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Record W3083668948 · doi:10.37514/per-b.2016.0810.2.05

Chapter 5. Integrating Writing into the Disciplines: Risks and Rewards of an Alternative Independent Writing Program

2016· book-chapter· en· W3083668948 on OpenAlexaff
W. Bruce MacDonald, Margaret Procter, A. Williams

Bibliographic record

VenueThe WAC Clearinghouse; University Press of Colorado eBooks · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWriting and Handwriting Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceMathematics educationPsychology

Abstract

fetched live from OpenAlex

2005-06, when there were only 45 institutions with such a major (CCC Committee on the Major in Writing and Rhetoric, 2009).To McLeod, a "robust research agenda and a thriving writing majors" will offer writing programs the best chance to achieve independence (2006, p. 532). THE CENTRAL ISSUES: WHERE ARE WE NOW?In this introduction we have considered the relatively brief history of the evolution of independent writing programs and departments, along with the issues that have been raised (primarily) in the literature on writing program administration.Our first observation is the dominance of the "separation narrative" in this literature, particularly after 1990 when most independent programs and departments began to separate from their home departments.(Of course, we recognize that a number of independent departments existed before this date.However, before this time, generally speaking, they were likely anomalies; following this they may be considered to be part of a disciplinary trend.)A second observation, drawn largely from the work of James Berlin, is that institutional and disciplinary issues that have led to separation have a long and complex history connected to the evolution of the American professional university.As the university continues to evolve there is not a single trend, but many.Liberal arts

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.692
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.055
GPT teacher head0.319
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 designTheoretical or conceptual
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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

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