MétaCan
Menu
Back to cohort
Record W4389068354 · doi:10.55016/ojs/ajer.v68i4.73428

Supporting Graduate Writers Through a Writing Commons

2022· article· en· W4389068354 on OpenAlexaffvenue
Christopher Eaton, Jill Dombroski

Bibliographic record

VenueAlberta Journal of Educational Research · 2022
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsWestern UniversityUniversity of Toronto
Fundersnot available
KeywordsGraduate studentsGraduate educationCommonsSociologyLibrary sciencePolitical sciencePedagogyComputer scienceLaw

Abstract

fetched live from OpenAlex

This paper reports on how we developed a Writing Commons to support graduate student needs within our faculty. Graduate writers often require more concentrated and specific support than traditional support sources (e.g., writing centres, supervisors) can provide. We argue that local writing support spaces, like a Writing Commons, can meet these needs for graduate writers by opening a flexible, student-centric space for both writing support and time to write. We detail how faculties can go beyond just establishing graduate communities and instead provide concentrated writing support for graduate students. A Writing Commons can mitigate the isolation and pressures of the high stakes writing experiences that graduate students face by providing feedback and support, space to discuss common writing challenges within a program, and community with other writers. Near the end of the paper, we discuss steps that others can take to increase support for graduate writers. Keywords: graduate education, graduate writing, writing support, writing groups, faculty support Cet article rend compte de la façon dont nous avons développé un centre d'écriture commune pour répondre aux besoins des étudiants diplômés au sein de notre faculté. Les écrivains diplômés ont souvent besoin d'un soutien plus concentré et plus spécifique que celui que les sources de soutien traditionnelles (p. ex., les centres d'écriture, les superviseurs) peuvent offrir. Nous soutenons que les espaces locaux de soutien à l'écriture, comme les centres d'écriture, peuvent répondre à ces besoins des écrivains diplômés en ouvrant un espace polyvalent, centré sur l'étudiant, à la fois pour le soutien à l'écriture et pour le temps d'écrire. Nous expliquons en détail comment les facultés peuvent aller au-delà de la simple création de communautés d'étudiants diplômés et offrir plutôt un soutien à l'écriture visant les étudiants diplômés. Un centre d'écriture peut atténuer l'isolement et la pression des expériences d'écriture à enjeux élevés auxquelles les étudiants diplômés sont confrontés en fournissant des commentaires et du soutien, un espace pour discuter des défis d'écriture communs au sein d'un programme et une communauté avec d'autres écrivains. Vers la fin du document, nous discutons des mesures que d'autres peuvent prendre pour accroître le soutien aux rédacteurs diplômés. Mots clés : enseignement supérieur, rédaction pendant les études supérieures, soutien à la rédaction, groupes de rédaction, soutien du corps enseignant

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0090.006
Scholarly communication0.0110.013
Open science0.0040.033
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0150.005

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 head0.628
GPT teacher head0.666
Teacher spread0.038 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueAlberta Journal of Educational ResearchSame topicDoctoral Education Challenges and SolutionsFrench-language works237,207