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Record W4391407830 · doi:10.1215/15314200-10872226

Contributors

2024· article· en· W4391407830 on OpenAlexaboutno aff

Bibliographic record

VenuePedagogy Critical Approaches to Teaching Literature Language Composition and Culture · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEducational Reforms and Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

Vivian Kao is associate professor of English and director of the first-year composition program at Lawrence Technological University. She teaches courses in writing, literature, film, and the intersection of technology and the humanities. Her courses often feature multimodal assignments that challenge students to think about composition as activity, experiment, and craft. Her other publications include an account of students exploring essay form by building three-dimensional structures, and a forthcoming visual essay on virtual museum exhibits created in response to modernist literary texts.Jessica Masterson is assistant professor at Washington State University Vancouver, where her research concerns the intersections of language, literacy, and democratic teacher education.Sarah Moon is assistant professor of humanities at Massachusetts Maritime Academy, where she teaches composition, writing about literature, environmental writing, and American theater. Her scholarly work has been published in Community Literacy Journal, Literacy in Composition Studies, Journal of Multimodal Rhetorics, and Center for Sustainable Practices in the Arts Quarterly. A playwright, she was the 2023 artist in residence for Eastern Connecticut Center for History, Art, and Performance, where she developed the original full-length drama Apostates.Molly Parsons earned her PhD in English and education at the University of Michigan. She is currently assistant director of the Center for Research and Writing at Keene State College, where she has the privilege of learning alongside talented undergraduate tutors. Her research interests include the ethics of writing center practice, grammar instruction for tutors, and, presently, the implications of artificial intelligence for tutoring and teaching. Find her other work in Praxis: A Writing Center Journal, Writing Lab Newsletter, and Another Word, a blog from the University of Wisconsin-Madison's writing center.Kevin Piper teaches literature and composition at Madison College and is an honorary fellow at the University of Wisconsin-Madison, where he received his PhD. His recent work looks at how teachers can use student feedback to improve their practice. His literary scholarship has spanned a wide range of areas, including ethnic and Indigenous literatures, postsecular literature, and literary modernisms. He can be reached at kcpiper@madisoncollege.edu.Malini Johar Schueller is professor in the Department of English at the University of Florida. She has been the faculty advisor for Students for Justice in Palestine on her campus for many years and is a member of the organizing collective for the US Campaign for the Academic and Cultural Boycott of Israel. She is the author of several books, including U.S. Orientalisms: Race, Nation, and Gender in Literature, 1790–1890 (1998), Locating Race: Global Sites of Post-Colonial Citizenship (2009), and Campaigns of Knowledge: U.S. Pedagogies of Colonialism and Occupation in the Philippines and Japan (2019). She has coedited Exceptional State: Contemporary US Culture and the New Imperialism (2007) and Dangerous Professors: Academic Freedom and the National Security Campus (2009). She is the director of the award-winning documentary In His Own Home (2015) about police brutality and campus militarization. In 2019 she was selected to participate in a Faculty Development Seminar by the Palestinian American Research Council. Currently she is working on an essay collection, From Palestine to You. She teaches courses in comparative settler colonialism, including Palestine, and courses in postcolonial theory, Asian American studies, and US imperialism.Elina Siltanen was university lecturer at the Department of English, University of Turku at the time of writing this article, and now works at the University of Eastern Finland. Her research focuses on contemporary American poetry, more specifically on the role of affect in reading complex literary texts, and her article is a part of her research project “Difficult Relations: Reading for Emotion in Recent American Experimental Poetry.” Recently, she has published articles on the connections between conceptualism and confessionalism in poetry in the Journal of Modern Literature and on metamodernism and New Sincerity in English Studies. She has a double doctoral degree from the University of Turku and Luleå University of Technology.D. T. Spitzer-Hanks is an early-career researcher interested in critical composition studies and in transatlantic critical classical reception in the long nineteenth century, specifically in North America and the United Kingdom. Spitzer-Hanks is particularly interested in analyzing how patterns of communication and perception create social structures in which inequity is fostered and sustained and seeks to find ways to intervene in such processes both as a scholar and as a member of society. Trained in gender and ethnicity studies at the University of Utrecht in the Netherlands, Spitzer-Hanks earned a PhD in English studies from the University of Texas at Austin. In their private life, Spitzer-Hanks enjoys gardening, parenting, and running from their anxieties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.481
Threshold uncertainty score0.686

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0070.004
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.5190.324

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.031
GPT teacher head0.323
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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