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Record W4392053159 · doi:10.26522/brocked.v33i1.1120

Well-Being Literacy in the Academic Landscape: Trioethnographic Inquiry Into Scholarly Writing

2024· article· en· W4392053159 on OpenAlexvenueno aff
Narelle Lemon, Jacqui Francis, Lisa M. Baker

Bibliographic record

VenueBrock Education Journal · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracySociologyAcademic writingPedagogy

Abstract

fetched live from OpenAlex

Writing well and being well as academic writers is rarely spoken about, often hidden, and at times evaded. We believe that developing, maintaining, and growing well-being literacy not only engages the act but also allows awareness, reflection, and metacognitive thinking that enable mindful writing for well-being. Well-being literacy, the capacity to understand and employ well-being language for personal, collective, and global well-being, intrigues us. It encompasses nurturing, sustaining, and safeguarding well-being for individuals, groups, and systems to thrive. As scholars delving into well-being literacy, we, a diverse collective from across higher education career trajectories, investigate its role in scholarly writing and our academic realities. Our focus lies in unraveling the paradoxes inherent in higher education, particularly as researchers and writers. In this paper, we examine our own stories as a trioethnography and the impact of our writing practices on our own professional and personal lives. By doing so, we reveal the place of vulnerability, relationships, and meaning in who we are and are becoming as academic scholars. Guiding principles are shared with peers and colleagues in how they might cultivate writing practices while valuing and embodying well-being in the higher education space.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.378
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.346
Teacher spread0.318 · 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 designQualitative
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

Citations3
Published2024
Admission routes1
Has abstractyes

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