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Record W4386422057 · doi:10.1007/s10437-023-09541-w

Why Weaving? Teaching Heritage, Mathematics, Science and the Self

2023· article· en· W4386422057 on OpenAlex
Allison Balabuch, Bako Rasoarifetra

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAfrican Archaeological Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsWeavingMathematics educationPatienceValue (mathematics)Point (geometry)ArchaeologySociologyEngineeringHistoryMathematicsPsychologyMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Weaving provides an access point to teach students about the heritage and the dynamic cultural importance of weaving practices in Africa. Weaving education teaches patience and perseverance. It also teaches math from a practical and problem-solving stance, which values ethnomathematical knowledge and skills. Weaving teaches science through the understanding and environmental sustainability of local plants and their practical uses. Throughout this article, we have interwoven our own teaching stories from Canada and Ghana (Allison Balabuch) and Madagascar (Bako Rasoarifetra) through the themes of heritage, mathematics, science, and the development of the self. This article discusses the importance and value of including weaving education into the classroom.

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.

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)0.007
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.006
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.024
GPT teacher head0.310
Teacher spread0.286 · 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