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Record W4403764070 · doi:10.24908/pceea.2023.17163

Reflections on "Voices from the Heart" Workshop

2024· article· en· W4403764070 on OpenAlexaffvenue
Dimpho Radebe, R. Paul, Kim Johnston, Kai Zhuang

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2024
Typearticle
Languageen
FieldNeuroscience
TopicCognitive Science and Education Research
Canadian institutionsUniversity of CalgaryYork UniversityUniversity of Toronto
Fundersnot available
KeywordsSociology

Abstract

fetched live from OpenAlex

The work of education innovation is stressful, challenging, and at times isolating. Through the delivery of a workshop we developed, we create an intimate and brave space to explore our own well-being and thriving using the practices of intention setting, embodiment, and wisdom circles, and facilitate a basic understanding of the neurobiology behind stress, trauma, and learning. In this practice paper, we review the process and literature used to develop the workshop. We share lessons learned from delivering the workshop. These are highlighted to demonstrate the empirical value that this workshop, as a practice, brings to the engineering education community. Based on initial offerings of the workshop, the authors have observed that participants have found the workshop to be a beneficial process that enables them to connect more deeply to themselves and to others within the engineering education community.

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)0.034
metaresearch head score (Gemma)0.075
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.179

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.075
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0200.014
Scholarly communication0.0200.013
Open science0.0060.026
Research integrity0.0180.035
Insufficient payload (model declined to judge)0.0140.006

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 head0.052
GPT teacher head0.350
Teacher spread0.298 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2024
Admission routes2
Has abstractyes

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