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Record W4389283630 · doi:10.22545/2023/00235

Shifting Paradigms: Bringing Transdisciplinarity into the Light

2023· article· en· W4389283630 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 · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicInterdisciplinary Research and Collaboration
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsTransdisciplinarityDisciplineParadigm shiftSociologySet (abstract data type)EpistemologyEngineering ethicsFaithSocial scienceComputer scienceEngineeringPhilosophy

Abstract

fetched live from OpenAlex

Addressing complex societal problems requires the collaboration of diverse academic and non-academic partners ideally through transdisciplinarity. Most academic faculty members are couched in their disciplinary mind set with more recent transitions to multi- and interdisciplinarity. Transdisciplinary thinking is the new kid on the block. Switching through mono, multi, and inter to transdisciplinarity will require a paradigm shift. Each is discussed in this paper, so people can more readily find themselves, clarify the nature of their work, and appreciate the magnitude of change required if they shift paradigms. The paper then (a) identifies traits of a transdisciplinary individual who can employ a transdisciplinary orientation, (b) addresses paradigm shifts at the collective and individual levels, (c) discusses how to deal with natural resistance to losing one’s familiar way of thinking and (d) concludes with touchstones and safety-nets that encourage people to take the leap of faith required to embrace transdisciplinarity.

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)0.018
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.257
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.011
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0040.000
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 head0.050
GPT teacher head0.380
Teacher spread0.330 · 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