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Record W2413570892 · doi:10.1002/tl.20187

SoTL<sup>2</sup>: Inquiring into the Impact of Inquiry

2016· article· en· W2413570892 on OpenAlexaffabout
Janice Miller‐Young, Michelle Yeo, Karen Manarin, Miriam Carey, J. Christopher Zimmer

Bibliographic record

VenueNew Directions for Teaching and Learning · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsMount Royal University
Fundersnot available
KeywordsContext (archaeology)MountScholarship of Teaching and LearningInstitutionImpact evaluationSociologyPedagogyPsychologyEngineeringTeaching methodSocial scienceGeographyTeaching and learning centerArchaeologyMedicine

Abstract

fetched live from OpenAlex

This chapter briefly describes the SoTL research development program and context at Mount Royal University, reports initial results from a study of the program's impact on participants’ teaching and scholarly activities, and situates the findings regarding individual impact, department‐level impact, institution‐level impact, and discipline‐level impact within the current literature and the Canadian context.

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)0.030
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.970
Threshold uncertainty score0.193

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.063
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0060.013
Scholarly communication0.0080.005
Open science0.0010.007
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.090
GPT teacher head0.444
Teacher spread0.353 · 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.

Study designObservational
DomainEvaluation
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

Citations7
Published2016
Admission routes2
Has abstractyes

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