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Ways of Knowing and Becoming: Learning Together in a Graduate Course on Interdisciplinarity

2023· article· en· W4389314116 on OpenAlexaffvenue
Andrea Breen, Tasha Falconer, Kimberly Squires, Stéphanie Martin, Anna Swain, E. Lipiński, Kaitlyn Avery, Cara Briscoe, C. Marchand, Madison Myers, Nicole Wylie-Curia, Stephanie Bryenton, Ariana Sams

Bibliographic record

VenueThe Canadian Journal for the Scholarship of Teaching and Learning · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSociologyScholarshipEmbeddednessAxiologyPedagogyHumanitiesEpistemologySocial sciencePolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Developing as a scholar is a critical aspect of graduate school. In this article, we use an autoethnographic approach to explore our experiences in a newly redeveloped interdisciplinary graduate course. The course was designed to emphasize interdisciplinary scholarship and to encourage students’ awareness of their own developing epistemological, ontological, and axiological commitments. In this paper, we identify themes that arose from the final class paper, in which the students/researchers reflected on our development as emerging scholars. Through this course we developed an understanding of the value of interdisciplinarity, the cultural embeddedness of knowledge, and our own responsibilities as researchers in relation to social structures of power and marginalization. Our analyses of our experiences suggests that reflections on our own positionality and axiology are important for developing our identities as emerging scholars and that becoming a scholar may be more about the process than an end goal. We conclude with a discussion of how our learning in this course may be relevant for other instructors and emerging scholars.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0340.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0000.000

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 head0.299
GPT teacher head0.451
Teacher spread0.152 · 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; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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