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Record W3156755451 · doi:10.31468/dw/r.829

What Can Students Tell Us about “Skill Building” in Canadian Writing Studies?

2021· article· en· W3156755451 on OpenAlexaffvenueabout
Christopher Eaton

Bibliographic record

VenueDiscourse and Writing/Rédactologie · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicDiscourse Analysis in Language Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsNarrativeProcess (computing)Class (philosophy)Mathematics educationWork (physics)PedagogyValue (mathematics)Professional writingWriting processPsychologySociologyComputer scienceEngineeringLiteratureArt

Abstract

fetched live from OpenAlex

This paper comes from narrative research that I did with ten former students who reflected on their experiences with writing both in a first-year writing class and beyond. As the participants and I worked together, it became clear that there was the tension between the way they described process and skill building in writing pedagogy. They emphasized that process and scaffolding were integral to their learning, but they equally emphasized the one-off, skills-oriented components of our work. Many conversations in Canadian writing studies have focused on dismantling or resisting the skills narrative, but the tension in the participants’ responses prompted me to think about this differently. The paper explores the tension between skills and process to argue that perhaps skill building has its place in our contexts, and that we as writing teachers and scholars must think about it differently in order to articulate the value of the work that we do. If we can use the skills-oriented components of our courses to open spaces to discuss the less quantifiable elements of our work that often get overlooked (i.e., scaffolding), then we may put ourselves in a better position to advocate for increased resources and funding.

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 categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.814
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.092
GPT teacher head0.417
Teacher spread0.325 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

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