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Record W4403672547 · doi:10.18357/otessaj.2024.4.2.79

Cross-Curricular, Inquiry-Based Collaborative Learning in Support of Truth and Reconciliation

2024· article· en· W4403672547 on OpenAlexaffvenueabout
Deirdre Houghton, Gary Soles, Andrew Vogelsang, Valerie Irvine, François Prince, Leona Prince, Carla Martin, Jean‐Paul Restoule, Michael Paskevicius

Bibliographic record

VenueThe Open/Technology in Education Society and Scholarship Association Journal · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCollaborative learningPsychologyMathematics educationPedagogy

Abstract

fetched live from OpenAlex

This project was conducted at Fort St. James Secondary School in the Nechako Lakes School District, which is in Northern British Columbia, Canada. Three high school teachers from different disciplines (Social Studies, Digital Media, and Carpentry) launched a cross-curricular inquiry-based project in partnership with local knowledge holders and School District 91, focusing on truth and reconciliation, which connected the learners in their high school with the broader community, including knowledge holders from the local Indigenous communities. Those engaged in the project examined questions around what truth and reconciliation meant to the learners and its significance. This project was completed in 2021 and resulting products included a legacy wall, installed as a permanent fixture in the school, containing individual learning represented in motifs, design of the feather using wood from around the world, and a video documentary containing interviews from school and community stakeholders.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.399
Teacher spread0.369 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes3
Has abstractyes

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