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Record W2914723692 · doi:10.22545/2019/0114

Transdisciplinarity at the Boundaries: Exploring a Sylvan Metaphor for Health

2019· article· en· W2914723692 on OpenAlex

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.

Bibliographic record

VenueTransdisciplinary Journal of Engineering & Science · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTransdisciplinarityMetaphorSociologyEpistemologyAppropriationEcologySocial scienceBiologyPhilosophy

Abstract

fetched live from OpenAlex

Transdisciplinarity is an action-oriented intellectual and ethical endeavor to address complex ecological, economic, and political challenges that humans face. Language is viewed as a powerful tool for necessary cultural change. Blending art and science looking for the difficult to define but critically important hidden spaces between apparently rigid conceptual structures is a core of transdisciplinarity. Metaphor is a particular powerful tool for examining boundaries and developing creative blends of structures and processes. Forests are biologically and culturally critical to life on the planet. In this paper we explore, a performance character named Sylvanus, the Tree Doctor, named after the Roman god of forests and boundaries. We consider the importance of intergenerational learning as a process for deeper reflection on human responsibility over time. Transdisciplinarity is energized by intergenerativity and collective wisdom. Systemic and holistic conceptions of health will be essential for the survival and reinvention of human civilization in better balance with planetary ecosystems.

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.003
Open science0.0030.000
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 head0.105
GPT teacher head0.407
Teacher spread0.302 · 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