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Record W4409838785 · doi:10.22545/2025/00275

Enriching Transdisciplinary Discourse with Nonviolence

2025· article· en· W4409838785 on OpenAlexaff
Sue L. T. McGregor

Bibliographic record

VenueTransdisciplinary Journal of Engineering & Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsMount Saint Vincent University
FundersNational Cancer Institute
KeywordsEpistemologySociologyLinguisticsPhilosophy

Abstract

fetched live from OpenAlex

Those engaged in transdisciplinary work and collaboration will encounter both positive and negative conflict. People can deal with negative conflict using violence or nonviolence. Violence is power over people, but nonviolence is power from within. Successful resolution of complex, wicked problems will require people to make significant changes in their human behavior. Nonviolence is proposed as a key element of this behavioral change. This paper brings the Gandhian notion of nonviolence to transdisciplinary discourse (i.e., communicating and exchanging thoughts and ideas with the intent to integrate into new knowledge). The objective of nonviolence is not to win or beat an opponent but to stop an injustice and change the situation. This entails learning and mastering the principles of nonviolence, which include several key concepts addressed in the paper: Satyagraha, seeking the Truth, self-discipline, self-sacrifice, suffering, no harm, resistance, and right actions.

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)0.029
metaresearch head score (Gemma)0.027
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0200.058
Scholarly communication0.0210.030
Open science0.0020.028
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.332
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
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
Published2025
Admission routes1
Has abstractyes

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