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Record W4251473839 · doi:10.20343/9.1.26

A Developmental Framework for Mentorship in SoTL Illustrated by Three Examples of Unseen Opportunities for Mentoring

2021· article· en· W4251473839 on OpenAlexaff
Jennifer C. Friberg, Mandy Frake-Mistak, Ruth L. Healey, Shannon Sipes, Julie Mooney, Stephanie Sanchez, Karena L. Waller

Bibliographic record

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversity of AlbertaYork University
Fundersnot available
KeywordsMentorshipOperationalizationScholarship of Teaching and LearningScholarshipOrder (exchange)Mathematics educationPsychologyComputer scienceSociologyTeaching methodEpistemologyMedical educationTeaching and learning centerPolitical sciencePhilosophyMedicine

Abstract

fetched live from OpenAlex

Mentoring relationships that form between scholars of teaching and learning occur formally and informally, across varied pathways and programs. In order to better understand such relationships, this paper proposes an adapted version of a three-stage model of mentoring, using three examples of unseen opportunities for mentoring in the Scholarship of Teaching and Learning (SoTL) to illustrate how this framework might be operationalized. We discuss how the adapted framework might be useful to SoTL scholars in the future to examine mentorship and how unseen opportunities for mentoring might shape how we consider this subset of mentorship going forward.

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)0.019
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0100.029
Scholarly communication0.0090.011
Open science0.0030.014
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.239
GPT teacher head0.436
Teacher spread0.197 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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