (9/21/23)

  • Posted by Matthew K. Gold (he/him) on October 25, 2023 at 10:27 am

    ———- Forwarded message ———
    From: Blevins, Cameron <[email protected]>
    Date: Tue, Oct 24, 2023 at 7:25 PM
    Subject: Re: [DHSI] Teaching Cultural Analysis of Datasets (9/21/23)
    To: [email protected] <[email protected]>

    Dear colleagues,

    I had several folks ask for a recording of Dr. Lindsay Poirier’s talk last
    month at CU Boulder, “Teaching Cultural Analysis of Datasets.” We’ve posted
    the recorded talk on our Data Advocacy for All website in the hopes that
    others can find it as thought-provoking and useful as we did:
    https://da4all.github.io/teaching-cultural-analysis-of-datasets/.

    Best,

    Cameron

    Cameron Blevins

    Associate Professor, Clinical Teaching Track (History)

    Director of Digital Initiatives (CLAS), University of Colorado Denver

    [email protected] | cameronblevins.org | he/him

    Recovering Auraria’s Past (https://aurariahistory.org/) | Data Advocacy
    For All (https://da4all.github.io/) | *Paper Trails*
    (https://global.oup.com/academic/product/paper-trails-9780190053673)

    *From: *Blevins, Cameron <[email protected]>
    *Date: *Tuesday, September 12, 2023 at 7:35 AM
    *To: *[email protected] <[email protected]>
    *Subject: *Teaching Cultural Analysis of Datasets (9/21/23)

    Dear colleagues,

    Dr. Lindsay Poirier (https://lindsaypoirier.github.io/) will be giving a
    public talk on *“Teaching Cultural Analysis of Datasets” *next Thursday,*
    September 21st from 12:30-1:30pm MST*. Register here
    (https://forms.gle/tTrKBkxsZP2xZwfV6) to attend either in-person or over
    Zoom. This is the first speaker in a series for Data Advocacy for All
    (https://da4all.github.io/), a teaching collaboration between faculty at CU
    Boulder and CU Denver. Please let me know if you have any questions!

    Cameron Blevins

    Associate Professor, Clinical Teaching Track (History)

    Director of Digital Initiatives (CLAS), University of Colorado Denver

    [email protected] | cameronblevins.org | he/him

    Recovering Auraria’s Past (https://aurariahistory.org/) | Data Advocacy
    For All (https://da4all.github.io/) | *Paper Trails*
    (https://global.oup.com/academic/product/paper-trails-9780190053673)

    *[image: A black background with a black square Description automatically
    generated with medium confidence]*

    *Teaching Cultural Analysis of Datasets*

    *A Talk by Dr. Lindsay Poirier*

    *Date/Time:* September 21, 2023, 12:30pm – 1:30pm MST

    *Location:* Case E422, CU Boulder

    *Event Mode:* In person with zoom-in option

    *Zoom-In Link:* https://cuboulder.zoom.us/j/97040493424
    (https://cuboulder.zoom.us/j/97040493424)

    *Registration Link: *https://forms.gle/tTrKBkxsZP2xZwfV6

    *Abstract:* Canonical ideologies tend to position datasets as neutral
    representational tools, when datasets may be more aptly characterized as
    power-laden systems for signification. While critical for interpreting the
    cultural meaning of data, the skills needed to historicize, situate, and
    deconstruct datasets are often underrepresented in STEM education. In this
    talk, Lindsay Poirier outlines a series of pedagogical approaches to
    teaching cultural analysis of datasets. Poirier shows how, by cultivating
    competency in hermeneutics, ethnography, and critical theory, students can
    learn to attend to the cultural provenance of datasets across a number of
    registers – from interrogating the belief systems of data designers, to
    examining the cultural logics of data infrastructures, to analyzing the
    interests of data-producing institutions, to unpacking the discourses that
    shape public understandings of data. Further, by pluralizing the epistemic
    lenses through which data are analyzed, students have an opportunity to
    nourish reflexive sensibilities – discerning their own cultural positioning
    as they question why culture tends to be deleted from data science work.

    *Speaker Biography:* Lindsay Poirier is an Assistant Professor of
    Statistical and Data Sciences at Smith College and a cultural
    anthropologist of data advocacy, governance and infrastructure. Interlacing
    methods in cultural analysis and exploratory data analysis, Poirier
    critically examines how meaning gets made from data—by whom, for whom,
    under what conditions and toward what ends. Poirier is the lead platform
    architect for the Platform for Experimental Collaborative Ethnography
    (PECE), has represented the empirical humanities in international efforts
    to advance interdisciplinary data sharing, and collaborates as a hacker and
    data wrangler on a number of community-engaged and justice-focused data
    science projects.

    ****This event is the first of in a Speaker Series hosted by Data Advocacy
    for All (https://da4all.github.io/) (DA4All) and supported by funding made
    possible by the University of Colorado System CU Next Award. Data Advocacy
    for All is a CU Next Award project that aims to extend data humanities
    education throughout and beyond the University of Colorado system. Contact
    Laurie Gries for more information about DA4All, the speaking series, and/or
    this event: **[email protected]* <[email protected]>*.*

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