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Developing Institutional Leadership for the Scholarship of Graduate Student Supervision: Lessons Learned in a Canadian Research-Intensive University

2016· book-chapter· en· W2492183870 on OpenAlexaboutno aff
Anthony Clarke, Harry Hubball, Andrea S. Webb

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipPromotion (chess)Context (archaeology)Formative assessmentMedical educationPolitical scienceSummative assessmentGraduate studentsEducational leadershipPedagogyLibrary scienceSociologyMedicine

Abstract

fetched live from OpenAlex

Abstract This chapter examines a recently launched initiative for developing institutional leadership for scholarly approaches to and the Scholarship of Graduate Student Supervision (SoGSS) at the University of British Columbia (UBC). This initiative is led by the Dean, Associate Dean, and former Associate Dean of the Faculty of Graduate and Postdoctoral Studies and is supported by a team of National Teaching Fellows and a graduate student. It involves a customized graduate student supervision (GSS) leaders’ cohort within the International Faculty SoTL Leadership Program at UBC. The initiative arose from institutional concerns about quality assurance and strategic supports for the enhancement of GSS in UBC’s multidisciplinary research-intensive context. The following were noted: (1) widespread discrepancies in the ways that GSS (sometimes referred to as mentoring) is being taken up and exercised across campus; (2) lack of strategic leadership for GSS within units and related professional development initiatives; and (3) inadequate faculty assessment and evaluation protocols (e.g., formative for professional development purposes or summative for tenure, promotion and reappointment purposes) for discipline-specific GSS practices.

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)0.003
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.900
GPT teacher head0.619
Teacher spread0.281 · 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
GenreOther

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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