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Record W7106029949 · doi:10.3138/jsp-2025-0005

A Trioethnographic Exploration of Co-Authoring in Higher Education: Perspectives of a PhD Student, a Supervisor, and an Editor

2025· article· en· W7106029949 on OpenAlexvenueno aff

Bibliographic record

VenueJournal of Scholarly Publishing · 2025
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsDialogicPublishingPower (physics)Affect (linguistics)Hofstede's cultural dimensions theoryKey (lock)

Abstract

fetched live from OpenAlex

As co-authoring becomes more prevalent internationally and across disciplines, there is a pressing need to examine the experiences of co-authors to understand how differing author identities and hierarchies may affect each author’s experience. This trioethnographic study, in which three researchers explored their experience of co-authoring through dialogic inquiry, offers a critical, reflective analysis of three publication stakeholders: a doctoral student, a doctoral supervisor, and a journal editor. Key findings emerge under two themes: ‘Working together benefits us all’ and ‘Working together isn’t always easy.’ While co-authoring fosters synergy, motivation, collegiality, and professional growth, it also surfaces challenges related to working styles, power dynamics, and cultural differences. These findings urge the authors to question existing beliefs about power imbalances within co-authoring relationships and challenge the expectations placed on PhD students and supervisors, with the aim of achieving more inclusive and sustainable publishing practices. Methodologically, this study promotes trioethnography as a legitimate approach to investigate relationships across cultural and geographical borders.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.031
Open science0.0000.000
Research integrity0.0000.001
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 head0.349
GPT teacher head0.549
Teacher spread0.200 · 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; a candidate call from one teacher head, not a consensus.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

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