Sustainability from the Inside Out: The Labyrinth as a Tool for Deepening Conversations in Higher Education
Bibliographic record
Abstract
First published advance online December 16, 2019This article describes a methodology of convening a community conversation, which took place during the 2018 Workshop on Regional Centres and the Sustainability of Canada’s Rural and Northern Landscapes held at Lakehead University in Thunder Bay, Ontario. In what follows, we both theorize and narrate the use of the labyrinth—a circular, circuitous walking path—as a tool for accessing another way of knowing, and for sharing personal vision for collective reflection and engagement. First, the labyrinth is described as an intervention into business-as-usual in academic, workshop, or conference settings. In this section, we briefly theorize the use of the labyrinth as a form of cultural reinvention. Next, we describe the labyrinth as a dynamic, transformational process that taps into embodied, interior experience, drawing it out into collective view. This process, centred on walking the labyrinth and sitting in a listening circle, challenges participants to identify and express their chief motivating purposes, as well as the internal barriers they face in meeting their most valued aims. Central to this process is attending to the close relationship between experience and reflection, thinking and feeling, and speaking and listening—at both individual and collective levels. The article concludes with observations about how the labyrinth and the listening circle can be used in higher education, and other workplace contexts, as a tool for creating space for fostering sustainability from the inside out.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.032 |
| Scholarly communication | 0.014 | 0.016 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".