Evoking Losing and Finding Community in Drama: A Methodology-in-Motion for Pandemic Times
Bibliographic record
Abstract
Our article explores the impact of the global health pandemic on our five-year, multi-sited, collaborative ethnographic study titled Global Youth (Digital) Citizen-Artists and their Publics: Performing for Socio-Ecological Justice (2019-2024). We illustrate how our arts-led, youth-driven ethnographic ”methodology-in-motion” responded to a destabilized world by planning, listening, and seeing differently across local and global research contexts through virtual fieldwork. By focusing on reciprocity and the relational, we examine how researchers, youth participants, and global collaborators, managed to ”lose” and ”find” each other through creative, artistic encounters.
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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 | 0.047 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.046 |
| Scholarly communication | 0.017 | 0.014 |
| Open science | 0.004 | 0.023 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".