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Record W2561680115 · doi:10.14746/se.2016.38.20

Analyzing Stories from Canadian Academic Writing Instructors: A Collaborative Autoethnography

2016· article· en· W2561680115 on OpenAlexaboutno aff
Jordana Garbati, Boba Samuels

Bibliographic record

VenueAdam Mickiewicz University Repository (Adam Mickiewicz University in Poznan) · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsnot available
Fundersnot available
KeywordsAutoethnographyAcademic writingCollaborative writingSociologyPedagogyMedia studiesPsychologyGender studies

Abstract

fetched live from OpenAlex

Writing instruction in Canadian universities takes a variety of forms. While there are few formal departments for writing studies, many institutions do have a writing centre – a place that offers writing instruction to varying degrees. The writing centre may be housed within a department, a library, or within a student services unit. Its position within a university may indicate the degree to which writing is valued by the administrative body. The goal of our paper is to share insights into the ways that writing professionals perceive, work in, and adapt to current demands for writing instruction in higher education. Using a collaborative ethnographic approach, three scholars at different career stages explore their experiences with writing centre work. Using data consisting of individually written reflections, our analysis revealed four major themes: (a) initial experience with writing centres, (b) community, (c) frustrations and tensions at work, and (d) mentorship. In this paper, we discuss our findings within the framework of positioning theory in order to understand how we position ourselves as scholars, mentors, and educators, and how we are positioned by others within the fields of writing studies and higher education. This study raises awareness about the value of writing centre professionals’ contributions, the place of mentorship within higher education, and the support required for continued writing centre work.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.741
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0030.002
Scholarly communication0.0000.004
Open science0.0020.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.278
Teacher spread0.265 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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