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Record W3015881161 · doi:10.1080/02697459.2020.1748331

Demystifying Academic Writing in the Doctoral Program: Writing Workshops, Peer Reviews, and Scholarly Identities

2020· article· en· W3015881161 on OpenAlex
Bjørn Sletto, Kristine Stiphany, Jane Futrell Winslow, Andrea Roberts, Marla Torrado, Alejandra Reyes, Ariadna Reyes, Juan G. Yunda, Christina Wirsching, Kwangyul Choi, Kristina Tajchman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePlanning Practice and Research · 2020
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIdentity (music)PedagogySociologyWriting processAcademic writingProcess (computing)Computer science

Abstract

fetched live from OpenAlex

This article discusses a course at The University of Texas at Austinwhich sought to facilitate doctoral students’ development of scholarly articles while simultaneously fostering their sense of scholarly identity. The article was co-authored by the instructor and two cohorts of doctoral students based on immediate as well as retrospective learning outcome assessments. The social constructivist approach to writing pedagogy fostered students’ scholarly identities and demystified the publication process. However, efforts should be made to maintain the practice of writing, sharing, and reviewing and the course should more explicitly foster critical reflections on the relationship between writing, scholarly identity, and knowledge production.

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.

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)0.014
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.005
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 head0.739
GPT teacher head0.681
Teacher spread0.058 · 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