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Record W2043005291 · doi:10.1080/13611261003678903

Storying the Terroir of Collaborative Writing: Like Wine and Food, a Unique Pairing of Mentoring Minds

2010· article· en· W2043005291 on OpenAlex
Shelley M. Griffin, Rodger J. Beatty

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueMentoring & Tutoring Partnership in Learning · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsBrock University
Fundersnot available
KeywordsTerroirWinePsychologyPairingFood scienceChemistry

Abstract

fetched live from OpenAlex

As two faculty members in a Canadian post‐secondary teacher education context, the authors inquired into their collaborative writing process initiated through an informal faculty mentoring relationship. Situating their writing in the discourses of personal practical knowledge, social constructionism, narrative inquiry, and autobiography grounds their understanding of relational writing as side‐by‐side collaborators who engage in a bodily co‐present writing process, negotiating the many nuances of text construction. By using a metaphor of carefully pairing exquisite wine with fine food, they convey the mutual co‐construction of their lived experiences that evolve through relational writing. Highlighting related literature in the areas of mentoring, writing terminology, traits of collaborators, writing process, and benefits of collaboration assists them in comparing and contrasting the literature with features unique to their own collaboration. They conclude by noting critical issues and implications regarding collaborative writing that offer insight into the importance of honoring collaborative scholarship within academic contexts.

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.040
GPT teacher head0.378
Teacher spread0.337 · 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