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Record W2754204046 · doi:10.1177/1541344616680350

Activating Hope in the Midst of Crisis

2016· article· en· W2754204046 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

VenueJournal of Transformative Education · 2016
Typearticle
Languageen
FieldPsychology
TopicEgo Development and Educational Practices
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsTransformative learningCompassionAction (physics)GratitudeGriefPsychologyConstructiveProcess (computing)Action learningSocial psychologyEnvironmental ethicsSociologyPsychotherapistPedagogyPolitical scienceCooperative learningTeaching method

Abstract

fetched live from OpenAlex

Joanna Macy’s “Work that Reconnects” (WTR) is a transformative learning process that endeavors to help participants acknowledge, experience, and understand the emotions that may either empower or inhibit action to address the ecological crisis. The WTR seeks to work through grief, fear, and despair to animate a sense of active, empowering hope rooted in gratitude, compassion, imagination, community, and collective action. Drawing on theoretical perspectives from neuroscience, ecopsychology, and transformative learning, this paper analyzes how emotions may either impede or facilitate active engagement in ecological issues. The assumptions, goals, and process of the WTR are then presented in light of these insights. Finally, a case study involving the use of the WTR with young adults along with their reflections on the experience are considered to illustrate how the process may be employed as well as to analyze some of the benefits, challenges, and limitations of using this transformative learning process.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.682
Threshold uncertainty score0.476

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 studies0.0000.000
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 head0.036
GPT teacher head0.382
Teacher spread0.346 · 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