Building Community: Vocabularies and Rituals Used to Define and Process Climate Grief by Politically Active Youth in Mi'kma'ki
Bibliographic record
Abstract
There are many terms that exist to describe and define climate grief but the vocabularies that youth use to describe climate grief are not well defined. The purpose of this research was to identify the vocabularies that politically active youth use to describe and define climate grief and the rituals that they use to process it through a poetry workshop, interviews, and arts-based engagement. Twenty youth ages 12-29 living in Mi’kma’ki (Atlantic Canada) engaged in political activism connected to climate change participated in individual interviews to understand their journey to becoming politically active, their personal experiences of climate grief, and how they define and manage their climate grief on a day-to-day basis. Five of those twenty youth participated in a facilitated poetry workshop that guided them through writing poetry expressing their definitions of and experiences with climate grief, followed by a focus group debriefing their experience in the workshop. An additional three of the twenty participants submitted individual visual and written pieces of art on climate grief and participated in short interviews following their submission. The main vocabularies used to define and describe climate grief were found to be in contrast: full of despair and focused on apocalypse; and full of hope and centered on community and building just futures. Additionally, participants identified that community-centered rituals that involved tangible change or meaningful interactions were crucial for helping them manage their grief through rituals.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".