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Record W1527986725 · doi:10.22329/celt.v7i1.3990

Knowledge mobilization across boundaries with the use of novel organizational structures, conferencing strategies, and technological tools: The Ontario Consortium of Undergraduate Biology Educators (oCUBE) Model

2014· article· en· W1527986725 on OpenAlexaffvenueabout
Lovaye Kajiura, Julie Smit, Colin J. Montpetit, Tamara Kelly, Jennifer A. Waugh, Fiona Rawle, Julie Clark, Melody Neumann, Michelle French

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsUniversity of TorontoUniversity of WindsorUniversity of OttawaWestern UniversityYork UniversityMcMaster University
Fundersnot available
KeywordsFace (sociological concept)Mathematics educationSociologyPedagogyPsychology

Abstract

fetched live from OpenAlex

The Ontario Consortium of Undergraduate Biology Educators (oCUBE) bringstogether over 50 biology educators from 18 Ontario universities with the commongoal to improve the biology undergraduate experience for both students andeducators. This goal is achieved through an innovative mix of highlyinteractive face-to-face meetings, online conferencing platforms (wiki andvideo conferencing), monthly online newsletters, and other activities. The beautyof the oCUBE model is that it meshes with the active learning methods that itsmembers use in their own teaching. It also creates a community of practice withintra- and inter-institutional collaborations that assist in resolving educationalissues of both common and immediate importance to oCUBE members. oCUBE membersreport that oCUBE activities and resources are very effective in helping themlearn new teaching strategies and in developing professionally.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.318
Teacher spread0.274 · 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

Citations1
Published2014
Admission routes3
Has abstractyes

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