Breathing New Legacies Forward
Bibliographic record
Abstract
This article unravels the meaning, purpose, and working philosophy underpinning Arrivals Legacy Voice, which is an emerging practice coming out of the Arrivals Legacy Project=. Arrivals Legacy Project founder Diane Roberts (Garifuna, Caribbean Canadian) engages her collaborators in reflection on specific moments of discovery and emerging themes and/or collisions that have influenced and continue to influence the ongoing development of our shared practice. The voices of storyteller and film-maker Rosemary Georgeson (Coast Salish), voice and speech instructor and Rolfer Lopa Sircar (Bengali, Canadian), voice/movement educator and inter-arts creator/performer Gerry Trentham (Scottish, English), and facilitator, writer, and systemic and experiential therapist Jude Wong (Chinese, German, Danish) address the central question: What new legacies breathe us forward, and what must we leave behind? Using the generative methodology of Legacy Voice, Diane and her collaborators draw on the personal to reveal their passion for un/recovering root cultural practices as a liberation from colonial performative inheritances.
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 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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.053 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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".