[Metadatalibrarians] Invitation to the Core Catalog Form and Function IG Discussion at 2021 ALA Annual Conference (Virtual)

Bela Gupta bgupta at umassd.edu
Tue May 25 06:59:46 PDT 2021

** Apologies for multiple postings... **
The ALA Core Catalog Form and Function Interest Group invite you to a focused discussion on the topic of equity, diversity, and inclusivity in the library catalog. This discussion session will be held at the 2021 ALA Annual Conference (Virtual)

Date: Friday, June 25, 2021

Time: 11:00 A.M. to Noon (CST: Central Time US and Canada)
            Noon to 1:00 P.M.  (EST: Eastern Time US and Canada)

The session will automatically be recorded. The recording will be posted to the IG Connect Space in ALA Connect.
Join Zoom Meeting:
Meeting ID: 970 0324 1920
Passcode: 949285
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Meeting ID: 970 0324 1920
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Topic: Catalog Form and Function Interest Group Discussion
Conveners will center the conversation on defining ways to address harmful language and harmful biases in catalogs.

There is evidence to suggest that for many users, classification languages that are used in our catalogs has in the past, and at present made use of problematic language, with results that are not inclusive.[i]
The Library of Congress uses controlled vocabularies and subjects to classify library resources.  They are difficult to change as they have been standardized. The LCSH vocabulary lacks a wholly inclusive language; instead, the language is one of a society divided by systemic inequity. For example, the Library of Congress uses outdated terminology for Native American subject headings and those for tribes of India. These topics do not provide actual representation.

In Data Feminism, D'Ignazio and Klein consider this context through a frame of data feminism, which "asserts that data are not neutral or objective. They are products of unequal social relations, and this context is essential for conducting accurate, ethical analysis."[ii] The contextual frame is imperative for understanding LCSH bias; its racism is rooted in the historical inequities of American history. Other contextual considerations for this principle of data feminism include: "... a process that includes understanding the provenance and environment from which the data was collected, as well as working hard to frame context in data communication..."[iii] Integrations or mappings to other subject vocabularies could replace the LCSH vocabulary of inequality and racism until such time as American society might produce equitable and inclusive language in a more systematic way.

There is also the possibility that a wholly just and equitable system of description may not be attainable from a system perspective, but rather may be negotiated by library professionals engaged in public service, offering information literacy praxis to engage critically with language the catalog offers.[iv]

Bela Gupta and Jim Hahn
Co-chairs, ALA Core Catalog Form and Function IG

Bela Gupta
Division Head, Library Technical Services
Cataloging & Metadata Librarian
Claire T. Carney Library
University of Massachusetts Dartmouth
285 Old Westport Rd<https://www.mapquest.com/us/ma/north-dartmouth/02747-2356/285-old-westport-rd-41.631146,-71.012470>
Dartmouth, MA 02747<https://www.mapquest.com/us/ma/north-dartmouth/02747-2356/285-old-westport-rd-41.631146,-71.012470>

Office: 508-999-8673
bgupta at umassd.edu<mailto:bgupta at umassd.edu>


i Safiya Umoja Noble, Algorithms of Oppression: How Search Engines Reinforce Racism. (NYU Press, 2018).
ii Catherine D'Ignazio and Lauren F. Klein, Data Feminism (Cambridge, MA: MIT Press, 2020), 18.
iii D'Ignazio and Klein, Data Feminism, 171-172.
iv Emily Drabinski, "Queering the Catalog: Queer Theory and the Politics of Correction." The Library Quarterly: Information, Community, Policy 83, no. 2 (2013): 94-111. https://doi.org/10.1086/669547<https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.1086%2F669547&data=04%7C01%7Cbgupta%40umassd.edu%7Cf95eb732053d4fe1e19208d916f1e189%7C328d6c0d0f2f4b7693109762ba1c3e2d%7C0%7C0%7C637566050392409367%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=2gZGUmsD%2BNRaPl2Q7ZJnlSolqmJ6qTI8RW31BzadQwM%3D&reserved=0>.

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