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Record W4412072973 · doi:10.36510/learnland.vi29.1145

Propositions for Sustainable Relationalities

2025· article· en· W4412072973 on OpenAlexaffvenue
Nicole Y. S. Lee, Ken Morimoto, Melissa Boucher-Guilbert, Fayrouz Ibrahim, Rebecca Zynomirski

Bibliographic record

VenueLEARNing Landscapes · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsNSCAD University
FundersJapan Society for the Promotion of Science
KeywordsBusinessComputer science

Abstract

fetched live from OpenAlex

From November 2023 to June 2024, an a/r/tographic study group gathered to engage with the concept of sustainable relationality. With the methodology of a/r/tography and propositional thinking, the relational gathering became an experimental curricular uncommonplace, a messy yet nourishing place from which to envision different ways of working and being. After introducing the intentions and theoretical background of the study, two art-based engagements that emerged for two groups of master’s students are offered. Reflecting on the transitions undergone by these groups, we speculate on the conditions that might enable similar educational opportunities for human flourishing sustained by deep relational encounters.

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)0.006
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0050.032
Scholarly communication0.0100.012
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0150.002

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 head0.054
GPT teacher head0.376
Teacher spread0.322 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2025
Admission routes2
Has abstractyes

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