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Record W4409838785 · doi:10.22545/2025/00275

Enriching Transdisciplinary Discourse with Nonviolence

2025· article· en· W4409838785 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 · 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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.010
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