Voices at the Edge of the Woods:An immersive soundscape of Haudenosaunee diplomatic speech and song
Bibliographic record
Abstract
This unique collection of seven Soundscapes, co-produced with the Mohawk and Cayuga Indigenous Nations (Canada, United States), is the first to use high-definition sound to transform understanding of speech-driven historical diplomacy between the nations of the Haudenosaunee and British imperial officials and diplomats. They are a new creative form of research expression and a model for the collaborative recovery of complex inter-cultural histories, the first such collaboration permitted by the Nations concerned and therefore an ongoing primary point of reference for understanding diplomacy between the Haudenosaunee, Great Britain, Canada and the United States. They engage with the complex problem of how to generate new thinking and practices that set aside settler narratives and instead foreground Indigenous oral epistemologies and interpretation of intercultural diplomatic experience. They do so by radically expanding the range and depth of available material, creating innovative oral source data that recovers endangered Mohawk language forms via new translations of under-researched English historic records, and creating new co-produced interpretation of Indigenous metaphor, song and wampum. They are a novel expansion of understanding that reveals Indigenous diplomatic practices, previously understood as locked in history, to be active, dynamic, and pivotal to present-day reconciliation. They significantly advance prior methods (Sterne, 2003, Culkpatrick 2023, Bocquillon, 2025) and are permanently exhibited at American Museum and Gardens, UK; Iroquois Museum, New York; NONAM, Switzerland, and worldwide via Bloomberg Connects. They influenced a) The Great Lakes Research Alliance and other North American research groups b) scholars and sound artists working on acoustic cultural heritage (Yildirim, Bursa, Turkey; Barclay, Sunshine Coast, Australia) and c) the Seneca-Iroquois National Museum, who requested their own Soundscape. Co-produced at Johnson Hall Historic Site, New York, as part of ‘Brightening the Covenant Chain: Revealing Cultures of Diplomacy between the Crown, the Iroquois and their Neighbours’, AHRC Standard Research Grant (AH/T006099/2).
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".