Mundane Joy as Emergent Strategy: Community Storytellers on “Happiness,” “Resilience,” and the “Good Life”
Bibliographic record
Abstract
This essay traces how community-based activist storytellers make room for emergent strategies in perilous times. It was sparked by the authors’ experience of working between two distinct communities that are both deeply invested in understanding the function of story-and-art-making in troubled and troubling times. For brevity’s sake, we will refer to the first community as the collective of “arts-based community-making” groups with whom we work under the auspices of the Centre for Community-Engaged Narrative Arts in Hamilton, Ontario, Canada. Our second community is the Spain-based RESHAP international group of literary and cultural studies scholars who are studying the theme of “Narrativas de la felicidad y la resiliencia / Narratives of Happiness and Resilience.” In the context of “risk society”—the widespread perception of life on earth as dangerous, vulnerable, and fraught with complex hazards—popular media, governments, and corporations, in addition to school systems, public think tanks, and the self-help industry often urge people to generate what Sara Ahmed has called “happiness scripts,” to keep positive and be resilient. These “scripts” become directive, insofar as stories of happiness, the good life, or resilience become mechanisms of discipline or coercive governance that can elicit what Lauren Berlant has called “cruel optimism.” Our essay teases out the emergent possibilities, the creative potential, that we see arising from community-based story-makers’ navigation of the tension between these (required) stories of the “good life” and the everyday, emergent strategies they invent in the midst of challenging times.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".