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Record W2593228436 · doi:10.1177/1541344617696973

Seeds and Stories of Transformation From the Individual to the Collective

2017· article· en· W2593228436 on OpenAlex
Catherine Etmanski

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

VenueJournal of Transformative Education · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsTransformative learningPatienceContext (archaeology)NarrativeSociologySocial transformationPsychologyPedagogySocial changePolitical scienceSocial psychologyHistoryLaw

Abstract

fetched live from OpenAlex

This article documents the author’s experience participating in a course taught primarily by food activist, Dr. Vandana Shiva, and run by the Earth University in Uttarakhand, India. Drawing on Gandhi’s four pillars of nonviolent action, this article links individual course participants’ experiences of transformative learning to the transformation of the global food system. It begins with a brief overview of the course content and structure followed by a transformative learning literature review. It then provides sample participant narratives exemplifying various aspects of their own transformation and suggesting that this course supported participants in their already-in-progress process of transformation. The important role community-based organizations such as Navdanya play in efforts for global food systems transformation is also discussed. Within the context of personal and social transformation, the article concludes with a call for transformative learning to be accompanied by patience, particularly in light of the urgency created by today’s complex challenges.

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)0.001
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 score0.406
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.038
GPT teacher head0.352
Teacher spread0.313 · 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