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Enregistrement W4306906521 · doi:10.21900/j.alise.2022.1094

Teaching to Respect Intersectional Neurodiversity in LIS Classrooms and Practice

2022· article· en· W4306906521 sur OpenAlexaff
Laura Ridenour, Heather Hill, Amy Waldman, Denice Adkins

Notice bibliographique

RevueProceedings of the ALISE Annual Conference · 2022
Typearticle
Langueen
DomaineComputer Science
ThématiqueDigital literacy in education
Établissements canadiensWestern University
Organismes subventionnairesnon disponible
Mots-clésPsychologySociologyPedagogyPsychoanalysis

Résumé

récupéré en direct d'OpenAlex

“Being a librarian is a people-person job….” – Xavier Ateneo Senior High Library, Facebook, 2020 “…libraries are actively trying NOT to recruit people who don't enjoy working with the public…” – iBrarian, r/librarians, 2020 “All I know is that if the jobs of the future depend on "likability," (and the corollary of being a "people person") I may as well give up now. That's the one skill I neither I or people like me cannot learn.” – pigbitinmad, Library Journal comments, 2017 The LIS profession, and in many cases, our textbooks, instructors, and professional guidelines, tend to frame librarianship as an exclusively social profession. For instance, a reference librarian has to be a good “people person” who can intuit patrons’ verbal and nonverbal communication and make others feel welcome. This devalues the skills and strengths that those for whom this is not a default bring to the LIS profession and is exclusionary or traumatizing to neurodiverse students (McCulloch, 2021). In this panel, we propose strategies for reframing instructional practices to allow all students to demonstrate their strengths and find apath in the LIS professions. Even as our profession aspires to adopt a growing definition of diversity and equity and recognition of intersectionality, invisible disabilities are often overlooked. This panel addresses issues of invisible diversity, social interaction, and ways to create an equitable classroom and work environment in which all voices, perspectives, and selves are valued. Previous works have presented the lived-in experiences of neurodiverse information professionals (Bonanno et al., 2018), and explored the potential for autistic university student inclusion in academic libraries through the development of guidelines for librarians (Anderson et al., 2018). Our panel delves into both the lived-in experiences of neurodiverse individuals in ALA-accredited master’s programs and the workplace, how best to support neurodiverse students, and preparing neurodiverse individuals for the information workforce in the face of employers averse to hiring “non-people persons1.” We do this through a moderated discussion revolving around the following critical topics in relation to neurodiversity and invisibledisabilities:1. Reframing deficit thinking to asset-based thinking, grounded in ALA policy2. Modification of teaching practices and policies in LIS classrooms, wording of policies, and acknowledging the “neurotypical professor1” perspective3. Modeling productive and positive interactions for neurotypical LIS students to build and strengthen the ability to interact with neurodiverse classmates, coworkers, and patrons and for neurodiverse LIS students to do the same in the opposite direction4. A discussion of potential holistic accommodations, strengths-based capacity building, and teaching to articulate translatable skills in professional library and information workplaces Our panel opens with a discussion of ALA “behavioral guidelines” and the impossible precedents they set for neurodiverse employees of information organizations. Takeaways for the audience, in addition to the outlined discussion points, include curated documents for the audience related to the panel to discuss with their institutional peers and management, available at https://bit.ly/3QBNaWZ; lived-in experiences of neurodiverse individuals in ALA-accredited masters programs who have gone on to information professions; and examples of how to 1) modify course documents to clarify expectations for neurodiverse students, 2) create an atmosphere of trust with students, 3) normalize asking for help and using resources (for students and faculty) and 4) how to respond appropriately to a private disclosure. We strive to impress upon attendees the importance of recognizing and honoring invisible differences, but recognize that as white, Jewish, and Hispanic women we can only acknowledge that the experience and reality of disability is different for BIPOC and LGBTQ+ members of society. Intersectional identities play an important role in neurodiverse communities, and theracist origins of autism and Asperger’s diagnoses still influence what we know of neurodiversity today (Botha & Gillespie-Lynch, 2022). This panel serves as a starting point in LIS education, and through informing our teaching with empathy, compassion, and acceptance for neurodiverse students, we hope to also improve teaching in LIS education for all students.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,014
score de la tête « metaresearch » (Gemma)0,021
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,022
Score d'incertitude au seuil0,073

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0140,021
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0220,021
Communication savante0,0110,013
Science ouverte0,0020,026
Intégrité de la recherche0,0050,008
Charge utile insuffisante (le modèle a refusé de juger)0,0140,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,019
Tête enseignante GPT0,270
Écart entre enseignants0,251 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2022
Routes d'admission1
Résumé présentoui

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Même revueProceedings of the ALISE Annual ConferenceMême sujetDigital literacy in educationTravaux en français237 207